Transcriptome Sequencing Data Research Articles

IPF-related new macrophage subpopulations and diagnostic biomarker identification - combine machine learning with single-cell analysis

sIdiopathic pulmonary fibrosis (IPF) is a chronic disease of unknown etiology that lacks a specific treatment. In IPF, macrophages play a key regulatory role as a major component of the lung immune system, especially during inflammation and fibrosis. However, our understanding of the cellular heterogeneity and molecular characterization of macrophages in IPF, as well as their relevance in the clinical setting, is relatively limited. In this study, we analyzed in-depth single-cell transcriptome sequencing (scRNA-seq) data from lung tissues of IPF patients, identified macrophage subpopulations in IPF, and probed their molecular characteristics and biological functions. hdWGCNA identified co-expressed gene modules of a subpopulation of IPF-associated macrophages (IPF-MΦ), and probed the IPF-MΦ by a machine-learning approach. hdWGCNA identified a subpopulation of IPF-associated macrophage subpopulations and probed the IPF-MΦ signature gene (IRMG) for its prognostic value, and a prediction model was developed on this basis. In addition, IPF-MΦ was obtained after recluster analysis of macrophages in IPF lung tissues. Coexpressed gene modules of IPF-MΦ were identified by hdWGCNA. Then, a machine learning approach was utilized to reveal the characteristic genes of IPF-MΦ, and a prediction model was built on this basis. In addition, we discovered a type of macrophage unique to IPF lung tissue named ATP5-MΦ. Its characteristic gene encodes a subunit of the mitochondrial ATP synthase complex, which is closely related to oxidative phosphorylation and proton transmembrane transport, suggesting that ATP5-MΦ may have higher ATP synthesis capacity in IPF lung tissue. This study provides new insights into the pathogenesis of IPF and provides a basis for evaluating disease prognosis and predictive medicine in IPF patients.Graphical

Single-cell transcriptomic sequencing coupled with Mendelian randomization analysis elucidates the pivotal role of CTSC in chronic rhinosinusitis

Objective: To investigate the molecular mechanisms of chronic rhinosinusitis (CRS), to identify key cell subgroups and genes, to construct effective diagnostic models, and to screen for potential therapeutic drugs. Methods: Key cell subgroups in CRS were identified through single-cell transcriptomic sequencing data. Essential genes associated with CRS were selected and diagnostic models were constructed by hdWGCNA (high dimensional weighted gene co-expression network analysis) and various machine learning algorithms. Causal inference analysis was performed using Mendelian randomization and colocalization analysis. Potential therapeutic drugs were identified using molecular docking technology, and the results of bioinformatics analysis were validated by immunofluorescence staining. Graphpad Prism, R, Python, and Adobe Illustrator software were used for data and image processing. Results: An increased proportion of basal and suprabasal cells was observed in CRS, especially in eosinophilic CRS with nasal polyps (ECRSwNP), with P=0.001. hdWGCNA revealed that the "yellow module" was closely related to basal and suprabasal cells in CRS. Univariate logistic regression and LASSO algorithm selected 13 key genes (CTSC, LAMB3, CYP2S1, TRPV4, ARHGAP21, PTHLH, CDH26, MRPS6, TENM4, FAM110C, NCKAP5, SAMD3, and PTCHD4). Based on these 13 genes, an effective CRS diagnostic model was developed using various machine learning algorithms (AUC=0.958). Mendelian randomization analysis indicated a causal relationship between CTSC and CRS (inverse variance weighted: OR=1.06, P=0.006), and colocalization analysis confirmed shared genetic variants between CTSC and CRS (PPH4/PPH3>2). Molecular docking results showed that acetaminophen binded well with CTSC (binding energy:-5.638 kcal/mol). Immunofluorescence staining experiments indicated an increase in CTSC+cells in CRS. Conclusion: This study integrates various bioinformatics methods to identify key cell types and genes in CRS, constructs an effective diagnostic model, underscores the critical role of the CTSC gene in CRS pathogenesis, and provides new targets for the treatment of CRS.

Identification of oxidative stress-related biomarkers in chronic rhinosinusitis with nasal polyps using WGCNA combined with machine learning algorithms

Objective: To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal polyps (CRSwNP) by analyzing transcriptome sequencing data, and to investigate their roles in CRSwNP. Methods: Utilizing four CRSwNP sequencing datasets, differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning methods for Hub gene selection were performed in this study. Subsequent validation was carried out using external datasets, as well as real-time quantitative polymerase chain reaction (Real-time qPCR), and immunofluorescence staining of clinical samples. Moreover, the diagnostic efficacy of the genes was assessed by receiver operating characteristic (ROC) curve, followed by functional and pathway enrichment analysis, immune-related analysis, and cell population localization. Additionally, a competing endogenous RNA (CeRNA) network was constructed to predict potential drug targets. Statistical analysis and plotting were conducted using SPSS 26.0 and Graphpad Prism9 software. Results: Through data analysis and clinical validation, CP, SERPINF1 and GSTO2 were identified among 4 138 DEGs as oxidative stress markers related to CRSwNP. Specifically, the expression of CP and SERPINF1 increased in CRSwNP, whereas that of GSTO2 decreased, with statistically significant differences (P<0.05). Additionally, an area under the curve (AUC)>0.7 indicated their effectiveness as diagnostic indicators. Importantly, functional analysis indicated that these genes were mainly related to lipid metabolism, cell adhesion migration, and immunity. Single-cell data analysis revealed that SERPINF1 was mainly distributed in epithelial cells, stromal cells, and fibroblasts, while CP was primarily located in epithelial cells, and GSTO2 was minimally present in the epithelial cells and fibroblasts of nasal polyps. Consequently, a CeRNA regulatory network was constructed for the genes CP and GSTO2. This construction allowed for the prediction of potential drugs that could target CP. Conclusion: This study successfully identifies CP, SERPINF1 and GSTO2 as diagnostic and therapeutic markers related to oxidative stress in CRSwNP.

Integrating Large Language Models in Bioinformatics Education for Medical Students: Opportunities and Challenges.

Large language models (LLMs) offer transformative opportunities in bioinformatics education for medical students by creating interactive experiences. The integration of LLMs enhances educational outcomes through providing accessible code templates, clarifying the function of coding elements, and assisting in error troubleshooting. Here, we demonstrate the practical applications of LLMs with a case study on transcriptome sequencing data processing, a vital component of medical research. However, the reliability of the content that LLMs generate requires rigorous validation. Ensuring the accuracy and appropriateness of the LLM-generated information requires integrating innovative LLMs with traditional educational methods to prepare medical students effectively for future challenges in bioinformatics.

Hif3α Plays Key Roles in the Progression of Alzheimer's Disease Caused by Circadian Rhythm Disruption through Regulating the m6A/KDM3A/TGF-β1 Axis.

Disrupted circadian rhythms are associated with the onset of chronic diseases and impairments, including cancer, diabetes, and hypertension. However, whether circadian disruptions accelerate the progression of Alzheimer's disease and the respective pathway remains unclear. In this study, we constructed animal models using male C57BL/6N and APP/PS1 mice. Irregular illumination during sleeping hours was administered to the mice in our intervention groups to consistently disrupt their circadian rhythms. The impact of the intervention was evaluated through body weight tracking, cerebral index determination, histopathological staining, and biochemical marker analysis. Transcriptomic sequencing identified critical genes, with the data subsequently validated using RNA m6A detection and site analysis. The evaluations revealed that circadian disruptions impaired normal weight gain, liver and kidney functions, neuronal cells, and overall brain function. Transcriptomic sequencing data revealed a trend of elevating expression of Hif3α mRNA in the intervention groups. Further analysis of specific gene sites revealed that m6A methylation of the Hif3α gene at m6A site 3632 primarily drove the observed variations in HIF3A protein expression in our model. Furthermore, the expression of proteins in PC12 cells, N2a cells, and mice brains validated that an increase in HIF3A expression decreased KDM3A and TGF-β1 protein expression. Our study reveals a hitherto unknown pathway through which the disruption of circadian rhythms, by triggering m6A methylation at m6A site 3632 in the Hif3α gene, leads to the initiation and acceleration of AD. These findings provide valuable insights and guidelines for treating AD patients and enhancing caregiving by professionals.

A molecular subtyping associated with the cGAS-STING pathway provides novel perspectives on the treatment of ulcerative colitis

Ulcerative colitis (UC) is characterized by an abnormal immune response, and the pathogenesis lacks clear understanding. The cGAS-STING pathway is an innate immune signaling pathway that plays a significant role in various pathophysiological processes. However, the role of the cGAS-STING pathway in UC remains largely unclear. In this study, we obtained transcriptome sequencing data from multiple publicly available databases. cGAS-STING related genes were obtained through literature search, and differentially expressed genes (DEGs) were analyzed using R package limma. Hub genes were identified through protein–protein interaction (PPI) network analysis and module construction. The ConsensuClusterPlus package was utilized to identify molecular subtypes based on hub genes. The therapeutic response, immune microenvironment, and biological pathways of subtypes were further investigated. A total of 18 DEGs were found in UC patients. We further identified IFI16, MB21D1 (CGAS), TMEM173 (STING) and TBK1 as the hub genes. These genes are highly expressed in UC. IFI16 exhibited the highest diagnostic value and predictive value for response to anti-TNF therapy. The expression level of IFI16 was higher in non-responders to anti-TNF therapy. Furthermore, a cluster analysis based on genes related to the cGAS-STING pathway revealed that patients with higher gene expression exhibited elevated immune burden and inflammation levels. This study is a pioneering analysis of cGAS-STING pathway-related genes in UC. These findings provide new insights for the diagnosis of UC and the prediction of therapeutic response.

Biomarker development from functional precision medicine datasets via explainable machine learning.

10061 Background: Genomics precision medicine, deployed via tumor panel sequencing, now assists in deploying targeted therapies to cancer patients. Numerous clinical trials have investigated the utility and benefit of genomics precision medicine in multiple cancer indications. Current large-scale studies report actionability rates from ~35% to ~60%, although clinical benefit rates have been shown to be closer to 10%. While this has positively impacted patients in need, the gap between actionability and benefit remains a clinical challenge attributed to multiple factors including the complex, multi-factorial relationship between molecular status and response to therapy. These differences go beyond simple disease states and may be reflective of multiple clinically relevant features including age, sex, and race/ethnicity. Methods: We implemented a functional precision medicine (FPM) program where patients with advanced pediatric cancers were prospectively profiled via high-throughput drug sensitivity testing (DST) of FDA-approved agents on patient-derived tumor cells as well as genomics testing. The objective was to investigate the clinical utility and benefit of FPM guidance in the treatment of pediatric cancer and elucidate the relationship between molecular status of patients’ diseases and treatment responses. We generated DST data (n = 21 patients) and genomic profiling data (n = 20 patients) on pediatric cancer patients in Miami, FL, as well as post-hoc whole exome and transcriptome sequencing data (n = 13 patients) and investigated three specific relationships. Results: We analyzed the relationship between racial/ethnic background and functional response to anti-cancer agents, determining potential differences in response to therapeutic classes. Next, we examined relationships between functional response and cancer type, identifying an unanticipated lack of clustering between disease indications in patients with advanced pediatric cancers. Finally, we applied an explainable machine learning (xML) framework to the functional genomic dataset to develop multi-omics biomarker hypotheses for the chemotherapy agent idarubicin, pinpointing a potential multi-cancer relationship between response to idarubicin and known disease mechanisms in acute myeloid leukemia (AML), the sole indication where idarubicin is approved. We further present additional proof-of-concept studies generating biomarker hypotheses via xML, demonstrating a framework for development of multi-omics biomarkers. Conclusions: We are now expanding our pan-pediatric cancer functional genomics dataset through an NIMHD-funded expansion cohort (NCT05857969, n = 65 patients) to further investigate multi-omics relationships between functional and molecular characteristics and understand the role of race/ethnicity in the complex relationship.

Infliximab inhibits TNF-α-dependent activation of the NLRP3/IL-1β pathway in acne inversa

BackgroundAcne inversa (AI) is a refractory inflammatory skin disease, and TNF-α plays an important role in the pathogenesis of AI. By blocking TNF-α, infliximab (IFX) has been proven to be a promising method. ObjectivesTo explore the underlying mechanisms of IFX treatment in AI patients. MethodsIn this research, we integrated transcriptome sequencing data from the samples of our patients with AI and the GEO database. Ex vivo skin culture of AI patients was conducted to evaluate the efficacy of IFX treatment. Animal studies and cell experiments were used to explore the therapeutic effect and mechanism of IFX treatment. ResultsBoth TNF-α and NLRP3 inflammasome-related pathways were enriched in skin lesions of AI patients and murine AI models. After IFX treatment, the NLRP3 inflammasome-related pathway was effectively blocked, and the IL-1β level was normalized in ex vivo AI skin explants and murine AI models. Mechanistically, IFX suppressed the NF-κB signaling pathway to lower the expression of NLRP3 and IL-1β in keratinocytes. ConclusionsIFX treatment alleviated skin lesions in murine AI models and downregulated NLRP3 and IL-1β expression levels by inhibiting the NF-κB signaling pathway, which was helpful for understanding the mechanism of IFX therapy.

Lumbar instability remodels cartilage endplate to induce intervertebral disc degeneration by recruiting osteoclasts via Hippo-CCL3 signaling

Degenerated endplate appears with cheese-like morphology and sensory innervation, contributing to low back pain and subsequently inducing intervertebral disc degeneration in the aged population.1 However, the origin and development mechanism of the cheese-like morphology remain unclear. Here in this study, we report lumbar instability induced cartilage endplate remodeling is responsible for this pathological change. Transcriptome sequencing of the endplate chondrocytes under abnormal stress revealed that the Hippo signaling was key for this process. Activation of Hippo signaling or knockout of the key gene Yap1 in the cartilage endplate severed the cheese-like morphological change and disc degeneration after lumbar spine instability (LSI) surgery, while blocking the Hippo signaling reversed this process. Meanwhile, transcriptome sequencing data also showed osteoclast differentiation related gene set expression was up regulated in the endplate chondrocytes under abnormal mechanical stress, which was activated after the Hippo signaling. Among the discovered osteoclast differentiation gene set, CCL3 was found to be largely released from the chondrocytes under abnormal stress, which functioned to recruit and promote osteoclasts formation for cartilage endplate remodeling. Over-expression of Yap1 inhibited CCL3 transcription by blocking its promoter, which then reversed the endplate from remodeling to the cheese-like morphology. Finally, LSI-induced cartilage endplate remodeling was successfully rescued by local injection of an AAV5 wrapped Yap1 over-expression plasmid at the site. These findings suggest that the Hippo signaling induced osteoclast gene set activation in the cartilage endplate is a potential new target for the management of instability induced low back pain and lumbar degeneration.

Genome-Wide Association Study and Candidate Gene Mining of Seed Size Traits in Soybean

Seed size traits, including seed length (SL), seed width (SW), and seed thickness (ST), are crucial appearance parameters that determine soybean seed weight, yield, and ultimate utilization. However, there is still a large gap in the understanding of the genetic mechanism of these traits. Here, 281 soybeans were utilized to analyze the genetic architecture of seed size traits in different years through multiple (single-locus and multi-locus) genome-wide association study (GWAS) models, and candidate genes were predicted by integrating information on gene function and transcriptome sequencing data. As a result, two, seven, and three stable quantitative trait nucleotides (QTNs) controlling SL, SW, and ST were detected in multiple environments using the single-locus GWAS model, and concurrently detected by the results of the multi-locus GWAS models. These stable QTNs are located on 10 linkage disequilibrium blocks, with single genome regions ranging in size from 20 to 440 kb, and can serve as the major loci controlling soybean seed size. Furthermore, by combining gene functional annotation and transcriptome sequencing data of seeds at different developmental stages from two extreme soybean accessions, nine candidate genes, including Glyma.05G038000, Glyma.05G244100, Glyma.05G246900, Glyma.07G070200, Glyma.11G010000, Glyma.11G012400, Glyma.17G165500, Glyma.17G166500, and Glyma.20G012600 within the major loci that may regulate soybean seed size, were mined. Overall, these findings offer valuable insights for molecular improvement breeding as well as gene functional studies to unravel the mechanism of soybean seed size.

Restricting Colorectal Cancer Cell Metabolism with Metformin: An Integrated Transcriptomics Study.

Metformin is a first-line therapy for type 2 diabetes as it disrupts cellular metabolism. Despite the association between metformin and lower cancer incidence, the anti-tumour activity of the drug in colorectal cancer (CRC) is incompletely understood. This study identifies underlying molecular mechanisms by which metformin slows colorectal cancer cell proliferation by investigating metformin-associated microRNA (miRNA) and target gene pairs implicated in signalling pathways. The present study analysed changes in miRNAs and the coding transcriptome in CRC cells treated with a sublethal dose of metformin, followed by the contextual validation of potential miRNA-target gene pairs. Analyses of small RNA and transcriptome sequencing data revealed 104 miRNAs and 1221 mRNAs to be differentially expressed in CRC cells treated with metformin for 72 h. Interaction networks between differentially expressed miRNAs and putative target mRNAs were identified. Differentially expressed genes were mainly implicated in metabolism and signalling processes, such as the PI3K-Akt and MAPK/ERK pathways. Further validation of potential miRNA-target mRNA pairs revealed that metformin induced miR-2110 and miR-132-3p to target PIK3R3 and, consequently, regulate CRC cell proliferation, cell cycle progression and the PI3K-Akt signalling pathway. Metformin also induced miR-222-3p and miR-589-3p, which directly target STMN1 to inhibit CRC cell proliferation and cell cycle progression. This study identified novel changes in the coding transcriptome and small non-coding RNAs associated with metformin treatment of CRC cells. Integration of these datasets highlighted underlying mechanisms by which metformin impedes cell proliferation in CRC. Importantly, it identified the post-transcriptional regulation of specific genes that impact both metabolism and cell proliferation.

Transcriptome analysis and development of EST-SSR markers in the mushroom Auricularia heimuer

Auricularia heimuer, the third most frequently cultivated edible mushroom species worldwide, has high medicinal value. However, a shortage of molecular marker hinders the efficiency and accuracy of genetic breeding efforts for A. heimuer. High-throughput transcriptome sequencing data are essential for gene discovery and molecular markers development. This study aimed to clarify the distribution of SSR loci across the A. heimuer transcriptome and to develop highly informative EST-SSR markers. These tools can be used for phylogenetic analysis, functional gene mining, and molecular marker-assisted breeding of A. heimuer. This study used Illumina high-throughput sequencing technology to obtain A. heimuer transcriptome data. The results revealed 37,538 unigenes in the A. heimuer transcriptome. Of these unigenes, 24,777 (66.01%) were annotated via comparison with the COG, Pfam, and NR databases. Overall, 2510 SSRs were identified from the unigenes, including 6 types of SSRs. The most abundant type of repeats were trinucleotides (1425, 56.77%), followed by mononucleotides (391, 15.58%) and dinucleotides (456, 18.17%). Primer pairs for 102 SSR loci were randomly designed for validity confirmation and polymorphism identification; this process yielded 53 polymorphic EST-SSR markers. Finally, 13 pairs of highly polymorphic EST-SSR primers were used to analyze the genetic diversity and population structure of 52 wild A. heimuer germplasms, revealing that the 52 germplasms could be divided into three categories. These results indicated that SSR loci were abundant in types, numbers, and frequencies, providing a potential basis for germplasm resource identification, genetic diversity analysis, and molecular marker-assisted breeding of A. heimuer.

Integrated transcriptomic and immunological profiling reveals new diagnostic and prognostic models for cutaneous melanoma.

The mortality rate associated with cutaneous melanoma (SKCM) remains alarmingly high, highlighting the urgent need for a deeper understanding of its molecular underpinnings. In our study, we leveraged bulk transcriptome sequencing data from the SKCM cohort available in public databases such as TCGA and GEO. We utilized distinct datasets for training and validation purposes and also incorporated mutation and clinical data from TCGA, along with single-cell sequencing data from GEO. Through dimensionality reduction, we annotated cell subtypes within the single-cell data and analyzed the expression of tumor-related pathways across these subtypes. We identified differentially expressed genes (DEGs) in the training set, which were further refined using the Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithm, employing tenfold cross-validation. This enabled the construction of a prognostic model, whose diagnostic efficacy we subsequently validated. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on the DEGs, and performed immunological profiling on two risk groups to elucidate the relationship between model genes and the immune responses relevant to SKCM diagnosis, treatment, and prognosis. We also knocked down the GMR6 expression level in the melanoma cells and verified its effect on cancer through multiple experiments. The results indicate that the GMR6 gene plays a role in promoting the proliferation, invasion, and migration of cancer cells in human melanoma. Our findings offer novel insights and a theoretical framework that could enhance prognosis, treatment, and drug development strategies for SKCM, potentially leading to more precise therapeutic interventions.

Prolactin receptor potentiates chemotherapy through miRNAs-induced G6PD/TKT inhibition in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies, with a notoriously dismal prognosis. As a competitive inhibitor of DNA synthesis, gemcitabine is the cornerstone drug for treating PDAC at all stages. The therapeutic effect of gemcitabine, however, is often hindered by drug resistance, and the underlying mechanisms remain largely unknown. It is unclear whether their response to chemotherapeutics is regulated by endocrine regulators, despite the association between PDAC risk and endocrine deregulation. Here, we show that prolactin receptor (PRLR) synergizes with gemcitabine in both invitro and invivo treatment of PDAC. Interestingly, PRLR promotes the expression of miR-4763-3p and miR-3663-5p, two novel miRNAs whose functions are unknown. Furthermore, the analysis of transcriptome sequencing data of tumors from lactating mouse models enriches the PPP pathway, a multifunctional metabolic pathway. In addition to providing energy, the PPP pathway mainly provides a variety of raw materials for anabolism. We demonstrate that two key enzymes of the pentose phosphate pathway (PPP), G6PD and TKT, are directly targeted by miR-4763-3p and miR-3663-5p. Notably, miR-4763-3p and miR-3663-5p diminish the nucleotide synthesis of the PPP pathway, thereby increasing gemcitabine sensitivity. As a result, PRLR harnesses these two miRNAs to suppress PPP and nucleotide synthesis, subsequently elevating the gemcitabine sensitivity of PDAC cells. Also, PDAC tissues and tumors from LSL-KrasG12D/+, LSL-Trp53R172H/+, and PDX1-cre (KPC) mice exhibit downregulation of PRLR. Bisulfite sequencing of PDAC tissues revealed that PRLR downregulation is due to epigenetic methylation. In this study, we show for the first time that the endocrine receptor PRLR improves the effects of gemcitabine by boosting two new miRNAs that block the PPP pathway and nucleotide synthesis by inhibiting two essential enzymes concurrently. The PRLR-miRNAs-PPP axis may serve as a possible therapeutic target to supplement chemotherapy advantages in PDAC.

Differential Antioxidant Enzyme Gene Expression and Functional Analysis of Pyridaben-Susceptible and -Resistant Strains of Tetranychus truncatus (Acari: Tetranychidae) under High Temperature Stress.

Tetranychus truncatus (Acari: Tetranychidae) has caused serious economic losses on some crops (soybean, corn, and cotton) in China, and has developed resistance to most acaricides. Our laboratory study found that T. truncatus was resistant to pyridaben and also adapted to high temperature (34-40 °C). High temperature stress may cause arthropods to produce a large amount of reactive oxygen species (ROS), causing oxidative damage. Antioxidant enzymes, as the main antioxidants, can reduce the damage caused by excessive ROS in arthropods. In order to study the adaptation mechanism of the pyridaben-resistant strain of T. truncatus to high temperature and the role of antioxidant enzyme genes under high temperature stress, four antioxidant enzyme genes, TtSOD, TtPOD3, TtPOD4, and TtGSTs2, were screened according to the transcriptome sequencing data of pyridaben-susceptible and -resistant strains in T. truncatus. Firstly, the phylogeny and structure analyses of these four genes were carried out. Then, real-time quantitative PCR (RT-qPCR) technology was used to analyze the gene expression patterns of antioxidant enzymes in two strains of T. truncatus at three different high temperature ranges (34 °C, 38 °C, and 42 °C). The results showed that the expression levels of four antioxidant enzyme genes of two strains of T. truncatus were induced by high temperature stress, and the expression levels of antioxidant enzyme genes were significantly different in each development state. The gene expression of antioxidant enzyme genes in resistant strains at the adult stage was significantly higher than that in susceptible strains. After the TtSOD and TtPOD4 genes of adult mites of the resistant strain were silenced by RNA interference (RNAi) technology, the mortality rate of mites with TtPOD4 gene silencing reached 41.11% after 96 h at 34 °C, which was significantly higher than that of the control and TtSOD gene silencing. It has been confirmed that the TtPOD4 gene plays a key role in the adaptation of pyridaben-resistant strain of T. truncatus to high temperature. It lays a theoretical foundation for revealing the thermal adaptation mechanism of T. truncatus.

Identification of YUC genes associated with leaf wrinkling trait in Tacai variety of Chinese cabbage.

Chinese cabbage (Brassica campestris L. ssp. chinensis (L.) Makino) stands as a widely cultivated leafy vegetable in China, with its leaf morphology significantly influencing both quality and yield. Despite its agricultural importance, the precise mechanisms governing leaf wrinkling development remain elusive. This investigation focuses on 'Wutacai', a representative cultivar of the Tacai variety (Brassica campestris L. ssp. chinensis var. rosularis Tsen et Lee), renowned for its distinct leaf wrinkling characteristics. Within the genome of 'Wutacai', we identified a total of 18 YUCs, designated as BraWTC_YUCs, revealing their conservation within the Brassica genus, and their close homology to YUCs in Arabidopsis. Expression profiling unveiled that BraWTC_YUCs in Chinese Cabbage exhibited organ-specific and leaf position-dependent variation. Additionally, transcriptome sequencing data from the flat leaf cultivar 'Suzhouqing' and the wrinkled leaf cultivar 'Wutacai' revealed differentially expressed genes (DEGs) related to auxin during the early phases of leaf development, particularly the YUC gene. In summary, this study successfully identified the YUC gene family in 'Wutacai' and elucidated its potential function in leaf wrinkling trait, to provide valuable insights into the prospective molecular mechanisms that regulate leaf wrinkling in Chinese cabbage.

P62 promotes FSH-induced antral follicle formation by directing degradation of ubiquitinated WT1

In females, the pathophysiological mechanism of poor ovarian response (POR) is not fully understood. Considering the expression level of p62 was significantly reduced in the granulosa cells (GCs) of POR patients, this study focused on identifying the role of the selective autophagy receptor p62 in conducting the effect of follicle-stimulating hormone (FSH) on antral follicles (AFs) formation in female mice. The results showed that p62 in GCs was FSH responsive and that its level increased to a peak and then decreased time-dependently either in ovaries or in GCs after gonadotropin induction in vivo. GC-specific deletion of p62 resulted in subfertility, a significantly reduced number of AFs and irregular estrous cycles, which were same as pathophysiological symptom of POR. By conducting mass spectrum analysis, we found the ubiquitination of proteins was decreased, and autophagic flux was blocked in GCs. Specifically, the level of nonubiquitinated Wilms tumor 1 homolog (WT1), a transcription factor and negative controller of GC differentiation, increased steadily. Co-IP results showed that p62 deletion increased the level of ubiquitin-specific peptidase 5 (USP5), which blocked the ubiquitination of WT1. Furthermore, a joint analysis of RNA-seq and the spatial transcriptome sequencing data showed the expression of steroid metabolic genes and FSH receptors pivotal for GCs differentiation decreased unanimously. Accordingly, the accumulation of WT1 in GCs deficient of p62 decreased steroid hormone levels and reduced FSH responsiveness, while the availability of p62 in GCs simultaneously ensured the degradation of WT1 through the ubiquitin‒proteasome system and autophagolysosomal system. Therefore, p62 in GCs participates in GC differentiation and AF formation in FSH induction by dynamically controlling the degradation of WT1. The findings of the study contributes to further study the pathology of POR.

Single-cell transcriptome analysis of macrophage subpopulations contributing to chemotherapy resistance in ovarian cancer

BackgroundOvarian cancer, a fatal gynecological malignancy, is primarily managed through surgery and chemotherapy. However, a significant challenge arises as patients frequently experience relapse due to chemotherapy resistance. This study delves into the complex functions and underlying mechanisms of macrophages in chemotherapy resistance in ovarian cancer. MethodThe single-cell transcriptome sequencing data of ovarian cancer with or without chemotherapy were analyzed. Then, corresponding cell types were identified, and macrophages were extracted from all cells. Following the standardized single-cell analysis using the Seurat package, 15 distinct macrophage clusters were found and differentially expressed genes among them were analyzed. Moreover, their association with chemotherapy resistance was explored through cell proportions and gene expression. ResultIn the single-cell transcriptomic analysis of ovarian cancer tissues before and after chemotherapy, the cellular proportion of CXCL5+ macrophages, THBS1+ macrophages, and MMP9+ macrophages were significantly increased following chemotherapy. Further investigation revealed that these macrophage subpopulations upregulated the expression of multiple pro-tumorigenic angiogenic or invasive factors, in addition to CXCL5, THBS1, and MMP9, including CTSL, CXCL1, and CCL18. Finally, pathway enrichment analysis revealed the significant activation of signaling pathways, such as NOD-like receptor, MAPK, and TNF in these macrophage subpopulations, which provides direction for studying the mechanism of these subpopulations. ConclusionCXCL5+, THBS1+, and MMP9+ macrophage subpopulations exhibit an increased cellular prevalence post-chemotherapy and pro-tumorigenic molecular expression profiles, suggesting a close association with chemoresistance in ovarian cancer. These findings contribute to our understanding of the roles and mechanisms of macrophages in ovarian cancer chemoresistance, providing a theoretical basis and direction for the development of therapies targeting macrophages in overcoming ovarian cancer chemoresistance.

Transcriptomic Profiles of Long Noncoding RNAs and Their Target Protein-Coding Genes Reveals Speciation Adaptation on the Qinghai-Xizang (Tibet) Plateau in Orinus.

Long noncoding RNAs (lncRNAs) are RNA molecules longer than 200 nt, which lack the ability to encode proteins and are involved in multifarious growth, development, and regulatory processes in plants and mammals. However, the environmental-regulated expression profiles of lncRNAs in Orinus that may associated with their adaptation on the Qinghai-Xizang (Tibet) Plateau (QTP) have never been characterized. Here, we utilized transcriptomic sequencing data of two Orinus species (O. thoroldii and O. kokonoricus) to identify 1624 lncRNAs, including 1119 intergenic lncRNAs, 200 antisense lncRNAs, five intronic lncRNAs, and 300 sense lncRNAs. In addition, the evolutionary relationships of Orinus lncRNAs showed limited sequence conservation among 39 species, which implied that Orinus-specific lncRNAs contribute to speciation adaptation evolution. Furthermore, considering the cis-regulation mechanism, from 286 differentially expressed lncRNAs (DElncRNAs) and their nearby protein coding genes (PCGs) between O. thoroldii and O. kokonoricus, 128 lncRNA-PCG pairs were obtained in O. thoroldii, whereas 92 lncRNA-PCG pairs were obtained in O. kokonoricus. In addition, a total of 19 lncRNA-PCG pairs in O. thoroldii and 14 lncRNA-PCG pairs in O. kokonoricus were found to participate in different biological processes, indicating that the different expression profiles of DElncRNAs between O. thoroldii and O. kokonoricus were associated with their adaptation at different elevations on the QTP. We also found several pairs of DElncRNA nearby transcription factors (TFs), indicating that these DElncRNAs regulate the expression of TFs to aid O. thoroldii in adapting to the environment. Therefore, this work systematically identified a series of lncRNAs in Orinus, laying the groundwork for further exploration into the biological function of Orinus in environmental adaptation.

Panoramic RNA expression of fibroblast growth factors in human glioblastoma tissues and the impact on the survival of patients.

Fibroblast growth factors (FGFs) have a key role in various critical steps of tumor growth and progression through effects on angiogenesis, inflammation and the growth and invasion of malignant cells. Nevertheless, the role of the FGF family in human glioblastoma (GBM) has been rarely studied. The objective of the present study was to assess the RNA expression of all FGF family members in tissues obtained from patients with GBM and to analyze the association between FGF expression and the survival of these patients. For this, the RNA expression of FGF family members in the malignant and proximal tissues of 12 patients with GBM was determined by analyzing high-throughput RNA transcriptome sequencing data uploaded to the National Center for Biotechnology Information database. The relationship between FGF genes and the survival of patients with GBM and glioma was also respectively studied by analyzing data from The Cancer Genome Atlas database using the Gene Expression Profiling Interactive Analysis tool. The results showed that the expression of FGF1, FGF17, FGF20 and FGF22 in GBM tissues was lower than that in adjacent tissues, with a difference of >2 times. Analysis of the overall survival of patients with GBM indicated there were no significant relationships between the expression of FGF1, FGF17, FGF20, FGF22 and overall survival. Analysis of the overall survival of patients with glioma showed that glioma patients with low FGF1 expression achieved a longer survival time than patients with high FGF1 expression; however, high expression of FGF17 and FGF22 indicated a longer survival time. In summary, the results of the present study demonstrated the panoramic expression of FGF family members in patients with GBM, and indicated that FGF1, FGF17 and FGF22 did not affect the survival of patients with GBM, but had a notable influence on the survival of patients with glioma.