The pan-cancer initiative aims to study the origin patterns of cancer cell, the processes of carcinogenesis, and the signaling pathways from a perspective that spans across different types of cancer. The construction of the pan-cancer related gene regulatory network is helpful to excavate the commonalities in regulatory relationships among different types of cancers. It also aids in understanding the mechanisms behind cancer occurrence and development, which is of great scientific significance for cancer prevention and treatment. In light of the high dimension and large sample size of pan-cancer omics data, a causal pan-cancer gene regulation network inference algorithm based on stochastic complexity is proposed. With the network construction strategy of local first and then global, the stochastic complexity is used in the conditional independence test and causal direction inference for the candidate adjacent node set of the target nodes. This approach aims to decrease the time complexity and error rate of causal network learning. By applying this algorithm to the sample data of seven types of cancers in the TCGA database, including breast cancer, lung adenocarcinoma, and so on, the pan-cancer related causal regulatory networks are constructed, and their biological significance is verified. The experimental results show that this algorithm can eliminate the redundant regulatory relationships effectively and infer the pan-cancer regulatory network more accurately (https://github.com/LindeEugen/CNI-SC).

Deep learning has emerged as a powerful tool for investigating intricate biological processes in plants by harnessing the potential of large-scale data. Gene regulation is a complex process that transcription factors (TFs), cooperating with their target genes, participate in through various aspects of biological processes. Despite its significance, the study of gene regulation has primarily focused on a limited number of notable instances, leaving numerous aspects and interactions yet to be explored comprehensively. Here, we developed DEGRN (Deep learning on Expression for Gene Regulatory Network), an innovative deep learning model designed to decipher gene interactions by leveraging high-dimensional expression data obtained from bulk RNA-Seq and scRNA-Seq data in the model plant Arabidopsis. DEGRN exhibited a compared level of predictive power when applied to various datasets. Through the utilization of DEGRN, we successfully identified an extensive set of 3,053,363 high-quality interactions, encompassing 1430 TFs and 13,739 non-TF genes. Notably, DEGRN\'s predictive capabilities allowed us to uncover novel regulators involved in a range of complex biological processes, including development, metabolism, and stress responses. Using leaf senescence as an example, we revealed a complex network underpinning this process composed of diverse TF families, including bHLH, ERF, and MYB. We also identified a novel TF, named MAF5, whose expression showed a strong linear regression relation during the progression of senescence. The mutant maf5 showed early leaf decay compared to the wild type, indicating a potential role in the regulation of leaf senescence. This hypothesis was further supported by the expression patterns observed across four stages of leaf development, as well as transcriptomics analysis. Overall, the comprehensive coverage provided by DEGRN expands our understanding of gene regulatory networks and paves the way for further investigations into their functional implications.

Many marine invertebrate phyla are characterized by indirect development. These animals transit from planktonic larvae to benthic spats via settlement and metamorphosis, which contributes to their adaption to the marine environment. Studying the biological process of metamorphosis is, thus, key to understanding the origin and evolution of indirect development. Although numerous studies have been conducted on the relationship between metamorphosis and the marine environment, microorganisms, and neurohormones, little is known about gene regulation network (GRN) dynamics during metamorphosis. Metamorphosis-competent pediveligers of the Pacific oyster Crassostrea gigas were assayed in this study. By assaying gene expression patterns and open chromatin region changes of different samples of larvae and spats, the dynamics of molecular regulation during metamorphosis were examined. The results indicated significantly different gene regulation networks before, during and post-metamorphosis. Genes encoding membrane-integrated receptors and those related to the remodeling of the nervous system were upregulated before the initiation of metamorphosis. Massive biogenesis, e.g., of various enzymes and structural proteins, occurred during metamorphosis as inferred from the comprehensive upregulation of the protein synthesis system post epinephrine stimulation. Hierarchical downstream gene networks were then stimulated. Some transcription factors, including homeobox, basic helix-loop-helix and nuclear receptors, showed different temporal response patterns, suggesting a complex GRN during the transition stage. Nuclear receptors, as well as their retinoid X receptor partner, may participate in the GRN controlling oyster metamorphosis, indicating an ancient role of the nuclear receptor regulation system in animal metamorphosis.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s42995-023-00204-y.

UNASSIGNED: Wilt is a soil-borne disease caused by Fusarium that has become a serious threat to wax gourd production. Disease-resistant graft wax gourds are an effective treatment for Fusarium wilt. However, there are few reports on the defense mechanism of graft wax gourd against wilt diseases.
UNASSIGNED: In the present study, disease and growth indices were compared between grafted and original wax gourds after infection with Fusarium. High level of disease resistance was observed in the grafted wax gourd, with a lower disease index and low impacts on growth after infection. RNA-seq was performed to identify the differentially expressed genes (DEGs) between the adjacent treatment time points in the grafted and original wax gourds, respectively. Then a comparative temporal analysis was performed and a total of 1,190 genes were identified to show different gene expression patterns between the two wax gourd groups during Fusarium infection.
UNASSIGNED: Here, high level of disease resistance was observed in the grafted wax gourd, with a lower disease index and low impacts on growth after infection. The DEG number was higher in grafted group than original group, and the enriched functional categories and pathways of DEGs were largely inconsistent between the two groups. These genes were enriched in multiple pathways, of which the mitogen-activated protein kinase (MAPK) signaling pathway enhanced the early defense response, and cutin, suberin, and wax biosynthesis signaling pathways enhanced surface resistance in grafted wax gourd in comparison to original group. Our study provides insights into the gene regulatory mechanisms underlying the resistance of grafted wax gourds to Fusarium wilt infection, which will facilitate the breeding and production of wilt-resistant rootstocks.

Serine hydroxymethyltransferase (SHMT) is a serine-glycine-one-carbon metabolic enzyme in which SHMT1 and SHMT2 encode the cytoplasmic and mitochondrial isoenzymes, respectively. SHMT1 and SHMT2 are key players in cancer metabolic reprogramming, and thus are attractive targets for cancer therapy. However, the role of SHMT in patients with renal cell carcinoma (RCC) has not been fully elucidated. We aimed to systematically analyze the expression, gene regulatory network, prognostic value, and target prediction of SHMT1 and SHMT2 in patients with kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), and kidney renal papillary cell carcinoma (KIRP); elucidate the association between SHMT expression and RCC; and identify potential new targets for clinical RCC treatment.
Several online databases were used for the analysis, including cBioPortal, TRRUST, GeneMANIA, GEPIA, Metascape, UALCAN, LinkedOmics, and TIMER.
SHMT1 and SHMT2 transcript levels were significantly down- and upregulated, respectively, in patients with KICH, KIRC, and KIRP, based on sample type, individual cancer stage, sex, and patient age. Compared to men, women with KIRC and KIRP showed significantly up- and downregulated SHMT1 transcript levels, respectively. However, SHMT2 transcript levels were significantly upregulated in the patients mentioned above. KIRC and KIRP patients with high SHMT1 expression had longer survival periods than those with low SHMT1 expression. In patients with KIRC, the findings were similar to those mentioned above. However, in KICH patients, the findings were the opposite regarding SHMT2 expression. SHMT1 versus SHMT2 were altered by 9% versus 3% (n = 66 KICH patients), 4% versus 4% (n = 446 KIRC patients), and 6% versus 7% (n = 280 KIRP patients). SHMT1 versus SHMT2 promoter methylation levels were significantly up- and downregulated in patients with KIRP versus KIRC and KIRP, respectively. SHMT1, SHMT2, and their neighboring genes (NG) formed a complex network of interactions. The molecular functions of SHMT1 and its NG in patients with KICH, KIRC, and KIRP, included clathrin adaptor, metalloendopeptidase, and GTPase regulator activities; lipid binding, active transmembrane transporter activity, and lipid transporter activity; and type I interferon receptor binding, integrin binding, and protein heterodimerization, respectively. Their respective Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were involved in lysosome activity, human immunodeficiency virus 1 infection, and endocytosis; coronavirus disease 2019 and neurodegeneration pathways (multiple diseases); and RIG-I-like receptor signaling pathway, cell cycle, and actin cytoskeleton regulation. The molecular functions of SHMT2 and its NG in patients with KICH, KIRC, and KIRP included cell adhesion molecule binding and phospholipid binding; protein domain-specific binding, enzyme inhibitor activity, and endopeptidase activity; and hormone activity, integrin binding, and protein kinase regulator activity, respectively. For patients with KIRC versus KIRP, the KEGG pathways were involved in cAMP and calcium signaling pathways versus microRNAs (MiRNAs) in cancer cells and neuroactive ligand-receptor interactions, respectively. We identified the key transcription factors of SHMT1 and its NG.
SHMT1 and SHMT2 expression levels were different in patients with RCC. SHMT1 and SHMT2 may be potential therapeutic and prognostic biomarkers in these patients. Transcription factor (MYC, STAT1, PPARG, AR, SREBF2, and SP3) and miRNA (miR-17-5P, miR-422, miR-492, miR-137, miR-30A-3P, and miR-493) regulations may be important strategies for RCC treatment.

Quadrotor unmanned aerial vehicles (UAVs) often encounter intricate environmental and dynamic limitations in real-world applications, underscoring the significance of proficient trajectory planning for ensuring both safety and efficiency during flights. To tackle this challenge, we introduce an innovative approach that harmonizes sophisticated environmental insights with the dynamic state of a UAV within a potential field framework. Our proposition entails a quadrotor trajectory planner grounded in a kinodynamic gene regulation network potential field. The pivotal contribution of this study lies in the amalgamation of environmental perceptions and kinodynamic constraints within a newly devised gene regulation network (GRN) potential field. By enhancing the gene regulation network model, the potential field becomes adaptable to the UAV\'s dynamic conditions and its surroundings, thereby extending the GRN into a kinodynamic GRN (K-GRN). The trajectory planner excels at charting courses that guide the quadrotor UAV through intricate environments while taking dynamic constraints into account. The amalgamation of environmental insights and kinodynamic constraints within the potential field framework bolsters the adaptability and stability of the generated trajectories. Empirical results substantiate the efficacy of our proposed methodology.

The genomic integrity of every organism is endangered by various intrinsic and extrinsic stresses. To maintain genomic integrity, a sophisticated DNA damage response (DDR) network is activated rapidly after DNA damage. Notably, the fundamental DDR mechanisms are conserved in eukaryotes. However, knowledge about many regulatory aspects of the plant DDR is still limited. Important, yet little understood, regulatory factors of the DDR are the long non-coding RNAs (lncRNAs). In humans, 13 lncRNAs functioning in DDR have been characterized to date, whereas no such lncRNAs have been characterized in plants yet. By meta-analysis, we identified the putative long intergenic non-coding RNA induced by DNA damage (LINDA) that responds strongly to various DNA double-strand break-inducing treatments, but not to replication stress induced by mitomycin C. After DNA damage, LINDA is rapidly induced in an ATM- and SOG1-dependent manner. Intriguingly, the transcriptional response of LINDA to DNA damage is similar to that of its flanking hypothetical protein-encoding gene. Phylogenetic analysis of putative Brassicales and Malvales LINDA homologs indicates that LINDA lncRNAs originate from duplication of a flanking small protein-encoding gene followed by pseudogenization. We demonstrate that LINDA is not only needed for the regulation of this flanking gene but also fine-tuning of the DDR after the occurrence of DNA double-strand breaks. Moreover, Δlinda mutant root stem cells are unable to recover from DNA damage, most likely due to hyper-induced cell death.

Bromodomain and extracellular terminal (BET) family (including BRD2, BRD3, and BRD4) is considered to be a major driver of cancer cell growth and a new target for cancer therapy. Currently, more than 30 targeted inhibitors have shown significant inhibitory effects against various tumors in preclinical and clinical trials. However, the expression levels, gene regulatory networks, prognostic value, and target prediction of BRD2, BRD3, and BRD4 in adrenocortical carcinoma (ACC) have not been fully elucidated. Therefore, this study aimed to systematically analyze the expression, gene regulatory network, prognostic value, and target prediction of BRD2, BRD3, and BRD4 in patients with ACC, and elucidated the association between BET family expression and ACC. We also provided useful information on BRD2, BRD3, and BRD4 and potential new targets for the clinical treatment of ACC.
We systematically analyzed the expression, prognosis, gene regulatory network, and regulatory targets of BRD2, BRD3, and BRD4 in ACC using multiple online databases, including cBioPortal, TRRUST, GeneMANIA, GEPIA, Metascape, UALCAN, LinkedOmics, and TIMER.
The expression levels of BRD3 and BRD4 were significantly upregulated in ACC patients at different cancer stages. Moreover, the expression of BRD4 was significantly correlated with the pathological stage of ACC. ACC patients with low BRD2, BRD3, and BRD4 expressions had longer survival than patients with high BRD2, BRD3, and BRD4 expressions. The expression of BRD2, BRD3, and BRD4 was altered by 5%, 5%, and 12% in 75 ACC patients, respectively. The frequency of gene alterations in the 50 most frequently altered BRD2, BRD3, and BRD4 neighboring genes in these ACC patients were ≥25.00%, ≥25.00%, and ≥44.44%, respectively. BRD2, BRD3, and BRD4 and their neighboring genes form a complex network of interactions mainly through co-expression, physical interactions, and shared protein domains. Molecular functions related to BRD2, BRD3, and BRD4 and their neighboring genes mainly include protein-macromolecule adaptor activity, cell adhesion molecule binding, and aromatase activity. Chemokine signaling pathway, thiamine metabolism, and olfactory transduction were found to be enriched as per the KEGG pathway analysis. SP1, NPM1, STAT3, and TP53 are key transcription factors for BRD2, BRD4, and their neighboring genes. MiR-142-3P, miR-484, and miR-519C were the main miRNA targets of BRD2, BRD3, BRD4, and their neighboring genes. We analyzed the mRNA sequencing data from 79 patients with ACC and found that ZSCAN12, DHX16, PRPF4B, EHMT1, CDK5RAP2, POMT1, WIZ, ZNF543, and AKAP8 were the top nine genes whose expression were positively associated with BRD2, BRD3, and BRD4 expression. The expression level of BRD2, BRD3, and BRD4 positively correlated with B cell and dendritic cell infiltration levels. BRD4-targeted drug PFI-1 and (BRD2, BRD3, and BRD4)-targeted drug I-BET-151 may have good inhibitory effects on the SW13 cell line.
The findings of this study provide a partial basis for the role of BRD2, BRD3, and BRD4 in the occurrence and development of ACC. In addition, this study also provides new potential therapeutic targets for ACC, which can serve as a reference for future basic and clinical research.

Pyrroline-5-carboxylate reductase (PYCR) includes three human genes encoding three isozymes, PYCR1, PYCR2, and PYCR3 (or PYCRL), which facilitate the final step in the conversion of glutamine to proline. These genes play important roles in regulating the cell cycle and redox homeostasis as well as promoting growth signaling pathways. Proline is abnormally upregulated in a variety of cancers, and as the last key enzyme in proline production, PYCR plays an integral role in promoting tumorigenesis and cancer progression. However, its role in patients with kidney renal papillary cell carcinoma (KIRP) has not been fully elucidated. In this study, we aimed to systematically analyze the expression, gene regulatory network, prognostic value, and target prediction of PYCR in patients with KIRP, elucidate the association between PYCR expression and KIRP, and identify potential new targets for the clinical treatment of KIRP.
We systematically analyzed the expression, prognosis, gene regulatory network, and regulatory targets of PYCR1, PYCR2, and PYCRL in KIRP using multiple online databases including cBioPortal, STRING, MethSurv, GeneMANIA, Gene Expression Profiling Interactive Analysis (GEPIA), Metascape, UALCAN, LinkedOmics, and TIMER.
The expression levels of PYCR1, PYCR2, and PYCRL were considerably upregulated in patients with KIRP based on sample type, sex, age, and individual cancer stage. PYCR1 and PYCR2 transcript levels were markedly upregulated in females than in males, and patients aged 21-40 years had higher PYCR1 and PYCR2 transcript levels than those in other age groups. Interestingly, PYCR2 transcript levels gradually decreased with age. In addition, the expressions of PYCR1 and PYCR2 were notably correlated with the pathological stage of KIRP. Patients with KIRP with low PYCR1 and PYCR2 expression had longer survival than those with high PYCR1 and PYCR2 expression. PYCR1, PYCR2, and PYCRL were altered by 4%, 7%, and 6%, respectively, in 280 patients with KIRP. The methylation levels of cytosine-phosphate-guanine (CpG) sites in PYCR were markedly correlated with the prognosis of patients with KIRP. PYCR1, PYCR2, PYCRL, and their neighboring genes form a complex network of interactions. The molecular functions of the genes, as demonstrated by their corresponding Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, included calcium channel activity, phospholipid binding, RNA polymerase II-specificity, and kinase and GTPase-regulatory activities. PYCR1, PYCR2, and PYCRL targeted miR-21, miR-221, and miR-222, resulting in a better prognosis of KIRP. We analyzed mRNA sequencing data from 290 patients with KIRP and found that ADA, NPM3, and TKT were positively associated with PYCR1 expression; PFDN2, JTB, and HAX1 were positively correlated with PYCR2 expression; SHARPIN, YDJC, and NUBP2 were positively correlated with PYCRL expression; PYCR1 was positively correlated with B cell and CD8+ T-cell infiltration levels; macrophage infiltration was negatively correlated with PYCR2 expression; and PYCRL expression was negatively correlated with B-cell, CD8+ T cell, and dendritic cell infiltration levels.
PYCR1, PYCR2, and PYCRL may be potential therapeutic and prognostic biomarkers for patients with KIRP. The regulation of microRNAs (miRNAs), including miR-21, miR-221, and miR-222, may prove an important strategy for KIRP treatment.

UNASSIGNED: One of the main causes of low back pain is intervertebral disc degeneration (IDD). Annulus fibrosus (AF) is important for the integrity and functions of the intervertebral disc (IVD). However, the resident functional cell components such as progenitors and vascularization-associated cells in AF are yet to be fully identified.
UNASSIGNED: Identification of functional AF cell subpopulations including resident progenitors and vascularization-associated cells.
UNASSIGNED: In this study, the single-cell RNA sequencing data of rat IVDs from a public database were analyzed using Seurat for cell clustering, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional analysis, StemID for stem cell identification, Monocle and RNA velocity for pseudotime differentiation trajectory validation, single-cell regulatory network inference and clustering (SCENIC) for gene regulatory network (GRN) analysis, and CellChat for cell-cell interaction analysis. Immunostaining on normal and degenerated rat IVDs, as well as human AF, was used for validations.
UNASSIGNED: From the data analysis, seven AF cell clusters were identified, including two newly discovered functional clusters, the Grem1 + subpopulation and the Lum + ​subpopulation. The Grem1 + subpopulation had progenitor characteristics, while the Lum + ​subpopulation was associated with vascularization during IDD. The GRN analysis showed that Sox9 and Id1 were among the key regulators in the Grem1 + subpopulation, and Nr2f2 and Creb5 could be responsible for the vascularization function in the Lum + ​subpopulation. Cell-cell interaction analysis revealed highly regulated cellular communications between these cells, and multiple signaling networks including PDGF and MIF signaling pathways were involved in the interactions.
UNASSIGNED: Our results revealed two new functional AF cell subpopulations, with stemness and vascularization induction potential, respectively.
UNASSIGNED: These findings complement our knowledge about IVDs, especially the AF, and in return provide potential cell source and regulation targets for IDD treatment and tissue repair. The existence of the cell subpopulations was also validated in human AF, which strengthen the clinical relevance of the findings.