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Intragenic translational heterogeneity describes the variation in translation at the level of transcripts for an individual gene. A factor that contributes to this source of variation is the mRNA structure. Both the composition of the thermodynamic ensemble, i.e., the stationary distribution of mRNA structures, and the switching dynamics between those play a role. The effect of the switching dynamics on intragenic translational heterogeneity remains poorly understood. We present a stochastic translation model that accounts for mRNA structure switching and is derived from a Markov model via approximate stochastic filtering. We assess the approximation on various timescales and provide a method to quantify how mRNA structure dynamics contributes to translational heterogeneity. With our approach, we allow quantitative information on mRNA switching from biophysical experiments or coarse-grain molecular dynamics simulations of mRNA structures to be included in gene regulatory chemical reaction network models without an increase in the number of species. Thereby, our model bridges a gap between mRNA structure kinetics and gene expression models, which we hope will further improve our understanding of gene regulatory networks and facilitate genetic circuit design. [ABSTRACT FROM AUTHOR]

In this study, we obtain an exact time-dependent solution of the chemical master equation (CME) of an extension of the two-state telegraph model describing bursty or non-bursty protein expression in the presence of positive or negative autoregulation. Using the method of spectral decomposition, we show that the eigenfunctions of the generating function solution of the CME are Heun functions, while the eigenvalues can be determined by solving a continued fraction equation. Our solution generalizes and corrects a previous time-dependent solution for the CME of a gene circuit describing non-bursty protein expression in the presence of negative autoregulation [Ramos et al., Phys. Rev. E 83, 062902 (2011)]. In particular, we clarify that the eigenvalues are generally not real as previously claimed. We also investigate the relationship between different types of dynamic behavior and the type of feedback, the protein burst size, and the gene switching rate. [ABSTRACT FROM AUTHOR]

AbstractThe transcription factor RUNX1 is a master regulator of hematopoiesis and is frequently mutated in myeloid malignancies. Mutations in its runt homology domain (RHD) frequently disrupt DNA binding and result in loss of RUNX1 function. However, it is not clearly understood how other RUNX1 mutations contribute to disease development. Here, we characterized RUNX1 mutations outside of the RHD. Our analysis of the patient data sets revealed that mutations within the C-terminus frequently occur in hematopoietic disorders. Remarkably, most of these mutations were nonsense or frameshift mutations and were predicted to be exempt from nonsense-mediated messenger RNA decay. Therefore, this class of mutation is projected to produce DNA-binding proteins that contribute to the pathogenesis in a distinct manner. To model this, we introduced the RUNX1R320∗ mutation into the endogenous gene locus and demonstrated the production of RUNX1R320∗ protein. Expression of RUNX1R320∗ resulted in the disruption of RUNX1 regulated processes such as megakaryocytic differentiation, through a transcriptional signature different from RUNX1 depletion. To understand the underlying mechanisms, we used Global RNA Interactions with DNA by deep sequencing (GRID-seq) to examine enhancer-promoter connections. We identified widespread alterations in the enhancer-promoter networks within RUNX1 mutant cells. Additionally, we uncovered enrichment of RUNX1R320∗ and FOXK2 binding at the MYC super enhancer locus, significantly upregulating MYC transcription and signaling pathways. Together, our study demonstrated that most RUNX1 mutations outside the DNA-binding domain are not subject to nonsense-mediated decay, producing protein products that act in concert with additional cofactors to dysregulate hematopoiesis through mechanisms distinct from those induced by RUNX1 depletion.

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

Zygnematophyceae are the algal sisters of land plants. Here we sequenced four genomes of filamentous Zygnematophyceae, including chromosome-scale assemblies for three strains of Zygnema circumcarinatum. We inferred traits in the ancestor of Zygnematophyceae and land plants that might have ushered in the conquest of land by plants: expanded genes for signaling cascades, environmental response, and multicellular growth. Zygnematophyceae and land plants share all the major enzymes for cell wall synthesis and remodifications, and gene gains shaped this toolkit. Co-expression network analyses uncover gene cohorts that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution.

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

UNLABELLED: There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (functional modules), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida. Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE: This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

Loss of Cdx2 in vivo leads to stunted development of the allantois, an extraembryonic mesoderm-derived structure critical for nutrient delivery and waste removal in the early embryo. Here, we investigate how CDX2 dose-dependently influences the gene regulatory network underlying extraembryonic mesoderm development. By engineering human induced pluripotent stem cells (hiPSCs) consisting of wild-type (WT), heterozygous (CDX2-Het), and homozygous null CDX2 (CDX2-KO) genotypes, differentiating these cells in a 2D gastruloid model, and subjecting these cells to single-nucleus RNA and ATAC sequencing, we identify several pathways that are dose-dependently regulated by CDX2 including VEGF and non-canonical WNT. snATAC-seq reveals that CDX2-Het cells retain a WT-like chromatin accessibility profile, suggesting accessibility alone is not sufficient to drive this variability in gene expression. Because the loss of CDX2 or TBXT phenocopy one another in vivo, we compared differentially expressed genes in our CDX2-KO to those from TBXT-KO hiPSCs differentiated in an analogous experiment. This comparison identifies several communally misregulated genes that are critical for cytoskeletal integrity and tissue permeability. Together, these results clarify how CDX2 dose-dependently regulates gene expression in the extraembryonic mesoderm and reveal pathways that may underlie the defects in vascular development and allantoic elongation seen in vivo.

BACKGROUND: Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction. METHODS: A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network. RESULTS: Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets. CONCLUSIONS: This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.

Cardiometabolic disorders (CMD) are a growing public health problem across the world. Among the known cardiometabolic risk factors are compounds that induce endocrine and metabolic dysfunctions, such as endocrine disrupting chemicals (EDCs). To date, how EDCs influence molecular programs and cardiometabolic risks has yet to be fully elucidated, especially considering the complexity contributed by species-, chemical-, and dose-specific effects. Moreover, different experimental and analytical methodologies employed by different studies pose challenges when comparing findings across studies. To explore the molecular mechanisms of EDCs in a systematic manner, we established a data-driven computational approach to meta-analyze 30 human, mouse, and rat liver transcriptomic datasets for 4 EDCs, namely bisphenol A (BPA), bis(2-ethylhexyl) phthalate (DEHP), tributyltin (TBT), and perfluorooctanoic acid (PFOA). Our computational pipeline uniformly re-analyzed pre-processed quality-controlled microarray data and raw RNAseq data, derived differentially expressed genes (DEGs) and biological pathways, modeled gene regulatory networks and regulators, and determined CMD associations based on gene overlap analysis. Our approach revealed that DEHP and PFOA shared stable transcriptomic signatures that are enriched for genes associated with CMDs, suggesting similar mechanisms of action such as perturbations of peroxisome proliferator-activated receptor gamma (PPARγ) signaling and liver gene network regulators VNN1 and ACOT2. In contrast, TBT exhibited highly divergent gene signatures, pathways, network regulators, and disease associations from the other EDCs. In addition, we found that the rat, mouse, and human BPA studies showed highly variable transcriptomic patterns, providing molecular support for the variability in BPA responses. Our work offers insights into the commonality and differences in the molecular mechanisms of various EDCs and establishes a streamlined data-driven workflow to compare molecular mechanisms of environmental substances to elucidate the underlying connections between chemical exposure and disease risks.

Stem cells exist in vitro in a spectrum of interconvertible pluripotent states. Analyzing hundreds of hiPSCs derived from different individuals, we show the proportions of these pluripotent states vary considerably across lines. We discover 13 gene network modules (GNMs) and 13 regulatory network modules (RNMs), which are highly correlated with each other suggesting that the coordinated co-accessibility of regulatory elements in the RNMs likely underlie the coordinated expression of genes in the GNMs. Epigenetic analyses reveal that regulatory networks underlying self-renewal and pluripotency are more complex than previously realized. Genetic analyses identify thousands of regulatory variants that overlapped predicted transcription factor binding sites and are associated with chromatin accessibility in the hiPSCs. We show that the master regulator of pluripotency, the NANOG-OCT4 Complex, and its associated network are significantly enriched for regulatory variants with large effects, suggesting that they play a role in the varying cellular proportions of pluripotency states between hiPSCs. Our work bins tens of thousands of regulatory elements in hiPSCs into discrete regulatory networks, shows that pluripotency and self-renewal processes have a surprising level of regulatory complexity, and suggests that genetic factors may contribute to cell state transitions in human iPSC lines.

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.

Signaling by the extracellular signal-regulated kinase (ERK) pathway controls many cellular processes, including cell division, death, and differentiation. In this second installment of a two-part review, we address the question of how the ERK pathway exerts distinct and context-specific effects on multiple processes. We discuss how the dynamics of ERK activity induce selective changes in gene expression programs, with insights from both experiments and computational models. With a focus on single-cell biosensor-based studies, we summarize four major functional modes for ERK signaling in tissues: adjusting the size of cell populations, gradient-based patterning, wave propagation of morphological changes, and diversification of cellular gene expression states. These modes of operation are disrupted in cancer and other related diseases and represent potential targets for therapeutic intervention. By understanding the dynamic mechanisms involved in ERK signaling, there is potential for pharmacological strategies that not only simply inhibit ERK, but also restore functional activity patterns and improve disease outcomes.

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Divergence of cis-regulatory elements drives species-specific traits1, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains unclear. Here we investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset and mouse using single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome and chromosomal conformation profiles from a total of over 200,000 cells. From these data, we show evidence that divergence of transcription factor expression corresponds to species-specific epigenome landscapes. We find that conserved and divergent gene regulatory features are reflected in the evolution of the three-dimensional genome. Transposable elements contribute to nearly 80% of the human-specific candidate cis-regulatory elements in cortical cells. Through machine learning, we develop sequence-based predictors of candidate cis-regulatory elements in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Finally, we show that epigenetic conservation combined with sequence similarity helps to uncover functional cis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits.

SUMMARY C‐glycosides are a predominant class of flavonoids that demonstrate diverse medical properties and plant physiological functions. The chemical stability, structural diversity, and differential aboveground distribution of these compounds in plants make them ideal protectants. However, little is known about the transcriptional regulatory mechanisms that play these diverse roles in plant physiology. In this study, chard was selected from 69 families for its significantly different flavonoid C‐glycosides distributions between the aboveground and underground parts to investigate the role and regulatory mechanism of flavonoid C‐glycosides in plants. Our results indicate that flavonoid C‐glycosides are affected by various stressors, especially UV‐B. Through cloning and validation of key biosynthetic genes of flavonoid C‐glycosides in chard (BvCGT1), we observed significant effects induced by UV‐B radiation. This finding was further confirmed by resistance testing in BvCGT1 silenced chard lines and in Arabidopsis plants with BvCGT1 overexpression. Yeast one‐hybrid and dual‐luciferase assays were employed to determine the underlying regulatory mechanisms of BvCGT1 in withstanding UV‐B stress. These results indicate a potential regulatory role of BvDof8 and BvDof13 in modulating flavonoid C‐glycosides content, through their influence on BvCGT1. In conclusion, we have effectively demonstrated the regulation of BvCGT1 by BvDof8 and BvDof13, highlighting their crucial role in plant adaptation to UV‐B radiation. Additionally, we have outlined a comprehensive transcriptional regulatory network involving BvDof8 and BvDof13 in response to UV‐B radiation. [ABSTRACT FROM AUTHOR]

α-Tocopherol (α-T) is a vitamin, but the reasons for the α-T requirement are controversial. Given that α-T deficiency was first identified in embryos, we studied to the premier model of vertebrate embryo development, the zebrafish embryo. We developed an α-T-deficient diet for zebrafish and used fish consuming this diet to produce α-T deficient (E−) embryos. We showed that α-T deficiency causes increased lipid peroxidation, leading to metabolic dysregulation that impacts both biochemical and morphological changes at very early stages in development. These changes occur at an early developmental window, which takes place prior to an analogous time to when a human knows she is pregnant. We found that α-T limits the chain reaction of lipid peroxidation and protects metabolic pathways and integrated gene expression networks that control embryonic development. Importantly, not only is α-T critical during early development, but the neurodevelopmental process is highly dependent on α-T trafficking by the α-T transfer protein (TTPa). Data from both gene expression and evaluation of the metabolome in E− embryos suggest that the activity of the mechanistic Target of Rapamycin (mTOR) signaling pathway is dysregulated—mTOR is a master regulatory mechanism, which controls both metabolism and neurodevelopment. Our findings suggest that TTPa is needed not only for regulation of plasma α-T in adults but is a key regulator during embryogenesis. [Display omitted] • α-Tocopherol (α-T) is a controversial vitamin. • α-T deficiency causes increased lipid peroxidation. • α-T deficiency impacts both biochemical and morphological changes. • α-T protects metabolic pathways and integrated gene expression networks. • α-T in adults but is a key regulator during embryogenesis. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is associated with significant risk factors such as polycystic ovarian syndrome (PCOS) and sedentary behavior. In our study, we aim to employ machine learning algorithms to investigate the potential molecular processes that underlie their interaction and explore their respective roles in the diagnosis and immunotherapy of EC. The GEO database provides access to microarray data, which was utilized in this study to identify gene expression modules associated with PCOS and sedentary behavior, using weighted gene expression network analysis (WGCNA). Cluego software was then employed to investigate the energy enrichment of shared pathways in both PCOS and sedentary individuals, and differential gene analysis was used to confirm another two databases. The miRNAs–mRNAs controlled network was constructed to verify the pathway. The immune-related factors of the shared pathway in EC were then analyzed. Finally, to validate our findings, we conducted cell experiments using EC cell lines (AN3CA, KLE, Ishikawa, RL95-2, and HEC-1A). We found that increased intracellular aromatic compound anabolism is a common feature of both PCOS and sedentary individuals. We then developed a disease pathway model that was based on the common genetic characteristics of PCOS and sedentary behavior. We utilized pathway typing in EC samples and found a significant survival difference between the two subgroups, with the upregulated expression type exhibiting an immune-hot phenotype. Finally, the experimental results confirmed the expression of the hub gene (NAA15) in EC. The findings of our study suggest that genes related to the intracellular aromatic compound metabolic pathway can be used for immunotherapy of EC. [ABSTRACT FROM AUTHOR]

The present study aimed to identify the selection signature associated with temperature adaptation in Iranian sheep breeds raised in cold and hot environments. The Illumina HD ovine SNP600K BeadChip genomic arrays were utilized to analyze 114 animals from eight Iranian sheep breeds, namely Ghezel, Afshari, Shall, Sanjabi, Lori-Bakhtiari, Karakul, Kermani, and Balochi. All animals were classified into two groups: cold-weather breeds and hot-weather breeds, based on the environments to which they are adapted and the regions where they have been raised for many years. The unbiased FST (Theta) and hapFLK tests were used to identify the selection signatures. The results revealed five genomic regions on chromosomes 2, 10, 11, 13, and 14 using the FST test, and three genomic regions on chromosomes 10, 14, and 15 using the hapFLK test to be under selection in cold and hot groups. Further exploration of these genomic regions revealed that most of these regions overlapped with genes previously identified to affect cold and heat stress, nervous system function, cell division and gene expression, skin growth and development, embryo and skeletal development, adaptation to hypoxia conditions, and the immune system. These regions overlapped with QTLs that had previously been identified as being associated with various important economic traits, such as body weight, skin color, and horn characteristics. The gene ontology and gene network analyses revealed significant pathways and networks that distinguished Iranian cold and hot climates sheep breeds from each other. We identified positively selected genomic regions in Iranian sheep associated with pathways related to cell division, biological processes, cellular responses to calcium ions, metal ions and inorganic substances. This study represents the initial effort to identify selective sweeps linked to temperature adaptation in Iranian indigenous sheep breeds. It may provide valuable insights into the genomic regions involved in climate adaptation in sheep. [ABSTRACT FROM AUTHOR]

Bud sports in fruit crops often result in new cultivars with unique traits, such as distinct fruit size and color, compared to their parent plants. This study investigates the phenotypic differences and gene expression patterns in Tonewase and Ohtanenashi persimmon bud sports compared to those in their parent, Hiratanenashi, based on RNA-seq data. Tonewase is characterized by early maturation, whereas Ohtanenashi is noted for its larger fruit size. Despite the importance of these traits in determining fruit quality, their molecular bases in persimmons have been understudied. We compared transcriptome-level differences during fruit development between the bud sport samples and their original cultivar. Comprehensive transcriptome analyses identified 15,814 differentially expressed genes and 26 modules via weighted gene coexpression network analysis. Certain modules exhibited unique expression patterns specific to the different cultivars during fruit development, likely contributing to the phenotypic differences observed. Specifically, M11, M16, M22, and M23 were uniquely expressed in Tonewase, whereas M13 and M24 showed distinct patterns in Ohtanenashi. By focusing on genes with distinct expression profiles, we aimed to uncover the genetic basis of cultivar-specific traits. Our findings suggest that changes in the expression of genes associated with ethylene and cell wall pathways may drive Tonewase's earlier maturation, whereas genes related to the cell cycle within the M24 module appear crucial for Ohtanenashi's larger fruit size. Additionally, ethylene and transcription factor genes within this module may contribute to the increased fruit size observed. This study elucidates the differences in transcriptomic changes during fruit development between the two bud sport samples and their original cultivar, enhancing our understanding of the genetic determinants influencing fruit size and maturation. [ABSTRACT FROM AUTHOR]

Background: Our study aimed to identify potential specific biomarkers for osteoarthritis (OA) and assess their relationship with immune infiltration. Methods: We utilized data from GSE117999, GSE51588, and GSE57218 as training sets, while GSE114007 served as a validation set, all obtained from the GEO database. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed to identify hub modules and potential functions of genes. We subsequently screened for potential OA biomarkers within the differentially expressed genes (DEGs) of the hub module using machine learning methods. The diagnostic accuracy of the candidate genes was validated. Additionally, single gene analysis and ssGSEA was performed. Then, we explored the relationship between biomarkers and immune cells. Lastly, we employed RT-PCR to validate our results. Results: WGCNA results suggested that the blue module was the most associated with OA and was functionally associated with extracellular matrix (ECM)-related terms. Our analysis identified ALB, HTRA1, DPT, MXRA5, CILP, MPO, and PLAT as potential biomarkers. Notably, HTRA1, DPT, and MXRA5 consistently exhibited increased expression in OA across both training and validation cohorts, demonstrating robust diagnostic potential. The ssGSEA results revealed that abnormal infiltration of DCs, NK cells, Tfh, Th2, and Treg cells might contribute to OA progression. HTRA1, DPT, and MXRA5 showed significant correlation with immune cell infiltration. The RT-PCR results also confirmed these findings. Conclusions: HTRA1, DPT, and MXRA5 are promising biomarkers for OA. Their overexpression strongly correlates with OA progression and immune cell infiltration. [ABSTRACT FROM AUTHOR]

Summary Bamboo with its remarkable growth rate and economic significance, offers an ideal system to investigate the molecular basis of organogenesis in rapidly growing plants, particular in monocots, where gene regulatory networks governing the maintenance and differentiation of shoot apical and intercalary meristems remain a subject of controversy. We employed both spatial and single‐nucleus transcriptome sequencing on 10× platform to precisely dissect the gene functions in various tissues and early developmental stages of bamboo shoots. Our comprehensive analysis reveals distinct cell trajectories during shoot development, uncovering critical genes and pathways involved in procambium differentiation, intercalary meristem formation, and vascular tissue development. Spatial and temporal expression patterns of key regulatory genes, particularly those related to hormone signaling and lipid metabolism, strongly support the hypothesis that intercalary meristem origin from surrounded parenchyma cells. Specific gene expressions in intercalary meristem exhibit regular and dispersed distribution pattern, offering clues for understanding the intricate molecular mechanisms that drive the rapid growth of bamboo shoots. The single‐nucleus and spatial transcriptome analysis reveal a comprehensive landscape of gene activity, enhancing the understanding of the molecular architecture of organogenesis and providing valuable resources for future genomic and genetic studies relying on identities of specific cell types. [ABSTRACT FROM AUTHOR]

Heart failure (HF) is a terminal condition of multiple cardiovascular disorders. Cancer is a deadly disease worldwide. The relationship between HF and cancer remains poorly understood. The Gene Expression Omnibus database was used to download the RNA sequencing data of 356 patients with hypertrophic cardiomyopathy-induced HF and non-HF. A co-expression network was established through the weighted correlation network analysis (WGCNA) to identify hub genes of HF and cancer. Cox risk analysis was performed to predict the prognostic risks of HF hub genes in pan-cancer. HF was linked to immune response pathway by the analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A positive correlation was observed between the expression levels of 4 hub genes and the infiltration of CD8+T-cells in pan-cancer. 4 hub genes were identified as beneficial prognostic factors in several cancers. Western blotting and real-time polymerase chain reaction validated the high expression of GZMM, NKG7, and ZAP70 in both mice and patients with HF compared to control groups. Our study highlights the shared immune pathogenesis of HF and cancer and provides valuable insights for developing novel therapeutic strategies, offering new opportunities for improving the management and treatment outcomes of both HF and cancer. [ABSTRACT FROM AUTHOR]

Phenotypic plasticity displayed by an animal in response to different environmental conditions is supposedly crucial for its survival and reproduction. The female adults of some ant lineages display phenotypic plasticity related to reproductive role. In pharaoh ant queens, insemination induces substantial physiological/behavioral changes and implicates remarkable gene regulatory network (GRN) shift in the brain. Here, we report a neuropeptide neuroparsin A (NPA) showing a conserved expression pattern associated with reproductive activity across ant species. Knock-down of NPA in unmated queen enhances ovary activity, whereas injection of NPA peptide in fertilized queen suppresses ovary activity. We found that NPA mainly affected the downstream gene JHBP in the ovary, which is positively regulated by NPA and suppression of which induces elevated ovary activity, and shadow which is negatively regulated by NPA. Furthermore, we show that NPA was also employed into the brain–ovary axis in regulating the worker reproductive changes in other distantly related species, such as Harpegnathos venator ants. Some female ants display phenotypic plasticity related to reproduction, such as the transition between gyne and queen castes. This study shows that the neuropeptide neuroparsin A mediates substantial physiological changes in response to insemination across ant species, acting via ovarian endocrine pathways. [ABSTRACT FROM AUTHOR]

Ligand–receptor systems, covalent modification cycles, and transcriptional networks are the fundamental components of cell signaling and gene expression systems. While their behavior in reaching a steady-state regime under step-like stimulation is well understood, their response under repetitive stimulation, particularly at early time stages is poorly characterized. Yet, early-stage responses to external inputs are arguably as informative as late-stage ones. In simple systems, a periodic stimulation elicits an initial transient response, followed by periodic behavior. Transient responses are relevant when the stimulation has a limited time span, or when the stimulated component's timescale is slow as compared to the timescales of the downstream processes, in which case the latter processes may be capturing only those transients. In this study, we analyze the frequency response of simple motifs at different time stages. We use dose-conserved pulsatile input signals and consider different metrics versus frequency curves. We show that in ligand–receptor systems, there is a frequency preference response in some specific metrics during the transient stages, which is not present in the periodic regime. We suggest this is a general system-level mechanism that cells may use to filter input signals that have consequences for higher order circuits. In addition, we evaluate how the described behavior in isolated motifs is reflected in similar types of responses in cascades and pathways of which they are a part. Our studies suggest that transient frequency preferences are important dynamic features of cell signaling and gene expression systems, which have been overlooked. [ABSTRACT FROM AUTHOR]

Plants, being sessile organisms, constantly need to respond to environmental stresses, often leading to the accumulation of reactive oxygen species (ROS). While ROS can be harmful, they also act as second messengers guiding plant growth and stress responses. Because chloroplasts are sensitive to environmental changes and are both a source and a target of ROS during stress conditions, they are important in conveying environmental changes to the nucleus, where acclimation responses are coordinated to maintain organellar and overall cellular homeostasis. ANAC102 has previously been established as a regulator of β-cyclocitral-mediated chloroplast-to-nucleus signaling, protecting plants against photooxidative stress. However, debates persist about where ANAC102 is located—in chloroplasts or in the nucleus. Our study, utilizing the genomic ANAC102 sequence driven by its native promoter, establishes ANAC102 primarily as a nuclear protein, lacking a complete N-terminal chloroplast-targeting peptide. Moreover, our research reveals the sensitivity of plants overexpressing ANAC102 to severe superoxide-induced chloroplast oxidative stress. Transcriptome analysis unraveled a dual role of ANAC102 in negatively and positively regulating genome-wide transcriptional responses to chloroplast oxidative stress. Through the integration of published data and our own study, we constructed a comprehensive transcriptional network, which suggests that ANAC102 exerts direct and indirect control over transcriptional responses through downstream transcription factor networks, providing deeper insights into the ANAC102-mediated regulatory landscape during oxidative stress. [ABSTRACT FROM AUTHOR]

Light is crucial for plants and serves as a signal for modulating their growth. Under shade, where red to far-red light ratio is low, plants exhibit shade avoidance responses (SAR). LONG HYPOCOTYL IN FAR-RED 1 (HFR1) and ELONGATED HYPOCOTYL 5 (HY5) are known to be negative regulators of SAR and physically interact with one another. However, transcriptional regulatory network underlying SAR by these two transcription factors has not been explored. Here, we performed organ-specific transcriptome analyses of Arabidopsis thaliana hfr1-5, hy5-215 and hfr1hy5 to identify genes that are co-regulated by HFR1 and HY5 in hypocotyls and cotyledons. Genes co-regulated by HFR1 and HY5 were enriched in various processes related to cell wall modification and chlorophyll biosynthesis in hypocotyls. Phytohormone (abscisic acid and jasmonic acid) and light responses were significantly regulated by HFR1 and HY5 in both organs, though it is more prominent under shade in cotyledons. HFR1 and HY5 also differentially regulate the expression of the cell wall-related genes for xyloglucan endotransglucosylase/hydrolase, expansin, arabinogalactan protein and class III peroxidase depending on the organs. Furthermore, HFR1 and HY5 cooperatively regulated hypocotyl responsiveness to shade through auxin metabolism. Together, our study illustrates the importance of the HFR1-HY5 module in regulating organ-specific shade responses in Arabidopsis. [ABSTRACT FROM AUTHOR]

Background: Atopic dermatitis (AD) is inflammatory disease. So far, therapeutic mechanism of Runfuzhiyang powder on AD remains to be studied. This study aimed to mine key biomarkers to explore potential molecular mechanism for AD incidence and Runfuzhiyang powder treatment. Methods: The control group, AD group, treat group (AD mice treated with Runfuzhiyang powder were utilized for studying. Differentially expressed ADrelated genes were acquired by intersecting of key module genes related to control group, AD group and treatment group which were screened by WGCNA and AD-related differentially expressed genes (DEGs). KEGG and GO analyses were further carried out. Next, LASSO regression analysis was utilized to screen feature genes. The ROC curves were applied to validate the diagnostic ability of feature genes to obtain AD-related biomarkers. Then protein-protein interaction (PPI) network, immune infiltration analysis and single-gene gene set enrichment analysis (GSEA) were presented. Finally, TF-mRNA-lncRNA and drug-gene networks of biomarkers were constructed. Results: 4 AD-related biomarkers (Ddit4, Sbf2, Senp8 and Zfp777) were identified in AD groups compared with control group and treat group by LASSO regression analysis. The ROC curves revealed that four biomarkers had good distinguishing ability between AD group and control group, as well as AD group and treatment group. Next, GSEA revealed that pathways of E2F targets, KRAS signaling up and inflammatory response were associated with 4 biomarkers. Then, we found that Ddit4, Sbf2 and Zfp777 were significantly positively correlated with M0 Macrophage, and were significantly negatively relevant to Resting NK. Senp8 was the opposite. Finally, a TF-mRNA-lncRNA network including 200 nodes and 592 edges was generated, and 20 drugs targeting SENP8 were predicted. Conclusion: 4 AD-related and Runfuzhiyang powder treatment-related biomarkers (Ddit4, Sbf2, Senp8 and Zfp777) were identified, which could provide a new idea for targeted treatment and diagnosis of AD. [ABSTRACT FROM AUTHOR]

HMGA1 is an abundant non-histone chromatin protein that has been implicated in embryonic development, cancer, and cellular senescence, but its specific role remains elusive. Here, we combine functional genomics approaches with graph theory to investigate how HMGA1 genomic deposition controls high-order chromatin networks in an oncogene-induced senescence model. While the direct role of HMGA1 in gene activation has been described previously, we find little evidence to support this. Instead, we show that the heterogeneous linear distribution of HMGA1 drives a specific 3D chromatin organization. HMGA1-dense loci form highly interactive networks, similar to, but independent of, constitutive heterochromatic loci. This, coupled with the exclusion of HMGA1-poor chromatin regions, leads to coordinated gene regulation through the repositioning of genes. In the absence of HMGA1, the whole process is largely reversed, but many regulatory interactions also emerge, amplifying the inflammatory senescence-associated secretory phenotype. Such HMGA1-mediated fine-tuning of gene expression contributes to the heterogeneous nature of senescence at the single-cell level. A similar 'buffer' effect of HMGA1 on inflammatory signalling is also detected in lung cancer cells. Our study reveals a mechanism through which HMGA1 modulates chromatin compartmentalization and gene regulation in senescence and beyond. HMGA1 helps regulate the topology of the chromatin network, supporting compartmentalization. Here, Olan et al. show that, in oncogene-induced senescence, genes are included or excluded from HMGA1 cores, suggesting HMGA1 has a fine-tuning role. [ABSTRACT FROM AUTHOR]

Objective: Gastric cancer (GC) is one of the most common malignancies worldwide and it is considered the fourth most common cause of cancer death. This study aimed to find critical genes/pathways in GC pathogenesis to be used as biomarkers or therapeutic targets. Methods: Differentially expressed genes were explored between human gastric cancerous and noncancerous tissues, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment analyses were done. Hub genes were identified based on the protein–protein interaction network constructed in the STRING database with Cytoscape software. The hub genes were selected for further investigation using GEPIA2 and DrugBank databases. Results: Ten overexpressed hub genes in GC were identified in the current study, including FN1, TP53, IL-6, CXCL5, ELN, ADAMTS2, WISP1, MMP2, CTGF, and THBS1. The study demonstrated the PI3K-Akt pathway's central involvement in GC, with pronounced alterations in essential components. Survival analysis revealed significant correlations between CTGF, FN1, IL-6, THBS1, and WISP1 overexpression and reduced overall survival times in GC patients. Conclusion: A mutual interplay emerged, where PI3K-Akt signaling could upregulate certain genes, forming feedback loops and intensifying cancer phenotypes. The interconnected overexpression of genes and the PI3K-Akt pathway fosters gastric tumorigenesis, suggesting therapeutic potential. DrugBank analysis identified limited FDA-approved drugs, advocating for further exploration while targeting these hub genes could reshape GC treatment. The identified genes could be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC, but further clinical validation is required. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, characterized by high rates of angiogenesis and immune evasion. Paraspeckle genes, involved in gene regulation and RNA metabolism, have recently been linked to tumor progression. This study aims to elucidate the relationship between paraspeckle genes and HCC prognosis, focusing on SFPQ, DDX39B, and UBAP2. Methods: We analyzed HCC (LIHC) and prostate cancer (PRAD) samples from the TCGA database to explore the correlation between paraspeckle genes and angiogenesis. We conducted unsupervised clustering, risk scoring, and survival analysis to identify distinct patient groups and their clinical outcomes. Gene expression data were used to perform differential analysis and Gene Ontology (GO) enrichment. Results: Our analysis identified significant correlations between paraspeckle genes and angiogenesis across multiple cancer types. Elevated expression levels of SFPQ, DDX39B, and UBAP2 were associated with poor prognosis in HCC patients, and all of them has statistical significance. Unsupervised clustering of HCC samples based on paraspeckle gene expression revealed two distinct clusters, with high-risk patients exhibiting stronger immune suppression and tumor immune evasion. GO enrichment highlighted critical pathways related to angiogenesis and immune regulation. Additionally, a risk scoring model based on these genes effectively distinguished high-risk and low-risk patient groups, providing valuable prognostic insights. Conclusion: This study demonstrates that SFPQ, DDX39B, and UBAP2 are significantly associated with poor prognosis in HCC, likely due to their roles in promoting angiogenesis and immune suppression. These findings highlight the potential of paraspeckle genes as prognostic biomarkers and therapeutic targets, offering new avenues for personalized treatment strategies in HCC. Further research into their functional mechanisms and clinical applicability is crucial for advancing HCC treatment and improving patient outcomes. [ABSTRACT FROM AUTHOR]

Discontinuous transcription is evolutionarily conserved and a fundamental feature of gene regulation; yet, the exact mechanisms underlying transcriptional bursting are unresolved. Analyses of bursting transcriptome-wide have focused on the role of cis-regulatory elements, but other factors that regulate this process remain elusive. We applied mathematical modeling to single-cell RNA sequencing data to infer bursting dynamics transcriptome-wide under multiple conditions to identify possible molecular mechanisms. We found that Mediator complex subunit 26 (MED26) primarily regulates frequency, MYC regulates burst size, while cohesin and Bromodomain-containing protein 4 (BRD4) can modulate both. Despite comparable effects on RNA levels among these perturbations, acute depletion of MED26 had the most profound impact on the entire gene regulatory network, acting downstream of chromatin spatial architecture and without affecting TATA box-binding protein (TBP) recruitment. These results indicate that later steps in the initiation of transcriptional bursts are primary nodes for integrating gene networks in single cells. [ABSTRACT FROM AUTHOR]

Objective To explore the underlying mechanisms of ulcerative colitis (UC) pathogenesis using single-cell transcriptomic bioinformatics approaches. Methods Single-cell transcriptome dataset GSE125527, consisting of UC samples, was downloaded from a high-throughput Gene Expression Omnibus for this study. Data filtering and normalization were conducted using the Seurat package in R. Cells with similar gene expression profiles were clustered and annotated. Cell subgroups associated with UC pathogenesis were identified, and differentially expressed genes (DEGs) were extracted. Enrichment analysis of these DEGs was performed to uncover potential signaling pathways involved in UC. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was applied to the cell subgroup with the greatest differences to select UC-related gene modules. Additional datasets, GSE36807, GSE42911, GSE65114, and GSE6731, were downloaded for DEG screening. By integrating single-cell DEGs with UC-related gene modules, core genes involved in UC pathogenesis were identified. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of these core genes for UC pathogenesis. The expression of core genes was validated in a UC rat model. Results After filtering, 18 642 cells from UC samples and 4 298 cells from normal colonic tissue were obtained and clustered into ten subgroups, with a high proportion of B cells in UC samples. Eighty-one upregulated and twenty-one downregulated DEGs related to mononuclear cells were identified. Significant enrichment of DEGs was observed in pathways related to tumor necrosis factor-alpha, nuclear factor Kappa B, interleukin-2, signal transducer and activator of transcription 5, and interferon-alpha. Two UC-related gene modules were identified through hdWGCNA. After screening and validation, LAPTM5 was confirmed as a core gene in UC pathogenesis. Compared to control rats, LAPTM5 expression was significantly higher in the colonic tissues of UC model rats. Conclusions There are significant differences in cell distribution between UC and normal colonic tissues, with B cells closely related to UC pathogenesis, serving as potential targets for prevention and treatment. LAPTM5 is identified as a potential core gene in UC pathogenesis. [ABSTRACT FROM AUTHOR]

Super‐enhancer‐associated transcription factor networks define cell identity in neuroblastoma (NB). Dysregulation of these transcription factors contributes to the initiation and maintenance of NB by enforcing early developmental identity states. We report that the class I basic helix–loop–helix (bHLH) transcription factor 4 (TCF4; also known as E2‐2) is a critical NB dependency gene that significantly contributes to these identity states through heterodimerization with cell‐identity‐specific bHLH transcription factors. Knockdown of TCF4 significantly induces apoptosis in vitro and inhibits tumorigenicity in vivo. We used genome‐wide expression profiling, TCF4 chromatin immunoprecipitation sequencing (ChIP‐seq) and TCF4 immunoprecipitation–mass spectrometry to determine the role of TCF4 in NB cells. Our results, along with recent findings in NB for the transcription factors T‐box transcription factor TBX2, heart‐ and neural crest derivatives‐expressed protein 2 (HAND2) and twist‐related protein 1 (TWIST1), propose a role for TCF4 in regulating forkhead box protein M1 (FOXM1)/transcription factor E2F‐driven gene regulatory networks that control cell cycle progression in cooperation with N‐myc proto‐oncogene protein (MYCN), TBX2, and the TCF4 dimerization partners HAND2 and TWIST1. Collectively, we showed that TCF4 promotes cell proliferation through direct transcriptional regulation of the c‐MYC/MYCN oncogenic program that drives high‐risk NB. Mechanistically, our data suggest the novel finding that TCF4 acts to support MYC activity by recruiting multiple factors known to regulate MYC function to sites of colocalization between critical NB transcription factors, TCF4 and MYC oncoproteins. Many of the TCF4‐recruited factors are druggable, giving insight into potential therapies for high‐risk NB. This study identifies a new function for class I bHLH transcription factors (e.g., TCF3, TCF4, and TCF12) that are important in cancer and development. [ABSTRACT FROM AUTHOR]

Cell fate specification occurs along invariant species-specific trajectories that define the animal body plan. This process is controlled by gene regulatory networks that regulate the expression of the limited set of transcription factors encoded in animal genomes. Here we globally assess the spatial expression of ~90% of expressed transcription factors during sea urchin development from embryo to larva to determine the activity of gene regulatory networks and their regulatory states during cell fate specification. We show that >200 embryonically expressed transcription factors together define >70 cell fates that recapitulate the morphological and functional organization of this organism. Most cell fate-specific regulatory states consist of ~15–40 transcription factors with similarity particularly among functionally related cell types regardless of developmental origin. Temporally, regulatory states change continuously during development, indicating that progressive changes in regulatory circuit activity determine cell fate specification. We conclude that the combinatorial expression of transcription factors provides molecular definitions that suffice for the unique specification of cell states in time and space during embryogenesis. Gene regulatory networks (GRNs) control developmental processes that define the body plan of multicellular animals. In this study, Valencia and Peter monitored the activity of GRNs during embryogenesis in sea urchins by determining the spatial and temporal changes in the expression of over 200 transcription factors. [ABSTRACT FROM AUTHOR]

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is being increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. In response, MOCHA (Model-based single cell Open CHromatin Analysis) presents major advances over existing analysis tools, including: 1) improving identification of sample-specific open chromatin, 2) statistical modeling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) modules for inferring temporal gene regulatory networks from longitudinal data. These advances, in addition to open chromatin analyses, provide a robust framework after quality control and cell labeling to study gene regulatory programs in human disease. We benchmark MOCHA with four state-of-the-art tools to demonstrate its advances. We also construct cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data. Analytical gaps limit the utility of scATAC-seq for studying gene regulatory programs in human disease. Here, authors describe MOCHA, a robust analytical tool with advanced statistical modelling that enables functional genomic inference in large cross-sectional and longitudinal human studies. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence reveals the involvement of mitochondria and macrophage polarisation in tumourigenesis and progression. This study aimed to establish mitochondria and macrophage polarisation-associated molecular signatures to predict prognosis in gastric cancer (GC) by single-cell and transcriptional data. Methods: Initially, candidate genes associated with mitochondria and macrophage polarisation were identified by differential expression analysis and weighted gene co-expression network analysis. Subsequently, candidate genes were incorporated in univariateCox analysis and LASSO to acquire prognostic genes in GC, and risk model was created. Furthermore, independent prognostic indicators were screened by combining risk score with clinical characteristics, and a nomogram was created to forecast survival in GC patients. Further, in single-cell data analysis, cell clusters and cell subpopulations were yielded, followed by the completion of pseudo-time analysis. Furthermore, a more comprehensive immunological analysis was executed to uncover the relationship between GC and immunological characteristics. Ultimately, expression level of prognostic genes was validated through public datasets and qRT-PCR. Results: A risk model including six prognostic genes (GPX3, GJA1, VCAN, RGS2, LOX, and CTHRC1) associated with mitochondria and macrophage polarisation was developed, which was efficient in forecasting the survival of GC patients. The GC patients were categorized into high-/low-risk subgroups in accordance with median risk score, with the high-risk subgroup having lower survival rates. Afterwards, a nomogram incorporating risk score and age was generated, and it had significant predictive value for predicting GC survival with higher predictive accuracy than risk model. Immunological analyses revealed showed higher levels of M2 macrophage infiltration in high-risk subgroup and the strongest positive correlation between risk score and M2 macrophages. Besides, further analyses demonstrated a better outcome for immunotherapy in low-risk patients. In single-cell and pseudo-time analyses, stromal cells were identified as key cells, and a relatively complete developmental trajectory existed for stromal C1 in three subclasses. Ultimately, expression analysis revealed that the expression trend of RGS2, GJA1, GPX3, and VCAN was consistent with the results of the TCGAGC dataset. Conclusion: Our findings demonstrated that a novel prognostic model constructed in accordance with six prognostic genes might facilitate the improvement of personalised prognosis and treatment of GC patients. [ABSTRACT FROM AUTHOR]

The development of the retina is under tight temporal and spatial control. To gain insights into the molecular basis of this process, we generate a single-nuclei dual-omic atlas of the human developing retina with approximately 220,000 nuclei from 14 human embryos and fetuses aged between 8 and 23-weeks post-conception with matched macular and peripheral tissues. This atlas captures all major cell classes in the retina, along with a large proportion of progenitors and cell-type-specific precursors. Cell trajectory analysis reveals a transition from continuous progression in early progenitors to a hierarchical development during the later stages of cell type specification. Both known and unrecorded candidate transcription factors, along with gene regulatory networks that drive the transitions of various cell fates, are identified. Comparisons between the macular and peripheral retinae indicate a largely consistent yet distinct developmental pattern. This atlas offers unparalleled resolution into the transcriptional and chromatin accessibility landscapes during development, providing an invaluable resource for deeper insights into retinal development and associated diseases. The authors build an atlas of the human retinal development, using approximately 220,000 nuclei from 14 embryos and fetuses (8–23 weeks post-conception). The study reveals major cell classes, key transcription factors, and differences in the development of macular and peripheral retina. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively. Methods: Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data. Results: We found that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue and tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also discovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS. Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database. Conclusions: These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management. Plain English Summary: Lung adenocarcinoma (LUAD) is a disease that affects males and females differently. Biological sex not only influences chances of developing the disease, but also how the disease progresses and how effective various therapies may be. We analyzed sex-specific gene regulatory networks consisting of transcription factors and the genes they regulate in both healthy lung tissue and in LUAD and identified sex-biased differences. We found that genes associated with cell proliferation, immune response, and drug metabolism are differentially targeted by transcription factors between males and females. We also found that several genes that are drug targets in LUAD, are also regulated differently between males and females. Importantly, these differences are also influenced by an individual's smoking history. Extending our analysis using a drug repurposing tool, we found candidate drugs with evidence that they might work better for one sex or the other. These results demonstrate that considering the differences in gene regulation between males and females will be essential if we are to develop precision medicine strategies for preventing and treating LUAD. Highlights: Genes associated with cell proliferation, immune response, and drug metabolism are differentially targeted by transcription factors between males and females in healthy lung tissue and lung adenocarcinoma samples. Gene regulatory differences between males and females are also affected by an individual's history of smoking. Significant sex bias exists in transcription factor targeting patterns of several clinically actionable oncogenes and tumor suppressor genes including AKT2 and KRAS. Analyzing sex-biased gene regulatory networks in lung adenocarcinoma identified small-molecule cancer therapeutics with potential sex-specific efficacy, underscoring the importance of considering sex-specific gene regulation in precision medicine. [ABSTRACT FROM AUTHOR]

p53 is a star protein in cancer biology, and its oscillatory dynamics have received much attention. However, most studies do not consider spatial effects. For this reason, we introduce the diffusion term in a classical p53-Mdm2 autoregulatory loop model. First, the equation is linearized at the positive equilibrium so that we can discuss the local asymptotic stability of this equilibrium. By taking the delay as a bifurcation parameter, the positive equilibrium transitions from stable to unstable and occurs a Hopf bifurcation. Second, we determine the stability of the bifurcating period solution by using a multiple time scales approach. Finally, the theoretical analysis is verified by the numerical simulations. Our study contributes to providing new insight in the controlling of p53 dynamics. [ABSTRACT FROM AUTHOR]

Background: A key step in nervous system development involves the coordinated control of neural progenitor specification and positioning. A long-standing model for the vertebrate CNS postulates that transient anatomical compartments – known as neuromeres – function to position neural progenitors along the embryonic anteroposterior neuraxis. Such neuromeres are apparent in the embryonic hindbrain – that contains six rhombomeres with morphologically apparent boundaries – but other neuromeres lack clear morphological boundaries and have instead been defined by different criteria, such as differences in gene expression patterns and the outcomes of transplantation experiments. Accordingly, the caudal hindbrain (CHB) posterior to rhombomere (r) 6 has been variably proposed to contain from two to five 'pseudo-rhombomeres', but the lack of comprehensive molecular data has precluded a detailed definition of such structures. Methods: We used single-cell Multiome analysis, which allows simultaneous characterization of gene expression and chromatin state of individual cell nuclei, to identify and characterize CHB progenitors in the developing zebrafish CNS. Results: We identified CHB progenitors as a transcriptionally distinct population, that also possesses a unique profile of accessible transcription factor binding motifs, relative to both r6 and the spinal cord. This CHB population can be subdivided along its dorsoventral axis based on molecular characteristics, but we do not find any molecular evidence that it contains multiple pseudo-rhombomeres. We further observe that the CHB is closely related to r6 at the earliest embryonic stages, but becomes more divergent over time, and that it is defined by a unique gene regulatory network. Conclusions: We conclude that the early CHB represents a single neuromere compartment that cannot be molecularly subdivided into pseudo-rhombomeres and that it may share an embryonic origin with r6. [ABSTRACT FROM AUTHOR]

Background: Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disease. However, there is a paucity of studies that reflect the available biomarkers from separate gene expression profiles in PAH. Methods: The GSE131793 and GSE113439 datasets were combined for subsequent analyses, and batch effects were removed. Bioinformatic analysis was then performed to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and a protein-protein interaction (PPI) network analysis were then used to further filter the hub genes. Functional enrichment analysis of the intersection genes was performed using Gene Ontology (GO), Disease Ontology (DO), Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA). The expression level and diagnostic value of hub gene expression in pulmonary arterial hypertension (PAH) patients were also analyzed in the validation datasets GSE53408 and GSE22356. In addition, target gene expression was validated in the lungs of a monocrotaline (MCT)-induced pulmonary hypertension (PH) rat model and in the serum of PAH patients. Results: A total of 914 differentially expressed genes (DEGs) were identified, with 722 upregulated and 192 downregulated genes. The key module relevant to PAH was selected using WGCNA. By combining the DEGs and the key module of WGCNA, 807 genes were selected. Furthermore, protein–protein interaction (PPI) network analysis identified HSP90AA1, CD8A, HIF1A, CXCL8, EPRS1, POLR2B, TFRC, and PTGS2 as hub genes. The GSE53408 and GSE22356 datasets were used to evaluate the expression of TFRC, which also showed robust diagnostic value. According to GSEA enrichment analysis, PAH-relevant biological functions and pathways were enriched in patients with high TFRC levels. Furthermore, TFRC expression was found to be upregulated in the lung tissues of our experimental PH rat model compared to those of the controls, and the same conclusion was reached in the serum of the PAH patients. Conclusions: According to our bioinformatics analysis, the observed increase of TFRC in the lung tissue of human PAH patients, as indicated by transcriptomic data, is consistent with the alterations observed in PAH patients and rodent models. These data suggest that TFRC may serve as a potential biomarker for PAH. [ABSTRACT FROM AUTHOR]

Background: The male sterile lines are an important foundation for heterosis utilization in wheat (Triticum aestivum L.). Thereinto, pollen development is one of the indispensable processes of wheat reproductive development, and its fertility plays an important role in wheat heterosis utilization, and are usually influencing by genes. However, these key genes and their regulatory networks during pollen abortion are poorly understood in wheat. Results: DEFECTIVE IN TAPETAL DEVELOPMENT AND FUNCTION 1 (TDF1) is a member of the R2R3-MYB family and has been shown to be essential for early tapetal layer development and pollen grain fertility in rice (Oryza sativa L.) and Arabidopsis thaliana. In order to clarify the function of TDF1 in wheat anthers development, we used OsTDF1 gene as a reference sequence and homologous cloned wheat TaTDF1 gene. TaTDF1 is localized in the nucleus. The average bolting time of Arabidopsis thaliana overexpressed strain (TaTDF1-OE) was 33 d, and its anther could be colored normally by Alexander staining solution, showing red. The dominant Mosaic suppression silence-line (TaTDF1-EAR) was blue-green in color, and the anthers were shrimpy and thin. The TaTDF1 interacting protein (TaMAP65) was confirmed using Yeast Two-Hybrid Assay (Y2H) and Bimolecular-Fluorescence Complementation (BiFC) experiments. The results showed that downregulated expression of TaTDF1 and TaMAP65 could cause anthers to be smaller and shrunken, leading to pollen abortion in TaTDF1 wheat plants induced by virus-induced gene-silencing technology. The expression pattern of TaTDF1 was influenced by TaMAP65. Conclusions: Thus, systematically revealing the regulatory mechanism of wheat TaTDF1 during anther and pollen grain development may provide new information on the molecular mechanism of pollen abortion in wheat. [ABSTRACT FROM AUTHOR]

Background: Metastasis remains the leading cause of mortality among colorectal cancer (CRC) patients. Identification of new metastasis-related genes are critical to improve colorectal cancer prognosis. Methods: Data on mRNA expression in metastatic and primary CRC was obtained from the Gene Expression Omnibus (GEO) database, including GSE81986, GSE41568, GSE71222, GSE21510, and GSE14333. Additionally, data concerning mRNA expression in colon cancer (COAD) and adjacent normal tissues were acquired from The Cancer Genome Atlas (TCGA) database. Hub genes were identified by weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. Moreover, we assessed the impact of hub gene expression on both overall survival (OS) and disease-free survival (DFS) in patients and identified ZG16 as a potential target. We generated CRC cell lines transfected with lentivirus OE-ZG16 to investigate proliferation, invasion, and migration in vitro. To further elucidate the involvement of ZG16, we utilized gene set enrichment analysis (GSEA) to identify enriched pathways, which were subsequently validated via Western blot analysis. Results: Five datasets containing primary and metastatic CRC samples from GEO database and CRC samples from TCGA database were included in this study and 29 hub genes were identified by WGCNA and differentially expressed gene (DEG) analysis. Low expression of the hub genes (CLCA1 and ZG16) was associated with poor DFS and OS. We confirmed the low expression of ZG16 in CRC using external database and IHC analysis at both transcriptional and protein levels. In addition, the expression of ZG16 was notably elevated in NCM460 cells in comparison to CRC cell lines. The overexpression of ZG16 in CRC cells has been shown to inhibit the proliferation, invasion, and migration of CRC cells. Furthermore, the overexpression of ZG16 has been found to suppress the activation of the epithelial-mesenchymal transition (EMT) and Wnt/b-catenin signaling pathways in CRC. Conclusion: ZG16 may serve as a promising therapeutic target for metastatic CRC treatment. [ABSTRACT FROM AUTHOR]

Objective: By utilizing machine learning, we can identify genes that are associated with recurrence, invasion, and tumor stemness, thus uncovering new therapeutic targets. Methods: To begin, we obtained a gene set related to recurrence and invasion from the GEO database, a comprehensive gene expression database. We then employed the Weighted Gene Co-expression Network Analysis (WGCNA) to identify core gene modules and perform functional enrichment analysis on them. Next, we utilized the random forest and random survival forest algorithms to calculate the genes within the key modules, resulting in the identification of three crucial genes. Subsequently, one of these key genes was selected for prognosis analysis and potential drug screening using the Kaplan-Meier tool. Finally, in order to examine the role of CDC20 in lung adenocarcinoma (LUAD), we conducted a variety of in vitro and in vivo experiments, including wound healing assay, colony formation assays, Transwell migration assays, flow cytometric cell cycle analysis, western blotting, and a mouse tumor model experiment. Results: First, we collected a total of 279 samples from two datasets, GSE166722 and GSE31210, to identify 91 differentially expressed genes associated with recurrence, invasion, and stemness in lung adenocarcinoma. Functional enrichment analysis revealed that these key gene clusters were primarily involved in microtubule binding, spindle, chromosomal region, organelle fission, and nuclear division. Next, using machine learning, we identified and validated three hub genes (CDC45, CDC20, TPX2), with CDC20 showing the highest correlation with tumor stemness and limited previous research. Furthermore, we found a close association between CDC20 and clinical pathological features, poor overall survival (OS), progression-free interval (PFI), progression-free survival (PFS), and adverse prognosis in lung adenocarcinoma patients. Lastly, our functional research demonstrated that knocking down CDC20 could inhibit cancer cell migration, invasion, proliferation, cell cycle progression, and tumor growth possibly through the MAPK signaling pathway. Conclusion: CDC20 has emerged as a novel biomarker for monitoring treatment response, recurrence, and disease progression in patients with lung adenocarcinoma. Due to its significance, further research studying CDC20 as a potential therapeutic target is warranted. Investigating the role of CDC20 could lead to valuable insights for developing new treatments and improving patient outcomes. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is an aggressive and highly lethal bone tumor, highlighting the urgent need for further exploration of its underlying mechanisms. In this study, we conducted analyses utilizing bulk transcriptome sequencing data of OS and healthy control samples, as well as single cell sequencing data, obtained from public databases. Initially, we evaluated the differential expression of four tumor microenvironment (TME)-related gene sets between tumor and control groups. Subsequently, unsupervised clustering analysis of tumor tissues identified two significantly distinct clusters. We calculated the differential scores of the four TME-related gene sets for Clusters 1 (C1) and 2 (C2), using Gene Set Variation Analysis (GSVA, followed by single-variable Cox analysis. For the two clusters, we performed survival analysis, examined disparities in clinical-pathological distribution, analyzed immune cell infiltration and immune evasion prediction, assessed differences in immune infiltration abundance, and evaluated drug sensitivity. Differentially expressed genes (DEGs) between the two clusters were subjected to Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA). We conducted Weighted Gene Co-expression Network Analysis (WGCNA) on the TARGETOS dataset to identify key genes, followed by GO enrichment analysis. Using LASSO and multiple regression analysis we conducted a prognostic model comprising eleven genes (ALOX5AP, CD37, BIN2, C3AR1, HCLS1, ACSL5, CD209, FCGR2A, CORO1A, CD74, CD163) demonstrating favorable diagnostic efficacy and prognostic potential in both training and validation cohorts. Using the model, we conducted further immune, drug sensitivity and enrichment analysis. We performed dimensionality reduction and annotation of cell subpopulations in single cell sequencing analysis, with expression profiles of relevant genes in each subpopulation analyzed. We further substantiated the role of ACSL5 in OS through a variety of wet lab experiments. Our study provides new insights and theoretical foundations for the prognosis, treatment, and drug development for OS patients. [ABSTRACT FROM AUTHOR]

Background: Metabolic dysregulation following sepsis can significantly compromise patient prognosis by altering immune-inflammatory responses. Despite its clinical relevance, the exact mechanisms of this perturbation are not yet fully understood. Methods: Single-cell RNA sequencing (scRNA-seq) was utilized to map the immune cell landscape and its association with metabolic pathways during sepsis. This study employed cell-cell interaction and phenotype profiling from scRNA-seq data, along with pseudotime trajectory analysis, to investigate neutrophil differentiation and heterogeneity. By integrating scRNA-seq with Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning techniques, key genes were identified. These genes were used to develop and validate a risk score model and nomogram, with their efficacy confirmed through Receiver Operating Characteristic (ROC) curve analysis. The model's practicality was further reinforced through enrichment and immune characteristic studies based on the risk score and in vivo validation of a critical gene associated with sepsis. Results: The complex immune landscape and neutrophil roles in metabolic disturbances during sepsis were elucidated by our in-depth scRNA-seq analysis. Pronounced neutrophil interactions with diverse cell types were revealed in the analysis of intercellular communication, highlighting pathways that differentiate between proximal and core regions within atherosclerotic plaques. Insight into the evolution of neutrophil subpopulations and their differentiation within the plaque milieu was provided by pseudotime trajectory mappings. Diagnostic markers were identified with the assistance of machine learning, resulting in the discovery of PIM1, HIST1H1C, and IGSF6. The identification of these markers culminated in the development of the risk score model, which demonstrated remarkable precision in sepsis prognosis. The model's capability to categorize patient profiles based on immune characteristics was confirmed, particularly in identifying individuals at high risk with suppressed immune cell activity and inflammatory responses. The role of PIM1 in modulating the immune-inflammatory response during sepsis was further confirmed through experimental validation, suggesting its potential as a therapeutic target. Conclusion: The understanding of sepsis immunopathology is improved by this research, and new avenues are opened for novel prognostic and therapeutic approaches. [ABSTRACT FROM AUTHOR]

Gene therapy has been adapted for improving malignant tumor treatment. However, pharmacotherapies targeting cancer remain limited and are generally inapplicable for rare disease patients. Oleanolic acid (OA) is a plant‐derived triterpenoid that is frequently used in Chinese medicine as a safe but slow‐acting treatment for many disorders. Here, the congruent pharmacological activities of OA and CRISPR‐dCas9 in targeting AURKA or KDM1A and improving disease‐specific prognosis and used a synthetic‐biology‐inspired design principle to engineer a therapeutic gene circuit that enables a concerted action of both drugs are utilized. In particular, the OA‐triggered CRISPR‐dCas9 transcriptional repression system rapidly and simultaneously attenuated lung and thyroid cancer. Collectively, this work shows that rationally engineered synthetic gene circuits are capable of treating multifactorial diseases in a synergistic manner by multiplexing the targeting efficiencies of single therapeutics. [ABSTRACT FROM AUTHOR]

The biosynthesis of cellulose, lignin, and hemicelluloses in plant secondary cell walls (SCWs) is regulated by a hierarchical transcriptional regulatory network. This network features orthologous transcription factors shared between poplar and Arabidopsis, highlighting a foundational similarity in their genetic regulation. However, knowledge on the discrepant behavior of the transcriptional‐level molecular regulatory mechanisms between poplar and Arabidopsis remains limited. In this study, we investigated the function of PagMYB128 during wood formation and found it had broader impacts on SCW formation compared to its Arabidopsis ortholog, AtMYB103. Transgenic poplar trees overexpressing PagMYB128 exhibited significantly enhanced xylem development, with fiber cells and vessels displaying thicker walls, and an increase in the levels of cellulose, lignin, and hemicelluloses in the wood. In contrast, plants with dominant repression of PagMYB128 demonstrated the opposite phenotypes. RNA sequencing and reverse transcription – quantitative polymerase chain reaction showed that PagMYB128 could activate SCW biosynthetic gene expression, and chromatin immunoprecipitation along with yeast one‐hybrid, and effector–reporter assays showed this regulation was direct. Further analysis revealed that PagSND1 (SECONDARY WALL‐ASSOCIATED NAC‐DOMAIN PROTEIN1) directly regulates PagMYB128 but not cell wall metabolic genes, highlighting the pivotal role of PagMYB128 in the SND1‐driven regulatory network for wood development, thereby creating a feedforward loop in SCW biosynthesis. [ABSTRACT FROM AUTHOR]