WGCNA: an R package for weighted correlation network analysis

Exploring the hub Genes and Potential Mechanisms of Complement system-related Genes in Parkinson Disease: Based on Transcriptome Sequencing and Mendelian Randomization

An accurate diagnosis of Parkinson's disease (PD) remains challenging and the exact cause of the disease is unclean. The aims are to identify hub genes associated with the complement system in PD and to explore their underlying molecular mechanisms. Initially, differentially expressed genes (DEGs) and key module genes related to PD were mined through differential expression analysis and WGCNA. Then, differentially expressed CSRGs (DE-CSRGs) were obtained by intersecting the DEGs, key module genes and CSRGs. Subsequently, MR analysis was executed to identify genes causally associated with PD. Based on genes with significant MR results, the expression level and diagnostic performance verification were achieved to yield hub genes. Functional enrichment and immune infiltration analyses were accomplished to insight into the pathogenesis of PD. qRT-PCR was employed to evaluate the expression levels of hub genes. After MR analysis and related verification, CD93, CTSS, PRKCD and TLR2 were finally identified as hub genes. Enrichment analysis indicated that the main enriched pathways for hub genes. Immune infiltration analysis found that the hub genes showed significant correlation with a variety of immune cells (such as myeloid-derived suppressor cell and macrophage). In the qRT-PCR results, the expression levels of CTSS, PRKCD and TLR2 were consistent with those we obtained from public databases. Hence, we mined four hub genes associated with complement system in PD which provided novel perspectives for the diagnosis and treatment of PD.

Integrative multi-omics analysis reveals genetic and heterotic contributions to male fertility and yield in potato

The genetic analysis of potato is hampered by the complexity of tetrasomic inheritance. An ongoing effort aims to transform the clonally propagated tetraploid potato into a seed-propagated diploid crop, which would make genetic analyses much easier owing to disomic inheritance. Here, we construct and report the large-scale genetic and heterotic characteristics of a diploid F2 potato population derived from the cross of two highly homozygous inbred lines. We investigate 20,382 traits generated from multi-omics dataset and identify 25,770 quantitative trait loci (QTLs). Coupled with gene expression data, we construct a systems-genetics network for gene discovery in potatoes. Importantly, we explore the genetic basis of heterosis in this population, especially for yield and male fertility heterosis. We find that positive heterotic effects of yield-related QTLs and negative heterotic effects of metabolite QTLs (mQTLs) contribute to yield heterosis. Additionally, we identify a PME gene with a dominance heterotic effect that plays an important role in male fertility heterosis. This study provides genetic resources for the potato community and will facilitate the application of heterosis in diploid potato breeding.

Integrative analyses of bulk and single-cell RNA-seq reveals the correlation between SPP1+ macrophages and resistance to neoadjuvant chemoimmunotherapy in esophageal squamous cell carcinoma

Neoadjuvant chemoimmunotherapy (NACI) has significant implications for the treatment of esophageal cancer. However, its clinical efficacy varies considerably among patients, necessitating further investigation into the underlying mechanisms. The rapid advancement of single-cell RNA sequencing (scRNA-seq) technology facilitates the analysis of patient heterogeneity at the cellular level, particularly regarding treatment outcomes. In this study, we first analyzed scRNA-seq data of esophageal squamous cell carcinoma (ESCC) following NACI, obtained from the Gene Expression Omnibus (GEO) database. After performing dimensionality reduction, clustering, and annotation on the scRNA-seq data, we employed CellChat to investigate differences in cell-cell communication among samples from distinct efficacy groups. The results indicated that macrophages in the non-responder exhibited stronger cell communication intensity compared to those in responders, with SPP1 and GALECTIN signals showing the most significant differences between the two groups. This finding underscores the crucial role of macrophages in the efficacy of NACI. Subsequently, reclustering of macrophages revealed that Mac-SPP1 may be primarily responsible for treatment resistance, while Mac-C1QC appears to promote T cell activation. Finally, we conducted transcriptome sequencing on ESCC tissues obtained from 32 patients who underwent surgery following NACI. Utilizing CIBERSORT, CIBERSORTx, and WGCNA, we analyzed the heterogeneity of tumor microenvironment among different efficacy groups and validated the correlation between SPP1+ macrophages and resistance to NACI in ESCC using publicly available transcriptome sequencing datasets. These findings suggest that SPP1+ macrophages may represent a key factor contributing to resistance against NACI in ESCC.

Elucidating Thermothielavioides terrestris secretome changes for improved saccharification of mild steam-pretreated spruce

BACKGROUND

The efficient use of softwood in biorefineries is hampered by its recalcitrance to enzymatic saccharification. In the present study, the fungus Thermothielavioides terrestris LPH172 was cultivated on three steam-pretreated spruce materials (STEX180°C/auto, STEX210°C/auto, and STEX210°C/H2SO4), characterized by different hemicellulose content and structure, as well as on untreated biomass. The aim of the study was to map substrate-induced changes in the secretome of T. terrestris grown on differently treated spruce materials and to evaluate the hydrolytic efficiency of the secretome as supplement for a commercial enzyme mixture.

RESULTS

The cultivation of T. terrestris was monitored by endo-cellulase, endo-xylanase, endo-mannanase, laccase, and peroxidase activity measurements. Proteomic analysis was performed on the secretomes induced by the spruce materials to map the differences in enzyme production. Growth of T. terrestris on STEX180°C/auto and STEX210°C/auto induced higher expression level of mannanases and mannosidases of the GH5_7 CAZy family compared to cultivation on the other materials. Cultivation on untreated biomass led to overexpression of GH47, GH76, and several hemicellulose debranching enzymes compared to the cultivation on the pretreated materials. T. terrestris grown on untreated, STEX180°C/auto and STEX210°C/auto induced three arabinofuranosidases of the GH43 and GH62 families; while growth on STEX210°C/H2SO4 induced a GH51 arabinofuranosidase and a GH115 glucuronidase. All secretomes contained five lytic polysaccharide monooxygenases of the AA9 family. Supplementation of Celluclast® + Novozym188 with the secretome obtained by growing the fungus grown on STEX180°C/auto achieved a twofold higher release of mannose from spruce steam-pretreated with acetic acid as catalyst, compared to the commercial enzyme cocktail alone.

CONCLUSIONS

Minor changes in the structure and composition of spruce affect the composition of fungal secretomes, with differences in some classes explaining an increased hydrolytic efficiency. As demonstrated here, saccharification of spruce biomass with commercial enzyme cocktails can be further enhanced by supplementation with tailor-made secretomes.

Identification of sanguinarine as a novel antagonist for perfluorooctanoate/perfluorooctane sulfonate-induced senescence of hepatocytes: An integrated computational and experimental analysis

Perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS), two prominent per- and polyfluoroalkyl substances (PFASs), are potentially harmful to many human organs. However, there only exist limited methods to mitigate their health hazards. The aim of this study is to combine a bioinformatics analysis with in vitro experiments to discover small molecules that can alleviate liver damage caused by PFOA/PFOS. We identified 192 and 82 key genes related to hepatocytes exposed to PFOA and PFOS, respectively. The functional enrichment analysis of key genes suggested cellular senescence may be important in PFOA/PFOS-induced hepatotoxicity. The in vitro models revealed that PFOA/PFOS led to hepatocyte senescence by increasing the activity of SA-β-gal, inducing mitochondrial dysfunction, impacting cell cycle arrest, and elevating the expressions of p21, p53, IL-1β, and SASP-related cytokines. The drug-target gene set enrichment analysis method was employed to compare the transcriptome data from the Gene Expression Omnibus database (GEO), Comparative Toxicogenomics Database (CTD), and the high-throughput experiment- and reference-guided database (HERB), and 21 traditional Chinese medicines (TCMs) were identified that may alleviate PFOA/PFOS-induced liver aging. The experimental results of co-exposure to PFOA/PFOS and TCMs showed that sanguinarine has particular promise in alleviating cellular senescence caused by PFOA/PFOS. Further investigations revealed that the mTOR-p53 signaling pathway was involved in PFOA/PFOS-mediated hepatic senescence and can be blocked using sanguinarine.

Bulk integrated single-cell-spatial transcriptomics reveals the impact of preoperative chemotherapy on cancer-associated fibroblasts and tumor cells in colorectal cancer, and construction of related predictive models using machine learning

BACKGROUND

Preoperative chemotherapy (PC) is an important component of Colorectal cancer (CRC) treatment, but its effects on the biological functions of fibroblasts and epithelial cells in CRC are unclear.

METHODS

This study utilized bulk, single-cell, and spatial transcriptomic sequencing data from 22 independent cohorts of CRC. Through bioinformatics analysis and in vitro experiments, the research investigated the impact of PC on fibroblast and epithelial cells in CRC. Subpopulations associated with PC and CRC prognosis were identified, and a predictive model was constructed using machine learning.

RESULTS

PC significantly attenuated the pathways related to tumor progression in fibroblasts and epithelial cells. NOTCH3 + Fibroblast (NOTCH3 + Fib), TNNT1 + Epithelial (TNNT1 + Epi), and HSPA1A + Epithelial (HSPA1A + Epi) subpopulations were identified in the adjacent spatial region and were associated with poor prognosis in CRC. PC effectively diminished the presence of these subpopulations, concurrently inhibiting pathway activity and intercellular crosstalk. A risk signature model, named the Preoperative Chemotherapy Risk Signature Model (PCRSM), was constructed using machine learning. PCRSM emerged as an independent prognostic indicator for CRC, impacting both overall survival (OS) and recurrence-free survival (RFS), surpassing the performance of 89 previously published CRC risk signatures. Additionally, patients with a high PCRSM risk score showed sensitivity to fluorouracil-based adjuvant chemotherapy (FOLFOX) but resistance to single chemotherapy drugs (such as Bevacizumab and Oxaliplatin). Furthermore, this study predicted that patients with high PCRSM were resistant to anti-PD1therapy.

CONCLUSION

In conclusion, this study identified three cell subpopulations (NOTCH3 + Fib, TNNT1 + Epi, and HSPA1A + Epi) associated with PC, which can be targeted to improve the prognosis of CRC patients. The PCRSM model shows promise in enhancing the survival and treatment of CRC patients.

Tumor draining lymph nodes connected to cold triple-negative breast cancers are characterized by Th2-associated microenvironment

Tumor draining lymph nodes (TDLN) represent a key component of the tumor-immunity cycle. There are few studies describing how TDLNs impact lymphocyte infiltration into tumors. Here we directly compare tumor-free TDLNs draining "cold" and "hot" human triple negative breast cancers (TDLNCold and TDLNHot). Using machine-learning-based self-correlation analysis of immune gene expression, we find unbalanced intranodal regulations within TDLNCold. Two gene pairs (TBX21/GATA3-CXCR1) with opposite correlations suggest preferential priming of T helper 2 (Th2) cells by mature dendritic cells (DC) within TDLNCold. This is validated by multiplex immunofluorescent staining, identifying more mature-DC-Th2 spatial clusters within TDLNCold versus TDLNHot. Associated with this Th2 priming preference, more IL4 producing mast cells (MC) are found within sinus regions of TDLNCold. Downstream, Th2-associated fibrotic TME is found in paired cold tumors with increased Th2/T-helper-1-cell (Th1) ratio, upregulated fibrosis growth factors, and stromal enrichment of cancer associated fibroblasts. These findings are further confirmed in a validation cohort and public genomic data. Our results reveal a potential role of IL4+ MCs within TDLNs, associated with Th2 polarization and reduced immune infiltration into tumors.

Tracing troubles: Unveiling the hidden impact of inorganic contamination on juvenile green sea turtle

Human activities and climate change have negatively affected the world's oceans, leading to a decline of 30 to 60 % in coastal ecosystems' biodiversity and habitats. The projected increase in the human population to 9.7 billion by 2050 raises concerns about the sustainability of marine ecosystem conservation and exploitation. Marine turtles, as sentinel species, accumulate contaminants, including trace elements, due to their extensive migration and long-life span. However, there is a lack of data on the degree of contamination and their effects on marine turtles' health. This study focuses on assessing in-situ inorganic contamination in juvenile green sea turtles from La Réunion Island and its short-term impact on individual health, using conventional biomarkers and proteomics. The goals include examining contamination patterns in different tissues and identifying potential new biomarkers for long-term monitoring and conservation efforts. The study identified differential metal contamination between blood and scute samples, which could help illuminate temporal exposure to trace elements in turtle individuals. We also found that some conventional biomarkers were related to trace element exposure, while the proteome responded differently to various contaminant mixtures. Immune processes, cellular organization, and metabolism were impacted, indicating that contaminant mixtures in the wild would have an effect on turtle's health. Fifteen biomarker candidates associated with strong molecular responses of sea turtle to trace element contamination are proposed for future long-term monitoring. The findings emphasize the importance of using proteomic approaches to detect subtle physiological responses to contaminants in the wild and support the need for non-targeted analysis of trace elements in the biomonitoring of sea turtle health.

Dynamic alterations and ecological implications of rice rhizosphere bacterial communities induced by an insect-transmitted reovirus across space and time

BACKGROUND

Cereal diseases caused by insect-transmitted viruses are challenging to forecast and control because of their intermittent outbreak patterns, which are usually attributed to increased population densities of vector insects due to cereal crop rotations and indiscriminate use of pesticides, and lack of resistance in commercial varieties. Root microbiomes are known to significantly affect plant health, but there are significant knowledge gaps concerning epidemics of cereal virus diseases at the microbiome-wide scale under a variety of environmental and biological factors.

RESULTS

Here, we characterize the diversity and composition of rice (Oryza sativa) root-associated bacterial communities after infection by an insect-transmitted reovirus, rice black-streaked dwarf virus (RBSDV, genus Fijivirus, family Spinareoviridae), by sequencing the bacterial 16S rRNA gene amplified fragments from 1240 samples collected at a consecutive 3-year field experiment. The disease incidences gradually decreased from 2017 to 2019 in both Langfang (LF) and Kaifeng (KF). BRSDV infection significantly impacted the bacterial community in the rice rhizosphere, but this effect was highly susceptible to both the rice-intrinsic and external conditions. A greater correlation between the bacterial community in the rice rhizosphere and those in the root endosphere was found after virus infection, implying a potential relationship between the rice-intrinsic conditions and the rhizosphere bacterial community. The discrepant metabolites in rhizosphere soil were strongly and significantly correlated with the variation of rhizosphere bacterial communities. Glycerophosphates, amino acids, steroid esters, and triterpenoids were the metabolites most closely associated with the bacterial communities, and they mainly linked to the taxa of Proteobacteria, especially Rhodocyclaceae, Burkholderiaceae, and Xanthomonadales. In addition, the greenhouse pot experiments demonstrated that bulk soil microbiota significantly influenced the rhizosphere and endosphere communities and also regulated the RBSDV-mediated variation of rhizosphere bacterial communities.

CONCLUSIONS

Overall, this study reveals unprecedented spatiotemporal dynamics in rhizosphere bacterial communities triggered by RBSDV infection with potential implications for disease intermittent outbreaks. The finding has promising implications for future studies exploring virus-mediated plant-microbiome interactions. Video Abstract.

Immunotherapy may be more appropriate for ERBB2 low-expressing extramammary paget's disease patients: a prognosis analysis and exploration of targeted therapy and immunotherapy of extramammary paget's disease patients

Extramammary Paget's disease (EMPD) is a rare cutaneous malignancy characterized by its uncertain etiology and metastatic potential. Surgery remains the first-line clinical treatment for EMPD, but the efficacy of radiotherapy and chemotherapy remains to be fully evaluated, and new therapies for EMPD are urgently needed. In this study, we initially screened 815 EMPD patients in the Surveillance, Epidemiology, and End Results (SEER) database and analyzed their clinical features and prognostic factors. Using the dataset from the Genome Sequence Archive (GSA) database, we subsequently conducted weighted gene coexpression network analysis (WGCNA), gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analyses, grouping the samples based on EMPD disease status and the levels of ERBB2 expression. The prognostic analysis based on the SEER database identified increased age at diagnosis, distant metastasis, and receipt of radiotherapy as independent risk factors for EMPD. Moreover, our results indicated that patients who received chemotherapy had worse prognoses than those who did not, highlighting the urgent need for novel treatment approaches for EMPD. Functional analysis of the GSA-derived dataset revealed that EMPD tissues were significantly enriched in immune-related pathways compared with normal skin tissues. Compared with those with high ERBB2 expression, tissues with low ERBB2 expression displayed greater immunogenicity and enrichment of immune pathways, particularly those related to B cells. These findings suggest that patients with low ERBB2 expression are likely to benefit from immunotherapy, especially B-cell-related immunotherapy.

Integration of Mitoflash and Time-Series Transcriptomics Facilitates Energy Dynamics Tracking and Substrate Supply Analysis of Floral Thermogenesis in Lotus

The high biosynthetic and energetic demands of floral thermogenesis render thermogenic plants the ideal systems to characterize energy metabolism in plants, but real-time tracking of energy metabolism in plant cells remains challenging. In this study, a new method was developed for tracking the mitochondrial energy metabolism at the single mitochondria level by real-time imaging of mitochondrial superoxide production (i.e., mitoflash). Using this method, we observed the increased mitoflash frequencies in the receptacles of Nelumbo nucifera Gaertn. at the thermogenic stages. This increase, combined with the higher expression of antioxidant response-related genes identified through time-series transcriptomics at the same stages, shows us a new regulatory mechanism for plant redox balance. Furthermore, we found that the upregulation of respiratory metabolism-related genes during the thermogenic stages not only correlates with changes in mitoflash frequency but also underscores the critical roles of these pathways in ensuring adequate substrate supply for thermogenesis. Metabolite analysis revealed that sugars are likely one of the substrates for thermogenesis and may be transported over long distances by sugar transporters. Taken together, our findings demonstrate that mitoflash is a reliable tool for tracking energy metabolism in thermogenic plants and contributes to our understanding of the regulatory mechanisms underlying floral thermogenesis.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Evolution of gene networks underlying adaptation to drought stress in the wild tomato Solanum chilense

Drought stress is a key limitation for plant growth and colonization of arid habitats. We study the evolution of gene expression response to drought stress in a wild tomato, Solanum chilense, naturally occurring in dry habitats in South America. We conduct a transcriptome analysis under standard and drought experimental conditions to identify drought-responsive gene networks and estimate the age of the involved genes. We identify two main regulatory networks corresponding to two typical drought-responsive strategies: cell cycle and fundamental metabolic processes. The metabolic network exhibits a more recent evolutionary origin and a more variable transcriptome response than the cell cycle network (with ancestral origin and higher conservation of the transcriptional response). We also integrate population genomics analyses to reveal positive selection signals acting at the genes of both networks, revealing that genes exhibiting selective sweeps of older age also exhibit greater connectivity in the networks. These findings suggest that adaptive changes first occur at core genes of drought response networks, driving significant network re-wiring, which likely underpins species divergence and further spread into drier habitats. Combining transcriptomics and population genomics approaches, we decipher the timing of gene network evolution for drought stress response in arid habitats.

GAN-WGCNA: Calculating gene modules to identify key intermediate regulators in cocaine addiction

Understanding time-series interplay of genes is essential for diagnosis and treatment of disease. Spatio-temporally enriched NGS data contain important underlying regulatory mechanisms of biological processes. Generative adversarial networks (GANs) have been used to augment biological data to describe hidden intermediate time-series gene expression profiles during specific biological processes. Developing a pipeline that uses augmented time-series gene expression profiles is needed to provide an unbiased systemic-level map of biological processes and test for the statistical significance of the generated dataset, leading to the discovery of hidden intermediate regulators. Two analytical methods, GAN-WGCNA (weighted gene co-expression network analysis) and rDEG (rescued differentially expressed gene), interpreted spatiotemporal information and screened intermediate genes during cocaine addiction. GAN-WGCNA enables correlation calculations between phenotype and gene expression profiles and visualizes time-series gene module interplay. We analyzed a transcriptome dataset of two weeks of cocaine self-administration in C57BL/6J mice. Utilizing GAN-WGCNA, two genes (Alcam and Celf4) were selected as missed intermediate significant genes that showed high correlation with addiction behavior. Their correlation with addictive behavior was observed to be notably significant in aspect of statistics, and their expression and co-regulation were comprehensively mapped in terms of time, brain region, and biological process.

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

Unveiling the impact of nitrogen deficiency on alkaloid synthesis in konjac corms (Amorphophallus muelleri Blume)

BACKGROUND

Konjac corms are known for their alkaloid content, which possesses pharmacological properties. In the primary cultivation areas of konjac, nitrogen deficiency is a common problem that significantly influences alkaloid synthesis. The impact of nitrogen deficiency on the alkaloids in konjac corms remains unclear, further complicated by the transition from mother to daughter corms during their growth cycle.

RESULTS

This study examined 21 alkaloids, including eight indole alkaloids, five isoquinoline alkaloids, and eight other types of alkaloids, along with the associated gene expressions throughout the development of Amorphophallus muelleri Blume under varying nitrogen levels. Nitrogen deficiency significantly reduced corm diameter and fresh weight and delayed the transformation process. Under low nitrogen conditions, the content of indole alkaloids and the expression of genes involved in their biosynthesis, such as tryptophan synthase (TRP) and tryptophan decarboxylase (TDC), exhibited a substantial increase in daughter corms, with fold changes of 61.99 and 19.31, respectively. Conversely, in the mother corm, TDC expression was markedly reduced, showing only 0.04 times the expression level observed under 10 N treatment. The patterns of isoquinoline alkaloid accumulation in corms subjected to nitrogen deficiency were notably distinct from those observed for indole alkaloids. The accumulation of isoquinoline alkaloids was significantly higher in mother corms, with expression levels of aspartate aminotransferase (GOT), chorismate mutase (CM), tyrosine aminotransferase (TAT), and pyruvate decarboxylase (PD) being 4.30, 2.89, 921.18, and 191.40 times greater, respectively. Conversely, in daughter corms, the expression levels of GOT and CM in the 0 N treatment were markedly lower (0.01 and 0.83, respectively) compared to the 10 N treatment.

CONCLUSIONS

The study suggests that under nitrogen deficiency, daughter corms preferentially convert chorismate into tryptophan to synthesize indole alkaloids, while mother corms convert it into tyrosine, boosting the production of isoquinoline alkaloids. This research provides valuable insights into the mechanisms of alkaloid biosynthesis in A. muelleri and can aid in developing nitrogen fertilization strategies and in the extraction and utilization of alkaloids.

Comprehensive analysis of aging-related gene expression patterns and identification of potential intervention targets

PURPOSE

This study aims to understand the molecular mechanisms underlying the aging process and identify potential interventions to mitigate age-related decline and diseases.

METHODS

This study utilized the GSE168753 dataset to conduct comprehensive differential gene expression analysis and co-expression module analysis. Machine learning and Mendelian randomization analyses were employed to identify core aging-associated genes and potential drug targets. Molecular docking simulations and mediation analysis were also performed to explore potential compounds and mediators involved in the aging process.

RESULTS

The analysis identified 4164 differentially expressed genes, with 1893 upregulated and 2271 downregulated genes. Co-expression analysis revealed 21 modules, including both positively and negatively correlated modules between older age and younger age groups. Further exploration identified 509 aging-related genes with distinct biological functions. Machine learning and Mendelian randomization analyses identified eight core genes associated with aging, including DPP9, GNAZ, and RELL2. Molecular docking simulations suggested resveratrol, folic acid, and ethinyl estradiol as potential compounds capable of attenuating aging through modulation of RELL2 expression. Mediation analysis indicated that eosinophil counts and neutrophil count might act as mediators in the causal relationship between genes and aging-related indicators.

CONCLUSION

This comprehensive study provides valuable insights into the molecular mechanisms of aging and offers important implications for the development of anti-aging therapeutics. Key Messages What is already known on this topic - Prior research outlines aging's complexity, necessitating precise molecular targets for intervention. What this study adds - This study identifies novel aging-related genes, potential drug targets, and therapeutic compounds, advancing our understanding of aging mechanisms. How this study might affect research, practice, or policy - Findings may inform targeted therapies for age-related conditions, influencing future research and clinical practices.

Differences in transcriptomic responses upon Phytophthora palmivora infection among cultivars reveal potential underlying resistant mechanisms in durian

BACKGROUND

Phytophthora palmivora is a devastating oomycete pathogen in durian, one of the most economically important crops in Southeast Asia. The use of fungicides in Phytophthora management may not be a long-term solution because of emerging chemical resistance issues. It is crucial to develop Phytophthora-resistant durian cultivars, and information regarding the underlying resistance mechanisms is valuable for smart breeding programs.

RESULTS

In this study, we conducted RNA sequencing (RNA-seq) to investigate early gene expression responses (at 8, 24, and 48 h) after the P. palmivora infection in three durian cultivars, which included one resistant cultivar (Puangmanee; PM) and two susceptible cultivars (Monthong; MT and Kradumthong; KD). We performed co-expression and differential gene expression analyses to capture gene expression patterns and identify the differentially expressed genes. The results showed that genes encoding heat shock proteins (HSPs) were upregulated in all infected durians. The expression levels of genes encoding HSPs, such as ERdj3B, were high only in infected PM. A higher level of P. palmivora resistance in PM appeared to be associated with higher expression levels of various genes encoding defense and chitin response proteins, such as lysM domain receptor-like kinases. MT had a lower resistance level than PM, although it possessed more upregulated genes during P. palmivora infection. Many photosynthetic and defense genes were upregulated in the infected MT, although their expression levels were lower than those in the infected PM. KD, the least resistant cultivar, showed downregulation of genes involved in cell wall organization or biogenesis during P. palmivora infection.

CONCLUSIONS

Our results showed that the three durian cultivars exhibited significantly different gene expression patterns in response to P. palmivora infection. The upregulation of genes encoding HSPs was common in all studied durians. The high expression of genes encoding chitin response proteins likely contributed to P. palmivora resistance in durians. Durian susceptibility was associated with low basal expression of defense genes and downregulation of several cell wall-related genes. These findings enhance our understanding of durian resistance to Phytophthora infection and could be useful for the development of elite durian cultivars.

Transcription factor PATZ1 promotes adipogenesis by controlling promoter regulatory loci of adipogenic factors

White adipose tissue (WAT) is essential for lipid storage and systemic energy homeostasis. Understanding adipocyte formation and stability is key to developing therapies for obesity and metabolic disorders. Through a high-throughput cDNA screen, we identified PATZ1, a POZ/BTB and AT-Hook Containing Zinc Finger 1 protein, as an important adipogenic transcription factor. PATZ1 is expressed in human and mouse adipocyte precursor cells (APCs) and adipocytes. In cellular models, PATZ1 promotes adipogenesis via protein-protein interactions and DNA binding. PATZ1 ablation in mouse adipocytes and APCs leads to a reduced APC pool, decreased fat mass, and hypertrophied adipocytes. ChIP-Seq and RNA-seq analyses show that PATZ1 supports adipogenesis by interacting with transcriptional machinery at the promoter regions of key early adipogenic factors. Mass-spec results show that PATZ1 associates with GTF2I, with GTF2I modulating PATZ1's function during differentiation. These findings underscore PATZ1's regulatory role in adipocyte differentiation and adiposity, offering insights into adipose tissue development.

Mechanisms of Berberine in anti-pancreatic ductal adenocarcinoma revealed by integrated multi-omics profiling

This study integrates pharmacology databases with bulk RNA-seq and scRNA-seq to reveal the latent anti-PDAC capacities of BBR. Target genes of BBR were sifted through TargetNet, CTD, SwissTargetPrediction, and Binding Database. Based on the GSE183795 dataset, DEG analysis, GSEA, and WGCNA were sequentially run to build a disease network. Through sub-network filtration acquired PDAC-related hub genes. A PPI network was established using the shared genes. Degree algorithm from cytoHubba screened the key cluster in the network. Analysis of differential mRNA expression and ROC curves gauged the diagnostic performance of clustered genes. CYBERSORT uncovered the potential role of the key cluster on PDAC immunomodulation. ScRNA-seq analysis evaluated the distribution and expression profile of the key cluster at the single-cell level, assessing enrichment within annotated cell subpopulations to delineate the target distribution of BBR in PDAC. We identified 425 drug target genes and 771 disease target genes, using 57 intersecting genes to construct the PPI network. CytoHubba anchored the top 10 highest contributing genes to be the key cluster. mRNA expression levels and ROC curves confirmed that these genes showed good robustness for PDAC. CYBERSORT revealed that the key cluster influenced immune pathways predominantly associated with Macrophages M0, CD8 T cells, and naïve B cells. ScRNA-seq analysis clarified that BBR mainly acted on epithelial cells and macrophages in PDAC tissues. BBR potentially targets CDK1, CCNB1, CTNNB1, CDK2, TOP2A, MCM2, RUNX2, MYC, PLK1, and AURKA to exert therapeutic effects on PDAC. The mechanisms of action appear to significantly involve macrophage polarization-related immunological responses.

Effect of time series on the degradation of lignin by Trametes gibbosa: Products and pathways

Lignin is the third most abundant organic resource in nature. The utilization of white-rot fungi for wood degradation effectively circumvents environmental pollution associated with chemical treatments, facilitating the benign decomposition of lignin. Trametes gibbosa is a typical white-rot fungus with rapid growth and strong wood decomposition ability. The lignin content decreased from 23.62 mg/mL to 17.05 mg/mL, which decreased by 27 % in 30 days. The activity of manganese peroxidase increased steadily by 9.44 times. The activities of laccase and lignin peroxidase had the same trend of change and reached peaks of 49.88 U/L and 10.43 U/L on the 25th day, respectively. The change in H2O2 content in vivo was opposite to its trend. For FTIR and GC-MS analysis, the fungi attacked the side chain structure of lignin phenyl propane polymer and benzene ring to crack into low molecular weight aromatic compounds. The side chains of low molecular weight aromatic compounds are oxidized, and long-chain carboxylic acids are formed. Additionally, the absorption peak in the vibration region of the benzene ring skeleton became complex, and the structure of the benzene rings changed. In the beginning, fungal growth was inhibited. Fungal autophagy was aggravated. The metal cation binding proteins of fungi were active, and the genes related to detoxification metabolism were upregulated. The newly produced compounds are related to xenobiotic metabolism. The degradation peak focused on the redox process, and the biological function was enriched in the regulation of macromolecular metabolism, lignin metabolism, and oxidoreductase activity acting on diphenols and related substances as donors. Notably, genes encoding key degradation enzymes, including lcc3, lcc4, phenol-2-monooxygenase, 3-hydroxybenzoate-6-hydroxylase, oxalate decarboxylase, and acetyl-CoA oxidase were significantly upregulated. On the 30th day, the N-glycan biosynthesis pathway was significantly enriched in glycan biosynthesis and metabolism. Weighted correlation network analysis was performed. A total of 1452 genes were clustered in the coral1 module, which were most related to lignin degradation. The genes were significantly enriched in oxidoreductase activity, peptidase activity, cell response to stimulation, signal transduction, lignin metabolism, and phenylpropane metabolism, while the rest were concentrated in glucose metabolism. In this study, the lignin degradation process and products were revealed by T. gibbosa. The molecular mechanism of lignin degradation in different stages was explored. The selection of an efficient utilization time of lignin will help to increase the degradation rate of lignin. This study provides a theoretical basis for the biofuel and biochemical production of lignin. SYNOPSIS: Trametes gibbosa degrades lignin in a pollution-free way, improving the utilization of carbon resources in an environmentally friendly spontaneous cycle. The products are the new way towards sustainable development and low-carbon technology.

Regular exercise suppresses steatosis-associated liver cancer development by degrading E2F1 and c-Myc via circadian gene upregulation

Regular exercise is believed to suppress cancer progression. However, the precise molecular mechanisms by which exercise prevents cancer development remain unclear. In this study, using a steatosis-associated liver cancer mouse model, we found that regular exercise at a speed of 18 m/min for 20 min daily suppressed liver cancer development. To explore the underlying mechanisms, we examined the gene expression profiles in the livers of the exercise and non-exercise groups. The expressions of circadian genes, such as Per1 and Cry2, were upregulated in the exercise group. As circadian rhythm disruption is known to cause various diseases, including cancer, improving circadian rhythm through exercise could contribute to cancer prevention. We further found that the expression of a series of E2F1 and c-Myc target genes that directly affect the proliferation of cancer cells was downregulated in the exercise group. However, the expression of E2F1 and c-Myc was transcriptionally unchanged but degraded at the post-translational level by exercise. Cry2, which is regulated by the Skp1-Cul1-FBXL3 (SCFFBXL3) ubiquitin ligase complex by binding to FBXL3, can form a complex with E2F1 and c-Myc, which we think is the mechanism to degrade them. Our study revealed a previously unknown mechanism by which exercise prevents cancer development.

Dissecting the lung transcriptome of pulmonary fibrosis-associated pulmonary hypertension

Integrative multiomics can help elucidate the pathophysiology of pulmonary fibrosis (PF)-associated pulmonary hypertension (PH) (PF-PH). Weighted gene coexpression network analysis (WGCNA) was performed on a transcriptomic dataset of explanted lung tissue from 116 patients with PF. Patients were stratified by pulmonary vascular resistance (PVR), and differential gene expression analysis was conducted. Gene modules were correlated with hemodynamics at the time of transplantation and tested for enrichment in the lung transcriptomics signature of an independent pulmonary arterial hypertension (PAH) cohort. We found 1,250 differentially expressed genes between high and low PVR groups. WGCNA identified that black and yellowgreen modules negatively correlated with PVR, whereas the tan and darkgrey modules are positively correlated with PVR in PF-PH. In addition, the tan module showed the strongest enrichment for an independent PAH gene signature, suggesting shared gene expression patterns between PAH and PF-PH. Pharmacotranscriptomic analysis using the Connectivity Map implicated the tan and darkgrey modules as potentially pathogenic in PF-PH, given their combined module signature demonstrated a high negative connectivity score for treprostinil, a medication used in the treatment of PF-PH, and a high positive connectivity score for bone morphogenetic protein (BMP) loss of function. Pathway enrichment analysis revealed that inflammatory pathways and oxidative phosphorylation were downregulated, whereas epithelial-mesenchymal transition was upregulated in modules associated with increased PVR. Our integrative systems biology approach to the lung transcriptome of PF with and without PH identified several PH-associated coexpression modules and gene targets with shared molecular features with PAH warranting further investigation to uncover potential new therapies for PF-PH.NEW & NOTEWORTHY An integrative systems biology approach that included transcriptomic analysis of explanted lung tissue from patients with pulmonary fibrosis (PF) with and without pulmonary hypertension (PH) undergoing lung transplantation, combined with hemodynamic correlation and pharmacotranscriptomics, identified modules of genes associated with pulmonary vascular disease severity. Comparison with an independent pulmonary arterial hypertension (PAH) dataset identified shared gene expression patterns between PAH and PF-PH.

Effect of myristic acid supplementation on triglyceride synthesis and related genes in the pectoral muscles of broiler chickens

Fatty acids (FAs) can serve as energy for poultry, maintain normal cell structure and function, and support a healthy immune system. Although the addition of polyunsaturated fatty acids (PUFAs) to the diet has been extensively studied and reported, the mechanism of action of saturated fatty acids (SFAs) remains to be elucidated. We investigated the effect of 0.04% dietary myristic acid (MA) on slaughter performance, lipid components, tissue FAs, and the transcriptome profile in chickens. The results showed that dietary MA had no effect on slaughter performance (body weight, carcass weight, eviscerated weight, and pectoral muscle weight) (P > 0.05). Dietary MA enrichment increased MA (P < 0.001) and triglycerides (TGs) (P < 0.01) levels in the pectoral muscle. The levels of palmitic acid, linoleic acid (LA), arachidonic acid (AA), SFAs, monounsaturated fatty acids (MUFAs), and PUFAs were significantly higher (P < 0.01) in the MA supplementation group compared to the control group. However, there were no significant differences in the ratios of PUFA/SFA and n6/omega-3 (n3) between the two groups. The MA content was positively correlated with the contents of palmitic acid, LA, linolenic acid (ALA), n3, n6, SFAs, and unsaturated fatty acids (UFA). DHCR24, which is known to be involved in steroid metabolism and cholesterol biosynthesis pathways, was found to be a significantly lower in the MA supplementation group compared to the control group (P < 0.05, log2(fold change) = -0.85). Five overlapping co-expressed genes were identified at the intersection between the differential expressed genes and Weighted Gene Co‑expression Network Analysis-derived hub genes associated with MA phenotype, namely BHLHE40, MSL1, PLAGL1, SRSF4, and ENSGALG00000026875. For the TG phenotype, a total of 28 genes were identified, including CHKA, KLF5, TGIF1, etc. Both sets included the gene PLAGL1, which has a negative correlation with the levels of MA and TG. This study provides valuable information to further understand the regulation of gene expression patterns by dietary supplementation with MA and examines at the molecular level the phenotypic changes induced by supplementation with MA.

Gene coexpression network analysis reveals the genes and pathways in pectoralis major muscle and liver associated with wooden breast in broilers

Wooden breast (WB) is a myopathy mainly affecting pectoralis major (PM) muscle in modern commercial broiler chickens, causing enormous economic losses in the poultry industry. Recent studies have observed hepatic and PM muscle injury in broilers affected by WB, but the relationships between WB and the 2 tissues are mostly unclear. In the current study, the RNA-seq raw data of PM muscle and liver were downloaded from GSE144000, and we constructed the gene coexpression networks of PM muscle and liver to explore the relationships between WB and the 2 tissues using the weighted gene coexpression network analysis (WGCNA) method. Six and 2 gene coexpression modules were significantly correlated with WB in the PM muscle and liver networks, respectively. TGF-beta signaling, Toll-like receptor signaling and mTOR signaling pathways were significantly enriched in the genes within the 6 gene modules of PM muscle network. Meanwhile, mTOR signaling pathway was significantly enriched in the genes within the 2 gene modules of liver network. In the consensus gene coexpression network across the 2 tissues, salmon module (r = -0.5 and p = 0.05) was significantly negatively correlated with WB, in which Toll-like receptor signaling, apoptosis, and autophagy pathways were significantly enriched. The genes related with the 3 pathways, myeloid differentiation primary response 88 (MYD88), interferon regulatory factor 7 (IRF7), mitogen-activated protein kinase 14 (MAPK14), FBJ murine osteosarcoma viral oncogene homolog (FOS), jun proto-oncogene (JUN), caspase-10, unc-51 like autophagy activating kinase 2 (ULK2) and serine/threonine kinase 11 (LKB1), were identified in salmon module. In this current study, we found that the signaling pathways related with cell inflammation, apoptosis and autophagy might influence WB across 2 tissues in broilers.

Integrated analysis of patients with bladder cancer from prospective transcription factor activity: Implications for personalized treatment approaches

Transcription factors are a specialized group of proteins that play important roles in regulating gene expression in human. These proteins control the transcription and translation of genes by binding to specific sites on DNA, thereby regulating key biological processes such as cell differentiation, proliferation, immune response, and neural development. Moreover, transcription factors are also involved in apoptosis and the pathogenesis of various diseases. By investigating transcription factors, researchers can uncover the mechanisms of gene regulation in organisms and develop more effective methods for preventing and treating human diseases. In the present study, the Virtual Inference of Protein-activity by Enriched Regulon algorithm was utilized to calculate the protein activity of transcription factors, and the metabolic-related protein activity were used for classifying bladder cancer patients into different subtype. To identify chemotherapy drugs with clinical benefits, the differences in prognosis and drug sensitivity between two distinct subtypes of bladder cancer patients were investigated. Simultaneously, the master regulators that display varying levels of transcription factor activity between two different bladder cancer subtypes were explored. Additionally, the potential transcriptional regulatory mechanisms and targets of these factors were investigated, thereby generating novel insights into bladder cancer research at the transcriptional regulation level.

Integrated multi-omics analysis reveals molecular changes associated with chronic lipid accumulation following contusive spinal cord injury

Functional and pathological recovery after spinal cord injury (SCI) is often incomplete due to the limited regenerative capacity of the central nervous system (CNS), which is further impaired by several mechanisms that sustain tissue damage. Among these, the chronic activation of immune cells can cause a persistent state of local CNS inflammation and damage. However, the mechanisms that sustain this persistent maladaptive immune response in SCI have not been fully clarified yet. In this study, we integrated histological analyses with proteomic, lipidomic, transcriptomic, and epitranscriptomic approaches to study the pathological and molecular alterations that develop in a mouse model of cervical spinal cord hemicontusion. We found significant pathological alterations of the lesion rim with myelin damage and axonal loss that persisted throughout the late chronic phase of SCI. This was coupled by a progressive lipid accumulation in myeloid cells, including resident microglia and infiltrating monocyte-derived macrophages. At tissue level, we found significant changes of proteins indicative of glycolytic, tricarboxylic acid cycle (TCA), and fatty acid metabolic pathways with an accumulation of triacylglycerides with C16:0 fatty acyl chains in chronic SCI. Following transcriptomic, proteomic, and epitranscriptomic studies identified an increase of cholesterol and m6A methylation in lipid-droplet-accumulating myeloid cells as a core feature of chronic SCI. By characterizing the multiple metabolic pathways altered in SCI, our work highlights a key role of lipid metabolism in the chronic response of the immune and central nervous system to damage.

Identification of transcription factor BnHDG4-A08 as a novel candidate associated with the accumulation of oleic, linoleic, linolenic, and erucic acid in Brassica napus

KEY MESSAGE

We screened 47 significantly associated haplotype blocks for oleic, linoleic, linolenic, and erucic acid, with 17 blocks influencing multiple traits. A novel candidate of transcription factor BnHDG4 A08 influencing oleic, linoleic, linolenic, and erucic acid was identified, by a joint strategy of haplotype-based genome-wide association study, genomic resequencing, gene cloning, and co-expression network Fatty acid (FA) composition determines the quality and economic value of rapeseed oil (Brassica napus). However, the molecular network of FAs is unclear. In the current study, multi-strategies of haplotype-based genome-wide association study (GWAS), genomic resequencing, gene cloning, and co-expression network were joint to reveal novel genetic factors influencing FA accumulation in rapeseed. We identified 47 significantly associated haplotype blocks for oleic, linoleic, linolenic, and erucic acid, with 17 blocks influencing multiple traits, using a haplotype-based GWAS with phenotype data from 203 Chinese semi-winter accessions. A total of 61 rapeseed orthologs involved in acyl-lipid metabolism, carbohydrate metabolism, or photosynthesis were identified in these 17 blocks. Among these genes, BnHDG4-A08, encoding a class IV homeodomain leucine-zipper transcription factor, exhibited two single-nucleotide polymorphisms (SNPs) in the exon and intron, with significant associations with oleic, linoleic, linolenic, and erucic acid. Gene cloning further validated two SNPs in the exon of BnHDG4-A08 in a population with 75 accessions, leading to two amino acid changes (T372A and P366L) and significant variation of oleic, linoleic, linolenic, and erucic acid. A competitive allele-specific PCR (KASP) marker based on the SNPs was successfully developed and validated. Moreover, 98 genes exhibiting direct interconnections and high weight values with BnHDG4-A08 were identified through co-expression network analysis using transcriptome data from 13 accessions. Our study identified a novel FA candidate of transcription factor BnHDG4-A08 influencing oleic, linoleic, linolenic, and erucic acid. This gene provides a potential promising gene resource for the novel mechanistic understanding of transcription factors regulating FA accumulation.

Trade-off between photosymbiosis and innate immunity influences cnidarian's response to pathogenic bacteria

Mutualistic relationships with photosynthetic organisms are common in cnidarians, which form an intracellular symbiosis with dinoflagellates in the family Symbiodiniaceae. The establishment and maintenance of these symbionts are associated with the suppression of key host immune factors. Because of this, there are potential trade-offs between the nutrition that cnidarian hosts gain from their symbionts and their ability to successfully defend themselves from pathogens. To investigate these potential trade-offs, we utilized the facultatively symbiotic polyps of the upside-down jellyfish Cassiopea xamachana and exposed aposymbiotic and symbiotic polyps to the pathogen Serratia marcescens. Symbiotic polyps had a lower probability of survival following S. marcescens exposure. Gene expression analyses 24 hours following pathogen exposure indicate that symbiotic animals mounted a more damaging immune response, with higher levels of inflammation and oxidative stress likely resulting in more severe disruptions to cellular homeostasis. Underlying this more damaging immune response may be differences in constitutive and pathogen-induced expression of immune transcription factors between aposymbiotic and symbiotic polyps rather than broadscale immune suppression during symbiosis. Our findings indicate that in facultatively symbiotic polyps, hosting symbionts limits C. xamachana's ability to survive pathogen exposure, indicating a trade-off between symbiosis and immunity that has potential implications for coral disease research.

An acidophilic fungus promotes prey digestion in a carnivorous plant

Leaves of the carnivorous sundew plants (Drosera spp.) secrete mucilage that hosts microorganisms, but whether this microbiota contributes to prey digestion is unclear. We identified the acidophilic fungus Acrodontium crateriforme as the dominant species in the mucilage microbial communities, thriving in multiple sundew species across the global range. The fungus grows and sporulates on sundew glands as its preferred acidic environment, and its presence in traps increased the prey digestion process. A. crateriforme has a reduced genome similar to other symbiotic fungi. During A. crateriforme-Drosera spatulata coexistence and digestion of prey insects, transcriptomes revealed significant gene co-option in both partners. Holobiont expression patterns during prey digestion further revealed synergistic effects in several gene families including fungal aspartic and sedolisin peptidases, facilitating prey digestion in leaves, as well as nutrient assimilation and jasmonate signalling pathway expression. This study establishes that botanical carnivory is defined by adaptations involving microbial partners and interspecies interactions.

Molecular forecasting of domoic acid during a pervasive toxic diatom bloom

In 2015, the largest recorded harmful algal bloom (HAB) occurred in the Northeast Pacific, causing nearly 100 million dollars in damages to fisheries and killing many protected marine mammals. Dominated by the toxic diatom Pseudo-nitzschia australis, this bloom produced high levels of the neurotoxin domoic acid (DA). Through molecular and transcriptional characterization of 52 near-weekly phytoplankton net-tow samples collected at a bloom hotspot in Monterey Bay, California, we identified active transcription of known DA biosynthesis (dab) genes from the three identified toxigenic species, including P. australis as the primary origin of toxicity. Elevated expression of silicon transporters (sit1) during the bloom supports the previously hypothesized role of dissolved silica (Si) exhaustion in contributing to bloom physiology and toxicity. We find that coexpression of the dabA and sit1 genes serves as a robust predictor of DA one week in advance, potentially enabling the forecasting of DA-producing HABs. We additionally present evidence that low levels of iron could have colimited the diatom population along with low Si. Iron limitation represents an overlooked driver of both toxin production and ecological success of the low-iron-adapted Pseudo-nitzschia genus during the 2015 bloom, and increasing pervasiveness of iron limitation may fuel the escalating magnitude and frequency of toxic Pseudo-nitzschia blooms globally. Our results advance understanding of bloom physiology underlying toxin production, bloom prediction, and the impact of global change on toxic blooms.

Establishment and characterization of a gill cell line from Takifugu obscurus and transcriptome analysis of its gene expression profiles upon low temperature

Takifugu obscurus is a farmed fish of great economic importance in China. The rapid development of T. obscurus aquaculture industry has been accompanied by disease and low-temperature stress, resulting in huge economic losses. Cell lines are used extensively in teleost physiology and pathology as the most cost-effective platform for in vitro research. A novel gill cell line of T. obscurus (named TOG) was first successfully established, and passed through 52 generations. The optimal conditions for TOG growth were 20 % FBS concentration and 24 °C, TOG could be grown in both hypotonic (150 mOsmol-kg-1) and hypertonic (600 mOsmol-kg-1) environments. TOG was determined to be derived from T. obscurus by sequencing the mitochondrial COI gene. Karyotype analysis revealed that the chromosome number of TOG was 44 (2n = 44). Transfection experiment showed that TOG was able to express foreign genes. Furthermore, several immune-related genes were significantly up-regulated in TOG after LPS and poly (I:C) stimulation, including tlr3, isg15, il1β and il10. Additionally, transcriptome analysis of TOG under low-temperature stress (24 °C, 18 °C, 12 °C, 10 °C and 8 °C) found that differentially expressed genes (DEGs) were significantly clustered in several immunological and energy metabolic pathways, and cold stress could disrupt the immune barrier and reduce immunity by downregulating the immune-related pathways. Additionally, weighted gene co-expression network analysis (WGCNA) revealed that bule module and turquoise module, which were closely correlated with low temperature and the degree of fish damage, were both predominantly found in PPAR, NOD-like receptor and Toll-like receptor signaling pathway. Hub genes were identified in these two modules, including mre11, clpb, dhx15, ddx18 and utp15. TOG cell line will become an effective experimental platform for genetic and immunological research, and our results would help us gain a deeper insight into the molecular mechanism of cold tolerance in teleost.

Genome-wide identification and expression analysis of phytochrome-interacting factor genes during abiotic stress responses and secondary metabolism in the tea plant

Phytochrome-interacting factors (PIFs) are pivotal transcriptional regulators controlling photomorphogenesis, environmental responses, and development in plants. However, their specific roles in coordinating adaptation towards abiotic stress and metabolism remain underexplored in tea plants. Here, we identified seven PIF members from four distinct clades (PIF1, PIF3, PIF7, and PIF8). Promoter analysis implicated CsPIFs in integrating light, stress, hormone, and circadian signals. Most CsPIFs exhibited rapid increase in expression under shading, especially CsPIF7b/8a, which displayed significant changes in long-term shading condition. Under drought/salt stress, CsPIF3b emerged as a potential positive regulator. CsPIF3a was induced by low temperature and co-expressed with CsCBF1/3 and CsDREB2A cold response factors. Dual-luciferase assays confirmed that act as negative regulator of the CBF pathway. Expression profiling across 11 tea cultivars associated specific CsPIFs with chlorophyll biosynthesis and accumulation of anthocyanins, flavonols, and other metabolites. In summary, this study highlights the significance of CsPIFs as central coordinators in managing intricate transcriptional reactions to simultaneous abiotic stresses and metabolic adjustments in tea plants. This insight informs future strategies for enhancing this economically crucial crop through crop improvement initiatives.

Insights into ACO genes across Rosaceae: evolution, expression, and regulatory networks in fruit development

BACKGROUND

ACO (1-aminocyclopropane-1-carboxylic acid) serves as a pivotal enzyme within the plant ethylene synthesis pathway, exerting influence over critical facets of plant biology such as flowering, fruit ripening, and seed development.

OBJECTIVE

This study aims to identify ACO genes from representative Rosaceae genomes, reconstruct their phylogenetic relationships by integrating synteny information, and investigate their expression patterns and networks during fruit development.

METHODS

we utilize a specialized Hidden Markov Model (HMM), crafted on the sequence attributes of ACO gene-encoded proteins, to systematically identify and analyze ACO gene family members across 12 representative species within the Rosaceae botanical family. Through transcriptome analysis, we delineate the expression patterns of ACO genes in six distinct Rosaceae fruits.

RESULTS

Our investigation reveals the presence of 62 ACO genes distributed among the surveyed Rosaceae species, characterized by hydrophilic proteins predominantly expressed within the cytoplasm. Phylogenetic analysis categorizes these ACO genes into three discernible classes, namely Class I, Class II, and Class III. Further scrutiny via collinearity assessment indicates a lack of collinearity relationships among these classes, highlighting variations in conserved motifs and promoter types within each class. Transcriptome analysis unveils significant disparities in both expression levels and trends of ACO genes in fruits exhibiting respiratory bursts compared to those that do not. Employing Weighted Gene Co-Expression Network Analysis (WGCNA), we discern that the co-expression correlation of ACO genes within loquat fruit notably differs from that observed in apples. Our findings, derived from Gene Ontology (GO) enrichment results, signify the involvement of ACO genes and their co-expressed counterparts in biological processes linked to terpenoid metabolism and carbohydrate synthesis in loquat. Moreover, our exploration of gene regulatory networks (GRN) highlights the potential pivotal role of the GNAT transcription factor (Ejapchr1G00010380) in governing the overexpression of the ACO gene (Ejapchr10G00001110) within loquat fruits.

CONCLUSION

The constructed HMM of ACO proteins offers a precise and systematic method for identifying plant ACO proteins, facilitating phylogenetic reconstruction. ACO genes from representative Rosaceae fruits exhibit diverse expression and regulative patterns, warranting further function characterizations.

Hepatic stearoyl-CoA desaturase-1 deficiency induces fibrosis and hepatocellular carcinoma-related gene activation under a high carbohydrate low fat diet

Stearoyl-CoA desaturase-1 (SCD1) is a pivotal enzyme in lipogenesis, which catalyzes the synthesis of monounsaturated fatty acids (MUFA) from saturated fatty acids, whose ablation downregulates lipid synthesis, preventing steatosis and obesity. Yet deletion of SCD1 promotes hepatic inflammation and endoplasmic reticulum stress, raising the question of whether hepatic SCD1 deficiency promotes further liver damage, including fibrosis. To delineate whether SCD1 deficiency predisposes the liver to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC), we employed in vivo SCD1 deficient global and liver-specific mouse models fed a high carbohydrate low-fat diet and in vitro established AML12 mouse cells. The absence of liver SCD1 remarkably increased the saturation of liver lipid species, as indicated by lipidomic analysis, and led to hepatic fibrosis. Consistently, SCD1 deficiency promoted hepatic gene expression related to fibrosis, cirrhosis, and HCC. Deletion of SCD1 increased the circulating levels of Osteopontin, known to be increased in fibrosis, and alpha-fetoprotein, often used as an early marker and a prognostic marker for patients with HCC. De novo lipogenesis or dietary supplementation of oleate, an SCD1-generated MUFA, restored the gene expression related to fibrosis, cirrhosis, and HCC. Although SCD1 deficient mice are protected against obesity and fatty liver, our results show that MUFA deprivation results in liver injury, including fibrosis, thus providing novel insights between MUFA insufficiency and pathways leading to fibrosis, cirrhosis, and HCC under lean non-steatotic conditions.

The nicotine demethylase CYP82E4 is essential for the formation of red dapples on flue-cured leaves of cherry-red tobacco

Common flue-cured tobacco (Nicotiana tabacum L.) primarily accumulates nicotine, and its flue-cured leaves exhibit a lemon appearance. In contrast, a spontaneous cherry-red variant (CR60) primarily accumulates nornicotine, accompanied by distinctive red dapples on the cured leaves. In this study, suppression of conversion of nicotine to nornicotine by genome editing resulted in decreased nornicotine and N-acyl nornicotines (NacNNs), and the subsequent disappearance of red dapples in CR60. Conversely, overexpression of CYP82E4 increased nornicotine and NacNNs accumulation, inducing a red dapple phenotype in common tobacco. Notably, nicotine conversion triggered significant alterations in leaf total sugars, alkaloids, and nitrogens. Metabolome analyses using 1352 identified compounds indicated nicotine conversion dramatically affected the entire metabolic network and induced unique metabolic responses across diverse genetic backgrounds. Further WGCNA analysis revealed that nicotine conversion caused substantial contents variation of alkaloids, flavonoids and amino acids and derivatives in cured leaves. Overall, this research provides valuable insights into the mechanisms underlying red dapple formation in cherry-red tobacco, elucidating profound influence of nicotine conversion on entire metabolic network.

Prognostic Model and Immune Response of Clear Cell Renal Cell Carcinoma Based on Co-Expression Genes Signature

BACKGROUND

The identification of reliable prognostic markers is crucial for optimizing patient management and improving clinical outcomes in clear cell renal cell carcinoma (ccRCC).

METHODS

We used the GSE89563 dataset from the GEO database and the Kidney Clear Cell Carcinoma (KIRC) dataset from the TCGA database to develop a prognostic model based on weighted gene co-expression network analysis (WGCNA) and non-negative matrix factorization (NMF) to predict disease progression and prognosis in ccRCC.

RESULT

We utilized WGCNA to identify risk genes and applied NMF to stratify high-risk populations in ccRCC. We characterized the immune gene features of these high-risk groups and ultimately developed a risk prediction model for ccRCC patients using a Lasso regression approach. The risk score was calculated as follows: Risk score = SUM (-0.136394797 ANK3 + 0.004238138 BIVM_ERCC5 - 0.046248451 C4orf19 - 0.036013206 F2RL3 - 0.125531316 GNG7 - 0.012698109 METTL7A + 0.078462369 MSTO1 - 0.050450656 PINK1 - 0.059446590 SLC16A12 - 0.039883686 SLC2A9 + 0.083310722 TLCD1 - 0.059801739 WDR72 + 0.071430088 ZNF117).

CONCLUSION

We develop a prognostic model for clear cell renal cell carcinoma and analyzed immune response in subgroups and confirmed protein-level expression concordance.

Bioinformatics Analysis and Identification of Ferroptosis-Related Hub Genes in Intervertebral Disc Degeneration

Approximately 80% of individuals encounter lower back pain (LBP), a prevalent clinical issue largely attributed to intervertebral disc degeneration (IDD). Ferroptosis is an iron-dependent lipid peroxidation-driven cell death, and there is growing evidence that ferroptosis plays an important role in various human diseases. However, the underlying mechanism of ferroptosis in IDD remains unclear. This study aims to reveal the potential hub genes and related pathways of ferroptosis in the pathogenesis and progression of IDD. In this study, we analyzed three microarray datasets from the GEO database. Additionally, we downloaded ferroptosis-related genes from FerrDb-V2 and extracted apoptosis-related genes from UniProt as a control to show the specificity of ferroptosis. Weighted gene co-expression network analysis (WGCNA) was performed to identify the IDD-related module genes. Then, ferroptosis-related genes and apoptosis-related genes were separately overlapped with the IDD-related module genes, resulting in the identification of 35 ferroptosis-related module genes (FRMG) and 142 apoptosis-related module genes (ARMG). Furthermore, we performed functional enrichment analysis and protein-protein interaction network, and Cytoscape along with CytoHubba was used to identify the hub genes. Finally, logistic regression models were constructed and identified two hub FRMGs (PTEN and EGFR) and one hub ARMG (CTNNB1), which could distinguish IDD patients from controls (P < 0.05). The areas under the ROC curves were 0.792 and 0.730, respectively, suggesting that ferroptosis is more specific than apoptosis in IDD. In conclusion, this study provided fresh perspectives on ferroptosis in the pathogenesis and progression of IDD that can be used to evaluate potential biomarker genes and therapeutic targets.

Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models.

The effects of climate and soil depth on living and dead bacterial communities along a longitudinal gradient in Chile

Soil bacterial communities play a critical role in shaping soil stability and formation, exhibiting a dynamic interaction with local climate and soil depth. We employed an innovative DNA separation method to characterize microbial assemblages in low-biomass environments such as deserts and distinguish between intracellular DNA (iDNA) and extracellular DNA (eDNA) in soils. This approach, combined with analyses of physicochemical properties and co-occurrence networks, investigated soil bacterial communities across four sites representing diverse climatic gradients (i.e., arid, semi-arid, Mediterranean, and humid) along the Chilean Coastal Cordillera. The separation method yielded a distinctive unimodal pattern in the iDNA pool alpha diversity, increasing from arid to semi-arid climates and decreasing in humid environments, highlighting the rapid feedback of the iDNA community to increasing soil moisture. In the arid region, harsh surface conditions restrict bacterial growth, leading to peak iDNA abundance and diversity occurring in slightly deeper layers than the other sites. Our findings confirmed the association between specialist bacteria and ecosystem-functional traits. We observed transitions from Halomonas and Delftia, resistant to extreme arid environments, to Class AD3 and the genus Bradyrhizobium, associated with plants and organic matter in humid environments. The distance-based redundancy analysis (dbRDA) analysis revealed that soil pH and moisture were the key parameters that influenced bacterial community variation. The eDNA community correlated slightly better with the environment than the iDNA community. Soil depth was found to influence the iDNA community significantly but not the eDNA community, which might be related to depth-related metabolic activity. Our investigation into iDNA communities uncovered deterministic community assembly and distinct co-occurrence modules correlated with unique bacterial taxa, thereby showing connections with sites and key environmental factors. The study additionally revealed the effects of climatic gradients and soil depth on living and dead bacterial communities, emphasizing the need to distinguish between iDNA and eDNA pools.

lncRNA-gene network analysis reveals the effects of early maternal nutrition on mineral homeostasis and energy metabolism in the fetal liver transcriptome of beef heifers

Maternal nutrition during pregnancy influences fetal development; however, the regulatory markers of fetal programming across different gestational phases remain underexplored in livestock models. Herein, we investigated the regulatory role of long non-coding RNAs (lncRNAs) on fetal liver gene expression, the impacts of maternal vitamin and mineral supplementation, and the rate of maternal body weight gain during the periconceptual period. To this end, crossbred Angus heifers (n=31) were randomly assigned to a 2×2 factorial design to evaluate the main effects of the rate of weight gain (low gain [LG, avg. daily gain of 0.28 kg/day] vs. moderate gain [MG, avg. daily gain of 0.79 kg/day]) and vitamins and minerals supplementation (VTM vs. NoVTM). On day 83±0.27 of gestation, fetuses were collected for morphometric measurements, and fetal liver was collected for transcriptomic and mineral analyses. The maternal diet significantly affected fetal liver development and mineral reserves. Using an RNA-Seq approach, we identified 320 unique differentially expressed genes (DEGs) across all six comparisons (FDR <0.05). Furthermore, lncRNAs were predicted through the FEELnc pipeline, revealing 99 unique differentially expressed lncRNAs (DELs). The over-represented pathways and biological processes (BPs) were associated with energy metabolism, Wnt signaling, CoA carboxylase activity, and fatty acid metabolism. The DEL-regulated BPs were associated with metal ion transport, pyrimidine metabolism, and classical energy metabolism-related glycolytic, gluconeogenic, and TCA cycle pathways. Our findings suggest that lncRNAs regulate mineral homeostasis- and energy metabolism-related gene networks in the fetal liver in response to early maternal nutrition.

A jasmonate-mediated regulatory network modulates diurnal floret opening time in rice

Diurnal floret opening time (DFOT) is a pivotal trait for successful fertilization and hybrid breeding in rice. However, the molecular mechanism underlying this trait is poorly understood in rice. In this study, we combined the cytological, genetic and molecular studies to demonstrate that jasmonic acid (JA) regulates DFOT in rice through modulating the turgor and osmotic pressure of the lodicules. We show that lodicules undergo dramatic morphologic changes, accompanied by changes in water and sugar contents during the process of floret opening. Consistently, a large set of genes associated with cell osmolality and cell wall remodeling exhibits distinct expression profiles at different time points in our time-course transcriptomes of lodicules. Notably, a group of JA biosynthesis and signaling genes is continuously upregulated, accompanied by a gradual increase in JA accumulation as floret opening approaching. Furthermore, we demonstrate that the JA biosynthesis gene OsAOS1 is required for endogenous JA biosynthesis in lodicules and promoting rice DFOT. Moreover, OsMYC2, a master regulator of JA signaling, regulates rice DFOT by directly activating OsAOS1, OsSWEET4, OsPIP2;2 and OsXTH9. Collectively, our findings establish a core regulatory network mediated by JA for modulating rice DFOT and provide effective gene targets for the genetic improvement of DFOT in rice.

ERP29 regulates the proliferation of endometrial carcinoma via M6A modification

AIMS

Endoplasmic reticulum protein 29 (ERP29) is crucial for endoplasmic reticulum stress (ERS). M6A plays an important role in the progression of endometrial cancer (EC). The study investigated the role of ERS-related gene (ERP29) and m6A in EC.

MATERIALS AND METHODS

We screened ERS-related genes based on the GEO dataset, GSEA dataset and TCGA-UCEC database using WGCNA and two machine learning algorithms. The m6A-related GEO dataset was employed to identify the ERS-related hub genes with m6A. Expression of hub genes in different cell types were visualize through scRNA-seq data analyzing. Using qPCR, Western blot, and Immunohistochemical assays to detect the expression of ERP29, the effect of ERP29 on cancer cell proliferation was investigated through CCK8, EdU and clone formation experiments. M6A modifications were studied using m6A Dot blot and MeRIP-qPCR. Finally, we conducted rescue experiments.

KEY FINDINGS

Ten ERS-related hub genes with m6A were identified. ERP29 is highly expressed in EC. ERP29 knockdown inhibits EC cell proliferation. METTL3 overexpression increases the ERP29 mRNA m6A and decreases the expression of ERP29. Cycloleucine (Cyc), a nucleic acid methylation inhibitor, treatment reduces ERP29 mRNA m6A and increases the expression of ERP29. Cyc rescue the low expression of ERP29 caused by overexpression of METTL3 through m6A. ERP29 knockdown rescued the increased proliferation of EC cells caused by low m6A.

SIGNIFICANCE

ERP29 is highly expressed in EC. m6A regulates ERP29 expression and affects the proliferation of endometrial cancer cells. This represents the premise for applying ERP29 and m6A modifications in diagnosing and treating EC.

Decoding the immune microenvironment: unveiling CD8 + T cell-related biomarkers and developing a prognostic signature for personalized glioma treatment

BACKGROUND

Gliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data.

METHODS

In this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted.

RESULTS

CD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram's predictions were supported by calibration plots, further validating its accuracy.

CONCLUSION

In conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma.

Nicotinamide riboside modulates the reactive species interactome, bioenergetic status and proteomic landscape in a brain-region-specific manner

Nicotinamide riboside (NR), a precursor of nicotinamide adenine dinucleotide (NAD+), has robust cognitive benefits and alleviates neuroinflammation in Alzheimer's Disease (AD) mouse models without decreasing beta-amyloid plaque pathology. Such effects may be mediated by the reactive species interactome (RSI), at the metabolome level. In this study, we employed in vitro and in vivo models of oxidative stress, aging and AD to profile the effects of NR on neuronal survival, RSI, and the whole proteome characterization of cortex and hippocampus. RSI analysis yielded a complex modulation upon NR treatment. We constructed protein co-expression networks and correlated them to NR treatment and all measured reactive species. We observed brain-area specific effects of NR on co-expressed protein modules of oxidative phosphorylation, fatty acid oxidation, and neurotransmitter regulation pathways, which correlated with RSI components. The current study contributes to the understanding of modulation of the metabolome, specifically after NR treatment in AD and how it may play disease-modifying roles.

DEFB119 stratifies dysbiosis with distorted networks in the seminal microbiome associated with male infertility

Infertility is associated with the alteration of the seminal microbiome. However, the onset of dysbiosis remains controversial and the involvement of host factors remains elusive. This study investigates the alterations of the seminal microbiome in male infertility and examines the association and function of DEFB119, a reproductive-tract-specific host antimicrobial peptide, on the seminal microbiome and male fertility. While we observed comparable genera, diversity and evenness of bacterial communities, a marked decrease in the modularity of the metacommunities was observed in patients with abnormal spermiogram (n = 57) as compared to the control (n = 30). A marked elevation of DEFB119 was observed in a subpopulation of male infertile patients (n = 5). Elevated seminal DEFB119 was associated with a decrease in the observed genera, diversity and evenness of bacterial communities, and further distortion of the metacommunities. Mediation analysis suggests the involvement of elevated DEFB119 and dysbiosis of the seminal microbiome in mediating the abnormalities in the spermiogram. Functional experiments showed that recombinant DEFB119 significantly decrease the progressive motility of sperm in patients with abnormal spermiogram. Moreover, DEFB119 demonstrated species-specific antimicrobial activity against common seminal and nonseminal species. Our work identifies an important host factor that mediates the host-microbiome interaction and stratifies the seminal microbiome associated with male infertility. These results may lead to a new diagnostic method for male infertility and regimens for formulating the microbiome in the reproductive tract and other organ systems.

Weighted gene co-expression network analysis identifies important modules and hub genes involved in the regulation of breast muscle yield in broilers

OBJECTIVE

Increasing breast meat production is one of the primary goals of the broiler industry. Over the past few decades, tremendous progress has been made in genetic selection and the identification of candidate genes for improving the breast muscle mass. However, the molecular network contributing to muscle production traits in chickens still needs to be further illuminated.

METHODS

A total of 150 1-day-old male 817 broilers were reared in a floor litter system. At the market age of 50 d, eighteen healthy 817 broilers were slaughtered and the left pectoralis major muscle sample from each bird was collected for RNA-seq sequencing. The birds were then plucked and eviscerated and the whole breast muscle was removed and weighed. Breast muscle yield was calculated as the ratio of the breast muscle weight to the eviscerated weight. To identify the co-expression networks and hub genes contributing to breast muscle yield in chickens, we performed weighted gene co-expression network analysis (WGCNA) based on the 18 transcriptome datasets of pectoralis major muscle from eighteen 817 broilers.

RESULTS

The WGCNA analysis classified all co-expressed genes in the pectoral muscle of 817 broilers into 44 modules. Among these modules, the turquoise and skyblue3 modules were found to be most significantly positively (r = 0.78, p = 1e-04) and negatively (r = -0.57, p = 0.01) associated with breast meat yield, respectively. Further analysis identified several hub genes (e.g., DLX3, SH3RF2, TPM1, CAV3, MYF6, and CFL2) that involved in muscle structure and muscle development were identified as potential regulators of breast meat production.

CONCLUSION

The present study has advanced our understanding of the molecular regulatory networks contributing to muscle growth and breast muscle production and will contribute to the molecular breeding of chickens in the future.

Lipocalin-2-mediated intestinal epithelial cells pyroptosis via NF-κB/NLRP3/GSDMD signaling axis adversely affects inflammation in colitis

Ulcerative colitis (UC) is a major inflammatory bowel disease (IBD) characterized by intestinal epithelium damage. Recently, Lipocalin-2 (LCN2) has been identified as a potential fecal biomarker for patients with UC. However, further investigation is required to explore its pro-inflammatory role in UC and the underlying mechanism. The biological analysis revealed that Lcn2 serves as a putative signature gene in the colon mucosa of patients with UC and its association with the capsase/pyroptosis signaling pathway in UC. In wild-type mice with DSS-induced colitis, LCN2 overexpression in colon mucosa via in vivo administration of Lcn2 overexpression plasmid resulted in exacerbation of colitis symptoms and epithelium damage, as well as increased expression levels of pyroptosis markers (cleaved caspase1, GSDMD, IL-1β, HMGB1 and IL-18). Additionally, we observed downregulation in the expression levels of pyroptosis markers following in vivo silencing of LCN2. However, the pro-inflammatory effect of LCN2 overexpression was effectively restrained in GSDMD-KO mice. Moreover, single-cell RNA-sequencing analysis revealed that Lcn2 was predominantly expressed in the intestinal epithelial cells (IECs) within the colon mucosa of patients with UC. We found that LCN2 effectively regulated pyroptosis events by modulating the NF-κB/NLRP3/GSDMD signaling axis in NCM460 cells stimulated by LPS and ATP. These findings demonstrate the pro-inflammatory role of LCN2 in colon epithelium and provide a potential target for inhibiting pyroptosis in UC.

Physiological and comprehensive transcriptome analysis reveals distinct regulatory mechanisms for aluminum tolerance of Trifolium repens

It is estimated that up to 50 % of arable lands worldwide are acidic, and most crops are severely inhibited due to the high active aluminum (Al). Trifolium repens is an excellent legume forage with a certain acid tolerance, although it is affected by Al toxicity in acidic soil. In this study, physiological and transcriptomic responses of different white clover varieties were analyzed when exposed to a high-level of Al stress. The results revealed that Trifolium repens had a high level of Al toxicity tolerance, and accumulated nearly 70 % of Al3+ in its roots. Al toxicity significantly inhibited the root length and root activity, decreased the chlorophyll (Chl) content and photosynthetic pigments, while significantly increased the intercellular CO2 concentration (Ci). The content of malondialdehyde (MDA), electrolyte leakage (EL), proline and reactive oxygen species (ROS) were significantly accumulated under Al stress. Furthermore, a total of 27,480 differentially expressed genes (DEGs) were identified after the treatment. Gene ontology (GO) and Kyoto encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that most Al-responsive genes enriched to chloroplast thylakoid membrane, chloroplast stroma and photosynthesis in Haifa leaf while in MAG leaf highly enriched in response to regulation of defense response, which could induce the different tolerance of the two cultivars to Al stress. Besides, pectin methylesterase (PME), glycosyl transferases (GT1) and chalcone synthase genes associated with cell wall biosynthesis may improve the Al accumulation and enhance tolerance of Al toxicity. The results established here would help to understand the morphological structure, physiological and biochemical response, and molecular mechanism of white clover under Al tolerance.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets

BACKGROUND

Transcriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait.

RESULTS

Using the phenotypic values of shoot and root traits and transcript abundances in leaves and roots of 57 rice accessions, we evaluated the predictive abilities of the transcriptome-based prediction models. Leaf transcripts predicted shoot phenotypes, such as plant height, more accurately than root transcripts, whereas root transcripts predicted root phenotypes, such as crown root length, more accurately than leaf transcripts. Furthermore, we used the following three features to train the prediction model: (1) tissue specificity of the transcripts, (2) ontology annotations, and (3) co-expression modules for selecting gene subsets. Although models trained by a gene subset often resulted in lower predictive abilities than the model trained by all genes, some gene subsets showed improved predictive ability. For example, using genes expressed in roots but not in leaves, the predictive ability for crown root diameter was improved by more than 10% (R2 = 0.59 when using all genes; R2 = 0.66, using 1,554 root-specifically expressed genes). Similarly, genes annotated as "gibberellic acid sensitivity" showed higher predictive ability than using all genes for root dry weight.

CONCLUSIONS

Our results highlight both the possibility and difficulty of selecting an appropriate gene subset to predict polygenic traits from transcript abundance, given the current biological knowledge and information. Further integration of multiple sources of information, as well as improvements in gene characterization, may enable the selection of an optimal gene set for the prediction of polygenic phenotypes.