A transcription-independent mechanism determines rapid periodic fluctuations of BRCA1 expression.

BRCA1 expression is highly regulated to prevent genomic instability and tumorigenesis. Dysregulation of BRCA1 expression correlates closely with sporadic basal-like breast cancer and ovarian cancer. The most significant characteristic of BRCA1 regulation is periodic expression fluctuation throughout the cell cycle, which is important for the orderly progression of different DNA repair pathways throughout the various cell cycle phases and for further genomic stability. However, the underlying mechanism driving this phenomenon is poorly understood. Here, we demonstrate that RBM10-mediated RNA alternative splicing coupled to nonsense-mediated mRNA decay (AS-NMD), rather than transcription, determines the periodic fluctuations in G1/S-phase BRCA1 expression. Furthermore, AS-NMD broadly regulates the expression of period genes, such as DNA replication-related genes, in an uneconomical but more rapid manner. In summary, we identified an unexpected posttranscriptional mechanism distinct from canonical processes that mediates the rapid regulation of BRCA1 as well as other period gene expression during the G1/S-phase transition and provided insights into potential targets for cancer therapy.

Higher TP53BP2 expression is associated with HBsAg loss in peginterferon-α-treated patients with chronic hepatitis B.

BACKGROUND & AIMS: HBsAg loss is only observed in a small proportion of patients with chronic hepatitis B (CHB) who undergo interferon treatment. Investigating the host factors crucial for functional cure of CHB can aid in identifying individuals who would benefit from peginterferon-α (Peg-IFNα) therapy. METHODS: We conducted a genome-wide association study (GWAS) by enrolling 48 patients with CHB who achieved HBsAg loss after Peg-IFNα treatment and 47 patients who didn't. In the validation stage, we included 224 patients, of whom 90 had achieved HBsAg loss, to validate the identified significant single nucleotide polymorphisms. To verify the functional involvement of the candidate genes identified, we performed a series of in vitro and in vivo experiments. RESULTS: GWAS results indicated a significant association between the rs7519753 C allele and serum HBsAg loss in patients with CHB after Peg-IFNα treatment (p = 4.85 × 10-8, odds ratio = 14.47). This association was also observed in two independent validation cohorts. Expression quantitative trait locus analysis revealed higher hepatic TP53BP2 expression in individuals carrying the rs7519753 C allele (p = 2.90 × 10-6). RNA-sequencing of liver biopsies from patients with CHB after Peg-IFNα treatment revealed that hepatic TP53BP2 levels were significantly higher in the HBsAg loss group compared to the HBsAg persistence group (p = 0.035). In vitro and in vivo experiments demonstrated that loss of TP53BP2 decreased interferon-stimulated gene levels and the anti-HBV effect of IFN-α. Mechanistically, TP53BP2 was found to downregulate SOCS2, thereby facilitating JAK/STAT signaling. CONCLUSION: The rs7519753 C allele is associated with elevated hepatic TP53BP2 expression and an increased probability of serum HBsAg loss post-Peg-IFNα treatment in patients with CHB. TP53BP2 enhances the response of the hepatocyte to IFN-α by suppressing SOCS2 expression. IMPACT AND IMPLICATIONS: Chronic hepatitis B (CHB) remains a global public health issue. Although current antiviral therapies are more effective in halting disease progression, only a few patients achieve functional cure for hepatitis B with HBsAg loss, highlighting the urgent need for a cure for CHB. This study revealed that the rs7519753 C allele, which is associated with high expression of hepatic TP53BP2, significantly increases the likelihood of serum HBsAg loss in patients with CHB undergoing Peg-IFNα treatment. This finding not only provides a promising predictor for HBsAg loss but identifies a potential therapeutic target for Peg-IFNα treatment. We believe our results are of great interest to a wide range of stakeholders based on their potential clinical implications.

MTM: a multi-task learning framework to predict individualized tissue gene expression profiles.

MOTIVATION: Transcriptional profiles of diverse tissues provide significant insights in both fundamental and translational researches, while transcriptome information is not always available for tissues that require invasive biopsies. Alternatively, predicting tissue expression profiles from more accessible "surrogate" samples, especially blood transcriptome, has become a promising strategy when invasive procedures are not practical. However, existing approaches ignore tissue-shared intrinsic relevance, inevitably limiting predictive performance. RESULTS: We propose a unified deep learning-based multi-task learning framework, multi-tissue transcriptome mapping (MTM), enabling the prediction of individualized expression profiles from any available tissue of an individual. By jointly leveraging individualized cross-tissue information from reference samples through multi-task learning, MTM achieves superior sample-level and gene-level performance on unseen individuals. With the high prediction accuracy and the ability to preserve individualized biological variations, MTM could facilitate both fundamental and clinical biomedical research. AVAILABILITY AND IMPLEMENTATION: MTM's code and documentation are available upon publication on GitHub (https://github.com/yangence/MTM).

A unique cell wall synthetic response evoked by glucosamine determines pathogenicity-associated fungal cellular differentiation.

The yeast-to-hypha transition is tightly associated with pathogenicity in many human pathogenic fungi, such as the model fungal pathogen Cryptococcus neoformans, which is responsible for approximately 180,000 deaths annually. In this pathogen, the yeast-to-hypha transition can be initiated by distinct stimuli: mating stimulation or glucosamine (GlcN), the monomer of cell wall chitosan. However, it remains poorly understood how the signal specificity for Cryptococcus morphological transition by disparate stimuli is ensured. Here, by integrating temporal expression signature analysis and phenome-based clustering evaluation, we demonstrate that GlcN specifically triggers a unique cellular response, which acts as a critical determinant underlying the activation of GlcN-induced filamentation (GIF). This cellular response is defined by an unusually hyperactive cell wall synthesis that is highly ATP-consuming. A novel cell surface protein Gis1 was identified as the indicator molecule for the GlcN-induced cell wall response. The Mpk1-directed cell wall pathway critically bridges global cell wall gene induction and intracellular ATP supply, ensuring the Gis1-dependent cell wall response and the stimulus specificity of GIF. We further reveal that the ability of Mpk1 to coordinate the cell wall response and GIF activation is conserved in different Cryptococcus pathogens. Phosphoproteomics-based profiling together with genetic and phenotypic analysis revealed that the Mpk1 kinase mediates the regulatory specificity of GIF through a coordinated downstream regulatory network centered on Skn7 and Crz1. Overall, our findings discover an unprecedented and conserved cell wall biosynthesis-dependent fungal differentiation commitment mechanism, which enables the signal specificity of pathogenicity-related dimorphism induced by GlcN in Cryptococcus pathogens.

PINA 3.0: mining cancer interactome.

Protein-protein interactions (PPIs) are crucial to mediate biological functions, and understanding PPIs in cancer type-specific context could help decipher the underlying molecular mechanisms of tumorigenesis and identify potential therapeutic options. Therefore, we update the Protein Interaction Network Analysis (PINA) platform to version 3.0, to integrate the unified human interactome with RNA-seq transcriptomes and mass spectrometry-based proteomes across tens of cancer types. A number of new analytical utilities were developed to help characterize the cancer context for a PPI network, which includes inferring proteins with expression specificity and identifying candidate prognosis biomarkers, putative cancer drivers, and therapeutic targets for a specific cancer type; as well as identifying pairs of co-expressing interacting proteins across cancer types. Furthermore, a brand-new web interface has been designed to integrate these new utilities within an interactive network visualization environment, which allows users to quickly and comprehensively investigate the roles of human interacting proteins in a cancer type-specific context. PINA is freely available at https://omics.bjcancer.org/pina/.

LncRNA-AC006129.1 reactivates a SOCS3-mediated anti-inflammatory response through DNA methylation-mediated CIC downregulation in schizophrenia.

Schizophrenia is a complex genetic disorder, the non-Mendelian features of which are likely complicated by epigenetic factors yet to be elucidated. Here, we performed RNA sequencing of peripheral blood RNA from monozygotic twins discordant for schizophrenia, and identified a schizophrenia-associated upregulated long noncoding RNA (lncRNA, AC006129.1) that participates in the inflammatory response by enhancing SOCS3 and CASP1 expression in schizophrenia patients and further validated this finding in AC006129.1-overexpressing mice showing schizophrenia-related abnormal behaviors. We find that AC006129.1 binds to the promoter region of the transcriptional repressor Capicua (CIC), facilitates the interactions of DNA methyltransferases with the CIC promoter, and promotes DNA methylation-mediated CIC downregulation, thereby ameliorating CIC-induced SOCS3 and CASP1 repression. Derepression of SOCS3 enhances the anti-inflammatory response by inhibiting JAK/STAT-signaling activation. Our findings reveal an epigenetic mechanism with etiological and therapeutic implications for schizophrenia.

CVCDAP: an integrated platform for molecular and clinical analysis of cancer virtual cohorts.

Recent large-scale multi-omics studies resulted in quick accumulation of an overwhelming amount of cancer-related data, which provides an unprecedented resource to interrogate diverse questions. While certain existing web servers are valuable and widely used, analysis and visualization functions with regard to re-investigation of these data at cohort level are not adequately addressed. Here, we present CVCDAP, a web-based platform to deliver an interactive and customizable toolbox off the shelf for cohort-level analysis of TCGA and CPTAC public datasets, as well as user uploaded datasets. CVCDAP allows flexible selection of patients sharing common molecular and/or clinical characteristics across multiple studies as a virtual cohort, and provides dozens of built-in customizable tools for seamless genomic, transcriptomic, proteomic and clinical analysis of a single virtual cohort, as well as, to compare two virtual cohorts with relevance. The flexibility and analytic competence of CVCDAP empower experimental and clinical researchers to identify new molecular mechanisms and develop potential therapeutic approaches, by building and analyzing virtual cohorts for their subject of interests. We demonstrate that CVCDAP can conveniently reproduce published findings and reveal novel insights by two applications. The CVCDAP web server is freely available at https://omics.bjcancer.org/cvcdap/.

Emergence of W272C Substitution in Hmg1 in a Triazole-Resistant Isolate of Aspergillus fumigatus from a Chinese Patient with Chronic Cavitary Pulmonary Aspergillosis.

Recently, mutations in the 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase gene (hmg1) have been identified to be associated with triazole resistance in Aspergillus fumigatus. Here, we describe the first case of the G929C mutation in the hmg1 gene, leading to the W272C amino acid substitution, in a triazole-resistant isolate of A. fumigatus recovered from a chronic cavitary pulmonary aspergillosis patient who failed voriconazole therapy in China.

Development of CRISPR-Cas9 genome editing system in Talaromyces marneffei.

Talaromyces marneffei is an important pathogenic thermally dimorphic fungus causing systemic talaromycosis mainly prevalent in Southeast Asia. The dimorphic transition between mycelium and yeast is considered crucial for the pathogenicity of T. marneffei. However, the lack of genetic toolbox has been a major impediment for understanding its pathogenicity. Here a CRISPR-Cas9 system was developed to facilitate genetic manipulations in this organism. In this study, the CRISPR-Cas9 gene editing system uses a native U6 snRNA promoter from T. marneffei to drive the expression of sgRNA. Employing this system and PEG-mediated protoplast transformation, the sakA gene was mutated. Sanger sequencing confirmed nearly 40% site-directed mutation rate. The phenotype analysis confirmed the sakA gene function in T. marneffei dimorphic transition. Our study provided a powerful genome-manipulating tool, which could accelerate studies on T. marneffei for further revealing the mechanisms of its pathogenicity.

Rapid identification of pathogens associated with ventilator-associated pneumonia by Nanopore sequencing.

BACKGROUND: Aetiology detection is crucial in the diagnosis and treatment of ventilator-associated pneumonia (VAP). However, the detection method needs improvement. In this study, we used Nanopore sequencing to build a quick detection protocol and compared the efficiency of different methods for detecting 7 VAP pathogens. METHODS: The endotracheal aspirate (ETA) of 83 patients with suspected VAP from Peking University Third Hospital (PUTH) was collected, saponins were used to deplete host genomes, and PCR- or non-PCR-amplified library construction methods were used and compared. Sequence was performed with MinION equipment and local data analysis methods were used for sequencing and data analysis. RESULTS: Saponin depletion effectively removed 11 of 12 human genomes, while most pathogenic bacterial genome results showed no significant difference except for S. pneumoniae. Moreover, the average sequence time decreased from 19.6 h to 3.62 h. The non-PCR amplification method and PCR amplification method for library build has a similar average sensitivity (85.8% vs. 86.35%), but the non-PCR amplification method has a better average specificity (100% VS 91.15%), and required less time. The whole method takes 5-6 h from ETA extraction to pathogen classification. After analysing the 7 pathogens enrolled in our study, the average sensitivity of metagenomic sequencing was approximately 2.4 times higher than that of clinical culture (89.15% vs. 37.77%), and the average specificity was 98.8%. CONCLUSIONS: Using saponins to remove the human genome and a non-PCR amplification method to build libraries can be used for the identification of pathogens in the ETA of VAP patients within 6 h by MinION, which provides a new approach for the rapid identification of pathogens in clinical departments.

Epistasis and destabilizing mutations shape gene expression variability in humans via distinct modes of action.

Increasing evidence shows that phenotypic variance is genetically determined, but the underlying mechanisms of genetic control over the variance remain obscure. Here, we conducted variance-association mapping analyses to identify expression variability QTLs (evQTLs), i.e. genomic loci associated with gene expression variance, in humans. We discovered that common genetic variants may contribute to increasing gene expression variance via two distinct modes of action­epistasis and destabilization. Specifically, epistasis explains a quarter of the identified evQTLs, of which the formation is attributed to the presence of 'third-party' eQTLs that influence the gene expression mean in a fraction, rather than the entire set, of sampled individuals. On the other hand, the destabilization model explains the other three-quarters of evQTLs, caused by mutations that disrupt the stability of the transcription process of genes. To show the destabilizing effect, we measured discordant gene expression between monozygotic twins, and estimated the stability of gene expression in single samples using repetitive qRT-PCR assays. The mutations that cause destabilizing evQTLs were found to be associated with more pronounced expression discordance between twin pairs and less stable gene expression in single samples. Together, our results suggest that common genetic variants work either interactively or independently to shape the variability of gene expression in humans. Our findings contribute to the understanding of the mechanisms of genetic control over phenotypic variance and may have implications for the development of variance-centred analytic methods for quantitative trait mapping.

The lncRNA RZE1 Controls Cryptococcal Morphological Transition.

In the fungal pathogen Cryptococcus neoformans, the switch from yeast to hypha is an important morphological process preceding the meiotic events during sexual development. Morphotype is also known to be associated with cryptococcal virulence potential. Previous studies identified the regulator Znf2 as a key decision maker for hypha formation and as an anti-virulence factor. By a forward genetic screen, we discovered that a long non-coding RNA (lncRNA) RZE1 functions upstream of ZNF2 in regulating yeast-to-hypha transition. We demonstrate that RZE1 functions primarily in cis and less effectively in trans. Interestingly, RZE1's function is restricted to its native nucleus. Accordingly, RZE1 does not appear to directly affect Znf2 translation or the subcellular localization of Znf2 protein. Transcriptome analysis indicates that the loss of RZE1 reduces the transcript level of ZNF2 and Znf2's prominent downstream targets. In addition, microscopic examination using single molecule fluorescent in situ hybridization (smFISH) indicates that the loss of RZE1 increases the ratio of ZNF2 transcripts in the nucleus versus those in the cytoplasm. Taken together, this lncRNA controls Cryptococcus yeast-to-hypha transition through regulating the key morphogenesis regulator Znf2. This is the first functional characterization of a lncRNA in a human fungal pathogen. Given the potential large number of lncRNAs in the genomes of Cryptococcus and other fungal pathogens, the findings implicate lncRNAs as an additional layer of genetic regulation during fungal development that may well contribute to the complexity in these "simple" eukaryotes.

Aberrant gene expression in humans.

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions.

Signature gene expression reveals novel clues to the molecular mechanisms of dimorphic transition in Penicillium marneffei.

Systemic dimorphic fungi cause more than one million new infections each year, ranking them among the significant public health challenges currently encountered. Penicillium marneffei is a systemic dimorphic fungus endemic to Southeast Asia. The temperature-dependent dimorphic phase transition between mycelium and yeast is considered crucial for the pathogenicity and transmission of P. marneffei, but the underlying mechanisms are still poorly understood. Here, we re-sequenced P. marneffei strain PM1 using multiple sequencing platforms and assembled the genome using hybrid genome assembly. We determined gene expression levels using RNA sequencing at the mycelial and yeast phases of P. marneffei, as well as during phase transition. We classified 2,718 genes with variable expression across conditions into 14 distinct groups, each marked by a signature expression pattern implicated at a certain stage in the dimorphic life cycle. Genes with the same expression patterns tend to be clustered together on the genome, suggesting orchestrated regulations of the transcriptional activities of neighboring genes. Using qRT-PCR, we validated expression levels of all genes in one of clusters highly expressed during the yeast-to-mycelium transition. These included madsA, a gene encoding MADS-box transcription factor whose gene family is exclusively expanded in P. marneffei. Over-expression of madsA drove P. marneffei to undergo mycelial growth at 37°C, a condition that restricts the wild-type in the yeast phase. Furthermore, analyses of signature expression patterns suggested diverse roles of secreted proteins at different developmental stages and the potential importance of non-coding RNAs in mycelium-to-yeast transition. We also showed that RNA structural transition in response to temperature changes may be related to the control of thermal dimorphism. Together, our findings have revealed multiple molecular mechanisms that may underlie the dimorphic transition in P. marneffei, providing a powerful foundation for identifying molecular targets for mechanism-based interventions.

Exploiting aberrant mRNA expression in autism for gene discovery and diagnosis.

Autism spectrum disorder (ASD) is characterized by substantial phenotypic and genetic heterogeneity, which greatly complicates the identification of genetic factors that contribute to the disease. Study designs have mainly focused on group differences between cases and controls. The problem is that, by their nature, group difference-based methods (e.g., differential expression analysis) blur or collapse the heterogeneity within groups. By ignoring genes with variable within-group expression, an important axis of genetic heterogeneity contributing to expression variability among affected individuals has been overlooked. To this end, we develop a new gene expression analysis method-aberrant gene expression analysis, based on the multivariate distance commonly used for outlier detection. Our method detects the discrepancies in gene expression dispersion between groups and identifies genes with significantly different expression variability. Using this new method, we re-visited RNA sequencing data generated from post-mortem brain tissues of 47 ASD and 57 control samples. We identified 54 functional gene sets whose expression dispersion in ASD samples is more pronounced than that in controls, as well as 76 co-expression modules present in controls but absent in ASD samples due to ASD-specific aberrant gene expression. We also exploited aberrantly expressed genes as biomarkers for ASD diagnosis. With a whole blood expression data set, we identified three aberrantly expressed gene sets whose expression levels serve as discriminating variables achieving >70 % classification accuracy. In summary, our method represents a novel discovery and diagnostic strategy for ASD. Our findings may help open an expression variability-centered research avenue for other genetically heterogeneous disorders.

Origin and evolution of carnivorism in the Ascomycota (fungi).

Carnivorism is one of the basic life strategies of fungi. Carnivorous fungi possess the ability to trap and digest their preys by sophisticated trapping devices. However, the origin and development of fungal carnivorism remains a gap in evolution biology. In this study, five protein-encoding genes were used to construct the phylogeny of the carnivorous fungi in the phylum Ascomycota; these fungi prey on nematodes by means of specialized trapping structures such as constricting rings and adhesive traps. Our analysis revealed a definitive pattern of evolutionary development for these trapping structures. Molecular clock calibration based on two fossil records revealed that fungal carnivorism diverged from saprophytism about 419 Mya, which was after the origin of nematodes about 550-600 Mya. Active carnivorism (fungi with constricting rings) and passive carnivorism (fungi with adhesive traps) diverged from each other around 246 Mya, shortly after the occurrence of the Permian-Triassic extinction event about 251.4 Mya. The major adhesive traps evolved around 198-208 Mya, which was within the time frame of the Triassic-Jurassic extinction event about 201.4 Mya. However, no major carnivorous ascomycetes divergence was correlated to the Cretaceous-Tertiary extinction event, which occurred more recently (about 65.5 Mya). Therefore, a causal relationship between mass extinction events and fungal carnivorism evolution is not validated in this study. More evidence including additional fossil records is needed to establish if fungal carnivorism evolution was a response to mass extinction events.

Mapping and genotypic analysis of the NK-lysin gene in chicken.

BACKGROUND: Antimicrobial peptides (AMP) are important elements of the first line of defence against pathogens in animals. NK-lysin is a cationic AMP that plays a critical role in innate immunity. The chicken NK-lysin gene has been cloned and its antimicrobial and anticancer activity has been described but its location in the chicken genome remains unknown. Here, we mapped the NK-lysin gene and examined the distribution of a functionally significant single nucleotide polymorphism (SNP) among different chicken inbred lines and heritage breeds. RESULTS: A 6000 rad radiation hybrid panel (ChickRH6) was used to map the NK-lysin gene to the distal end of chromosome 22. Two additional genes, the adipocyte enhancer-binding protein 1-like gene (AEBP1) and the DNA polymerase delta subunit 2-like (POLD2) gene, are located in the same NW_003779909 contig as NK-lysin, and were thus indirectly mapped to chromosome 22 as well. Previously, we reported a functionally significant SNP at position 271 of the NK-lysin coding sequence in two different chicken breeds. Here, we examined this SNP and found that the A allele appears to be more common than the G allele in these heritage breeds and inbred lines. CONCLUSIONS: The chicken NK-lysin gene mapped to the distal end of chromosome 22. Two additional genes, AEBP1 and POLD2, were indirectly mapped to chromosome 22 also. SNP analyses revealed that the A allele, which encodes a peptide with a higher antimicrobial activity, is more common than the G allele in our tested inbred lines and heritage breeds.

Unraveling the molecular basis of temperature-dependent genetic regulation in Penicillium marneffei.

Penicillium marneffei is an opportunistic fungal pathogen endemic in Southeast Asia, causing lethal systemic infections in immunocompromised patients. P. marneffei grows in a mycelial form at the ambient temperature of 25°C and transitions to a yeast form at 37°C. The ability to alternate between the mycelial and yeast forms at different temperatures, namely, thermal dimorphism, has long been considered critical for the pathogenicity of P. marneffei, yet the underlying genetic mechanisms remain elusive. Here we employed high-throughput sequencing to unravel global transcriptional profiles of P. marneffei PM1 grown at 25 and 37°C. Among ∼11,000 protein-coding genes, 1,447 were overexpressed and 1,414 were underexpressed at 37°C. Counterintuitively, heat-responsive genes, predicted in P. marneffei through sequence comparison, did not tend to be overexpressed at 37°C. These results suggest that P. marneffei may take a distinct strategy of genetic regulation at the elevated temperature; the current knowledge concerning fungal heat response, based on studies of model fungal organisms, may not be applicable to P. marneffei. Our results further showed that the tandem repeat sequences (TRSs) are overrepresented in coding regions of P. marneffei genes, and TRS-containing genes tend to be overexpressed at 37°C. Furthermore, genomic sequences and expression data were integrated to characterize gene clusters, multigene families, and species-specific genes of P. marneffei. In sum, we present an integrated analysis and a comprehensive resource toward a better understanding of temperature-dependent genetic regulation in P. marneffei.

Lower ratio of IMPDH1 to IMPDH2 sensitizes gliomas to chemotherapy.

Gliomas are the most common primary tumors of the central nervous system, with approximately half of patients presenting with the most aggressive form of glioblastoma. Although several molecular markers for glioma have been identified, they are not sufficient to predict the prognosis due to the extensive genetic heterogeneity within glioma. Our study reveals that the ratio of IMPDH1 to IMPDH2 expression levels serves as a molecular indicator for glioma treatment prognosis. Patients with a higher IMPDH1/IMPDH2 ratio exhibit a worse prognosis, while those with a lower ratio display a more favorable prognosis. We further demonstrate that IMPDH1 plays a crucial role in maintaining cellular GTP/GDP levels following DNA damage compared to IMPDH2. In the absence of IMPDH1, cells experience an imbalance in the GTP/GDP ratio, impairing DNA damage repair capabilities and rendering them more sensitive to TMZ. This study not only introduces a novel prognostic indicator for glioma clinical diagnosis but also offers innovative insights for precise and stratified glioma treatment.

Unraveling the dynamic transcriptomic changes during the dimorphic transition of Talaromyces marneffei through time-course analysis.

Introduction: Systemic dimorphic fungi pose a significant public health challenge, causing over one million new infections annually. The dimorphic transition between saprophytic mycelia and pathogenic yeasts is strongly associated with the pathogenesis of dimorphic fungi. However, despite the dynamic nature of dimorphic transition, the current omics studies focused on dimorphic transition primarily employ static strategies, partly due to the lack of suitable dynamic analytical methods. Methods: We conducted time-course transcriptional profiling during the dimorphic transition of Talaromyces marneffei, a model organism for thermally dimorphic fungi. To capture non-uniform and nonlinear transcriptional changes, we developed DyGAM-NS (dynamic optimized generalized additive model with natural cubic smoothing). The performance of DyGAM-NS was evaluated by comparison with seven other commonly used time-course analysis methods. Based on dimorphic transition induced genes (DTIGs) identified by DyGAM-NS, cluster analysis was utilized to discern distinct gene expression patterns throughout dimorphic transitions of T. marneffei. Simultaneously, a gene expression regulatory network was constructed to probe pivotal regulatory elements governing the dimorphic transitions. Results: By using DyGAM-NS, model, we identified 5,223 DTIGs of T. marneffei. Notably, the DyGAM-NS model showcases performance on par with or superior to other commonly used models, achieving the highest F1 score in our assessment. Moreover, the DyGAM-NS model also demonstrates potential in predicting gene expression levels throughout temporal processes. The cluster analysis of DTIGs suggests divergent gene expression patterns between mycelium-to-yeast and yeast-to-mycelium transitions, indicating the asymmetrical nature of two transition directions. Additionally, leveraging the identified DTIGs, we constructed a regulatory network for the dimorphic transition and identified two zinc finger-containing transcription factors that potentially regulate dimorphic transition in T. marneffei. Discussion: Our study elucidates the dynamic transcriptional profile changes during the dimorphic transition of T. marneffei. Furthermore, it offers a novel perspective for unraveling the underlying mechanisms of fungal dimorphism, emphasizing the importance of dynamic analytical methods in understanding complex biological processes.