WGCNA: an R package for weighted correlation network analysis

Acute toxicity of salicylic acid and its derivatives on the diatom Phaeodactylum tricornutum: Physico-Biochemical and transcriptomic insights

Salicylate pollutants (SAs) poses a serious threat to marine ecosystems as emerging contaminants. However, the toxic effects of SAs on marine phytoplankton, as well as the potential mechanisms and their ecological risks linked with them, are remain largely unknown. In this study, we aimed to evaluate the toxic effects of salicylic acid (SA) and its 5-substituted derivatives (5-sSA) on the marine diatom Phaeodactylum tricornutum, as well as the potential molecular mechanism involved in the toxicity. Physiological assays conducted on P. tricornutum revealed significant changes in photosynthetic pigments, chlorophyll fluorescence parameters, and antioxidant enzyme activities. The results showed that exposure of P. tricornutum to SAs caused a significant decline in chlorophyll contents and damage to the photosystem II (PSII) core resulting in the decline of photosynthesis. Although the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) were enhanced, oxidative damage occurred. Transcriptome analysis showed that a large number of differentially expresses genes (DEGs) were significantly enriched in metabolic pathways such as porphyrin metabolism, terpenoid backbone biosynthesis, and carbon fixation in photosynthetic organisms after SA and 5-BrSA treatments. In addition, key genes in transcriptomic metabolic pathways were further analyzed and validated using weighted correlation network analysis (WGCNA) and real-time fluorescence quantitative PCR (qPCR). Considering the above results, SAs mainly inhibit the processes of photosynthesis by repressing the expression of genes involved in secondary metabolite synthesis and photosynthetic carbon sequestration pathways, thus exerting toxic effects on algal cells. The results of the study will provide key data for understanding the ecological risk and toxicity mechanisms of SA pollutants.

A MYB transcription factor underlying plant height in sorghum qHT7.1 and maize Brachytic 1 loci

Manipulating plant height is an essential component of crop improvement. Plant height was generally reduced through breeding in wheat, rice, and sorghum to resist lodging and increase grain yield but kept high for bioenergy crops. Here, we positionally cloned a plant height quantitative trait locus (QTL) qHT7.1 as a MYB transcription factor controlling internode elongation, cell proliferation, and cell morphology in sorghum. A 740 bp transposable element insertion in the intronic region caused a partial mis-splicing event, generating a novel transcript that included an additional exon and a premature stop codon, leading to short plant height. The dominant allele had an overall higher expression than the recessive allele across development and internode position, while both alleles' expressions peaked at 46 days after planting and progressively decreased from the top to lower internodes. The orthologue of qHT7.1 was identified to underlie the brachytic1 (br1) locus in maize. A large insertion in exon 3 and a 160 bp insertion at the promoter region were identified in the br1 mutant, while an 18 bp promoter insertion was found to be associated with reduced plant height in a natural recessive allele. CRISPR/Cas9-induced gene knockout of br1 in two maize inbred lines showed significant plant height reduction. These findings revealed functional connections across natural, mutant, and edited alleles of this MYB transcription factor in sorghum and maize. This enriched our understanding of plant height regulation and enhanced our toolbox for fine-tuning plant height for crop improvement.

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.

Network analysis reveals age- and virus-specific circuits in nasal epithelial cells of extremely premature infants

BACKGROUND AND OBJECTIVES

Viral respiratory infections significantly affect young children, particularly extremely premature infants, resulting in high hospitalization rates and increased health-care burdens. Nasal epithelial cells, the primary defense against respiratory infections, are vital for understanding nasal immune responses and serve as a promising target for uncovering underlying molecular and cellular mechanisms.

METHODS

Using a trans-well pseudostratified nasal epithelial cell system, we examined age-dependent developmental differences and antiviral responses to influenza A and respiratory syncytial virus through systems biology approaches.

RESULTS

Our studies revealed differences in innate-receptor repertoires, distinct developmental pathways, and differentially connected antiviral network circuits between neonatal and adult nasal epithelial cells. Consensus network analysis identified unique and shared cellular-viral networks, emphasizing highly relevant virus-specific pathways, independent of viral replication kinetics.

CONCLUSION

This research highlights the importance of nasal epithelial cells in innate antiviral immune responses and offers crucial insights that allow for a deeper understanding of age-related differences in nasal epithelial cell immunity following respiratory virus infections.

Decoding marker genes and immune landscape of unstable carotid plaques from cellular senescence

Recently, cellular senescence-induced unstable carotid plaques have gained increasing attention. In this study, we utilized bioinformatics and machine learning methods to investigate the correlation between cellular senescence and the pathological mechanisms of unstable carotid plaques. Our aim was to elucidate the causes of unstable carotid plaque progression and identify new therapeutic strategies. First, differential expression analysis was performed on the test set GSE43292 to identify differentially expressed genes (DEGs) between the unstable plaque group and the control group. These DEGs were intersected with cellular senescence-associated genes to obtain 40 cellular senescence-associated DEGs. Subsequently, key genes were then identified through weighted gene co-expression network analysis, random forest, Recursive Feature Elimination for Support Vector Machines algorithm and cytoHubba plugin. The intersection yielded 3 CSA-signature genes, which were validated in the external validation set GSE163154. Additionally, we assessed the relationship between these CSA-signature genes and the immune landscape of the unstable plaque group. This study suggests that cellular senescence may play an important role in the progression mechanism of unstable plaques and is closely related to the influence of the immune microenvironment. Our research lays the foundation for studying the progression mechanism of unstable carotid plaques and provides some reference for targeted therapy.

CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease

In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers.

Multi-omics revealed that ELAVL3 regulates MYCN in neuroblastoma via immunogenic cell death: Risk stratification and experimental research

Neuroblastoma (NB), a common and highly lethal malignant disease in pediatrics, still lacks an effective therapeutic approach that addresses all conditions. Immunogenic Cell Death (ICD) plays a crucial role in tumor cell death and triggers a potent anti-tumor immune response. In this study, we report an ICD-related index (ICDR-Index) in NB through various machine learning methodologies, utilizing bulk transcriptome data from 1244 NB samples and 16 scRNA-seq datasets. Our results showed that the ICDR-Index could accurately identify different risk subtypes of patients with NB and provide predictive value for prognosis. Importantly, we found that high-risk patients with NB exhibited significantly poor overall survival (OS) rates, adverse clinical phenotypes, poor immune cell infiltration, and low sensitivity to immunotherapy. Furthermore, we identified ELAVL3 as a key gene within the ICDR-Index, where high expression levels were associated with malignancy and poor OS in NB. Additionally, targeted silencing of ELAVL3 down-regulated MYCN gene expression and reduced the malignancy of NB cells. Notably, the si-ELAVL3-transfected NB cells enhanced the anti-tumor activity of NK cells. Collectively, this study offers avenues for predicting the risk stratification of patients with NB and reveals a potential mechanism by which ELAVL3 regulates NB cell death.

Discovery of PANoptosis-related signatures correlates with immune cell infiltration in psoriasis

Psoriasis is an inflammatory skin disease that relapses frequently. Keratinocyte apoptosis dysregulation plays a crucial role in the pathological mechanisms of psoriasis. PANoptosis is a process with intermolecular interaction among pyroptosis, apoptosis, and necroptosis. The mechanism of PANoptosis in the occurrence and development of psoriasis is still unclear. Here we present a novel approach by identifying PANoptosis-related signatures (PANoptosis-sig) from skin tissue of psoriasis patients and healthy controls on transcriptional and protein levels. Five PANoptosis-sig (TYMP, S100A8, S100A9, NAMPT, LCN2) were identified. Enrichment analysis showed they were mainly enriched in response to leukocyte aggregation, leukocyte migration, chronic inflammatory response and IL-17 signaling pathway. Single cell transcriptome analysis showed TYMP and NAMPT were expressed in almost all cell populations, while LCN2, S100A8 and S100A9 were significantly highly expressed in keratinocyte. We then constructed predictive and diagnostic models with the PANoptosis-sig and evaluated their performance. Finally, unsupervised consensus clustering analysis was conducted to ascertain psoriasis molecular subtypes by the PANoptosis-sig. The psoriasis cohort was divided into two distinct subtypes. Immune landscape showed that the stromal score of cluster 1 was significantly higher than cluster 2, while the immune and estimate scores of cluster 2 were expressively higher than cluster 1. Cluster 1 exhibited high expression of Plasma cells, Tregs and Mast cells resting, while cluster 2 showed high expression of T cells, Macrophages M1, Dendritic cells activated, and Neutrophils in immune infiltration analysis. And cluster 2 was more sensitive to immune checkpoints. In conclusion, our findings revealed potential biomarkers and therapeutic targets for the prevention, diagnosis, and treatment of psoriasis, enhancing our understanding of the molecular mechanisms underlying PANoptosis.

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Sex dimorphism and tissue specificity of gene expression changes in aging mice

BACKGROUND

Aging is a complex process that involves all tissues in an organism and shows sex dimorphism. While transcriptional changes in aging have been well characterized, the majority of studies have focused on a single sex and sex differences in gene expression in aging are poorly understood. In this study, we explore sex dimorphism in gene expression in aging mice across three tissues.

METHODS

We collected gastrocnemius muscle, liver and white adipose tissue from young (6 months, n = 14) and old (24 months, n = 14) female and male C57BL/6NIA mice and performed RNA-seq. To investigate sex dimorphism in aging, we considered two levels of comparisons: (a) differentially expressed genes between females and males in the old age group and (b) comparisons between females and males across the aging process. We utilized differential expression analysis and gene feature selection to investigate candidate genes. Gene set enrichment analysis was performed to identify candidate molecular pathways. Furthermore, we performed a co-expression network analysis and chose the gene module(s) associated with aging independent of sex or tissue-type.

RESULTS

We identified both tissue-specific and tissue-independent genes associated with sex dimorphism in aged mice. Unique differentially expressed genes between old males and females across tissues were mainly enriched for pathways related to specific tissue function. We found similar results when exploring sex differences in the aging process, with the exception that in the liver genes enriched for lipid metabolism and digestive system were identified in both females and males. Combining enriched pathways across analyses, we identified amino acid metabolism, digestive system, and lipid metabolism as the core mechanisms of sex dimorphism in aging. Although the vast majority of age-related genes were sex and tissue specific, we identified 127 hub genes contributing to aging independent of sex and tissue that were enriched for the immune system and signal transduction.

CONCLUSIONS

There are clear sex differences in gene expression in aging across liver, muscle and white adipose. Core pathways, including amino acid metabolism, digestive system and lipid metabolism, contribute to sex differences in aging.

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

Alcohol use disorder (AUD) induces complex transcriptional and regulatory changes across multiple brain regions including the caudate nucleus, which remains understudied. Using paired single-nucleus RNA-seq and ATAC-seq on caudate samples from 143 human postmortem brains, including 74 with AUD, we identified 17 distinct cell types. We found that a significant portion of the alcohol-induced changes in gene expression occurred through altered chromatin accessibility. Notably, we identified novel transcriptional and chromatin accessibility differences in medium spiny neurons, impacting pathways such as RNA metabolism and immune response. A small cluster of D1/D2 hybrid neurons showed distinct differences, suggesting a unique role in AUD. Microglia exhibited distinct activation states deviating from classical M1/M2 designations, and astrocytes entered a reactive state partially regulated by JUND , affecting glutamatergic synapse pathways. Oligodendrocyte dysregulation, driven in part by OLIG2 , was linked to demyelination and increased TGF-β1 signaling from microglia and astrocytes. We also observed increased microglia-astrocyte communication via the IL-1β pathway. Leveraging our multiomic data, we performed cell type-specific expression quantitative trait loci analysis, integrating that with public genome-wide association studies to identify AUD risk genes such as ADAL and PPP2R3C , providing a direct link between genetic variants, chromatin accessibility, and gene expression in AUD. These findings not only provide new insights into the genetic and cellular mechanisms in the caudate related to AUD but also demonstrate the broader utility of large-scale multiomic studies in uncovering complex gene regulation across diverse cell types, which has implications beyond the substance use field.

Unravelling alternative splicing patterns in susceptible and resistant Brassica napus lines in response to Xanthomonas campestris infection

BACKGROUND

Rapeseed (Brassica napus L.) is an important oil and industrial crop worldwide. Black rot caused by the bacterial pathogen Xanthomonas campestris pv. campestris (Xcc) is an infectious vascular disease that leads to considerable yield losses in rapeseed. Resistance improvement through genetic breeding is an effective and sustainable approach to control black rot disease in B. napus. However, the molecular mechanisms underlying Brassica-Xcc interactions are not yet fully understood, especially regarding the impact of post-transcriptional gene regulation via alternative splicing (AS).

RESULTS

In this study, we compared the AS landscapes of a susceptible parental line and two mutagenized B. napus lines with contrasting levels of black rot resistance. Different types of AS events were identified in these B. napus lines at three time points upon Xcc infection, among which intron retention was the most common AS type. A total of 1,932 genes was found to show differential AS patterns between different B. napus lines. Multiple defense-related differential alternative splicing (DAS) hub candidates were pinpointed through an isoform-based co-expression network analysis, including genes involved in pathogen recognition, defense signalling, transcriptional regulation, and oxidation reduction.

CONCLUSION

This study provides new insights into the potential effects of post-transcriptional regulation on immune responses in B. napus towards Xcc attack. These findings could be beneficial for the genetic improvement of B. napus to achieve durable black rot resistance in the future.

Unveiling mitochondria as central components driving cognitive decline in alzheimer's disease through cross-transcriptomic analysis of hippocampus and entorhinal cortex microarray datasets

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by symptoms such as memory loss and impaired learning. This study conducted a cross-transcriptomic analysis of AD using existing microarray datasets from the hippocampus (HC) and entorhinal cortex (EC), comparing them with age-matched non-AD controls. Both of these brain regions are critical for learning and memory processing and are vulnerable areas that exhibit abnormalities in early AD. The cross-transcriptomic analysis identified 564 significantly differentially expressed genes in HC and 479 in EC. Among these, 151 genes were significantly differentially expressed in both tissues, with functions related to synaptic vesicle clustering, synaptic vesicle exocytosis/endocytosis, mitochondrial ATP synthesis, hydrogen ion transmembrane transport, and structural constituent of cytoskeleton, suggesting a potential association between cognitive decline in AD, synaptic vesicle dynamics, dysregulation of cytoskeleton organization, and mitochondrial dysfunction. Further gene ontology analysis specific to the HC revealed the gene ontology enrichment in aerobic respiration, synaptic vesicle cycle, and oxidative phosphorylation. The enrichment analysis in CA1 of HC revealed differentiation in gene expression related to mitochondrial membrane functions involved in bioenergetics, mitochondrial electron transport, and biological processes associated with microtubule-based process, while analysis in the EC region showed enrichment in synaptic vesicle dynamics which is associated with neurotransmitter release and the regulation of postsynaptic membrane potential and synaptic transmission of GABAergic and glutamatergic synapse. Protein-protein interaction analysis highlighted central hub proteins predominantly expressed in mitochondria, involved in regulation of oxidative stress and ATP synthesis. These hub proteins interact not only within the mitochondria but also with proteins in the vesicular membrane and neuronal cytoskeleton, indicating a central role of mitochondria. This finding underscores the association between clinical symptoms and mitochondrial dysregulation of synaptic vesicle dynamics, cytoskeleton organization, and mitochondrial processes in both the HC and EC of AD. Therefore, targeting these dysregulated pathways could provide promising therapeutic targets aimed at cognitive decline and memory impairment in early AD stages.

Brain-targeting liposome-based APOE2 gene delivery exacerbates soluble amyloid-β accumulation in App NL-G-F mice

Alzheimer's disease (AD) is the most common cause of late-life dementia characterized by progressive neurodegeneration and brain deposition of amyloid-β (Aβ) and phosphorylated tau. The APOE ε2 encoding apolipoprotein E (APOE2) is a protective allele against AD among the three genotypes (APOE ε2, ε3, ε4), while APOE4 is the strongest genetic factor substantially increasing AD risk. APOE regulates brain lipid homeostasis and maintaining synaptic plasticity and neuronal function, where APOE2 has a superior function compared to APOE3 and APOE4. Gene therapy that increases APOE2 levels in the brain is, therefore, a promising therapeutic strategy for AD treatment. We previously reported that PEGylated liposomes conjugated with transferrin and a cell-penetrating peptide Penetratin sufficiently deliver chitosan-APOE2 cDNA plasmid complex into the brain of wild-type mice. Here, we investigated how brain-targeting liposome-based APOE2 gene delivery influences Aβ-related pathologies in amyloid model App NL-G-F knockin mice at 12-month-old. We found a trend of reductions of insoluble Aβ levels in the mouse cortices 1 month after APOE2 gene therapy. Furthermore, in the App NL-G-F knockin mice that received the APOE2 gene therapy, brain transcriptome analysis through RNA-sequencing identified the upregulation of genes/pathways related to neuronal development. This was supported by increases of Dlg4 and Syp mRNAs coding synaptic proteins in the experimental group. On the other hand, we found that APOE2 gene delivery increased soluble Aβ levels, including oligomers, as well as exacerbated neurite dystrophy and decreased synaptophysin. Together, our results suggest that brain-targeting liposome-based APOE2 gene therapy is potentially beneficial for synaptic formation at the transcriptional level. Forced APOE2 expressions, however, may exacerbate Aβ toxicity by increasing the dissociation of Aβ oligomers from aggregates in the presence of considerable amyloid burden.

Deciphering the molecular mechanisms of heat stress tolerance in goats: Insights from transcriptome and Gene Co-expression analysis

Climate change poses a significant threat to the sustainability of livestock production systems in developing countries, particularly impacting small ruminants like goats, which are highly susceptible to heat stress. This stressor not only reduces productivity but also undermines economic viability. This study aimed to delve into the molecular mechanisms underlying heat stress tolerance in goats by conducting a comprehensive transcriptome analysis of heat-tolerant (HT, n = 4) and heat-susceptible (HS, n = 6) Jamunapari goats. Physiological metrics, such as rectal temperature, respiratory rate, and heart rate, were meticulously monitored under extreme environmental conditions (Temperature Humidity Index >92) to effectively classify goats based on their distinct heat stress responses. Samples of blood were obtained, and peripheral blood mononuclear cells (PBMCs) were extracted for subsequent RNA extraction. RNA-Seq analysis revealed a sum of 734 differentially expressed genes (DEGs), comprising 251 upregulated and 483 downregulated genes in HT goats compared to their HS counterparts. The WGCNA revealed three key modules, darkorange (tolerance), paleturquoise (respiration rate), and darkmagenta (heart rate). Moreover, functional enrichment analysis revealed that DEGs within these modules played intricate roles in crucial biological processes and pathways, including mitochondrial function, cardiac function, immune response, genomic stability, and metabolic regulation. This research notably enhances our comprehension of the genetic underpinnings of thermo-tolerance in goats and provides invaluable guidance for formulating breeding strategies aimed at bolstering livestock resilience against the challenges of climate change.

The transcription factor EjNAC5 regulates loquat fruit chilling lignification

Changes in both lignin biosynthesis and DNA methylation have been reported to be associated with chilling stress in plants. When stored at low temperatures, red-fleshed loquat is prone to lignification, with increased lignin content and fruit firmness, which has deleterious effects on taste and eating quality. Here, we found that 5 °C storage mitigated the increasing firmness and lignin content of red-fleshed 'Dahongpao' ('DHP') loquat fruit that occurred during 0 °C storage. EjNAC5 was identified by integrating RNA sequencing with whole-genome bisulfite sequencing analysis of 'DHP' loquat fruit. The transcript levels of EjNAC5 were positively correlated with changes in firmness and negatively correlated with changes in DNA methylation level of a differentially methylated region in the EjNAC5 promoter. In white-fleshed 'Baisha' ('BS') loquat fruit, which do not undergo chilling-induced lignification at 0 °C, the transcripts of EjNAC5 remained low and the methylation level of the differentially methylated region in the EjNAC5 promoter was higher, compared with 'DHP' loquat fruit. Transient overexpression of EjNAC5 in loquat fruit and stable overexpression in Arabidopsis and liverwort led to an increase in lignin content. Furthermore, EjNAC5 interacts with EjERF39 and EjHB1 and activates the transcription of Ej4CL1 and EjPRX12 genes involved in lignin biosynthesis. This regulatory network involves different transcription factors from those involved in the lignification pathway. Our study indicates that EjNAC5 promoter methylation modulates EjNAC5 transcript levels and identifies novel EjNAC5-EjERF39-Ej4CL1 and EjNAC5-EjHB1-EjPRX12 regulatory modules involved in chilling induced-lignification.

Cuticle development and the underlying transcriptome-metabolome associations during early seedling establishment

The plant cuticle is a complex extracellular lipid barrier that has multiple protective functions. This study investigated cuticle deposition by integrating metabolomics and transcriptomics data gathered from six different maize seedling organs of four genotypes, the inbred lines B73 and Mo17, and their reciprocal hybrids. These datasets captured the developmental transition of the seedling from heterotrophic skotomorphogenic growth to autotrophic photomorphogenic growth, a transition that is highly vulnerable to environmental stresses. Statistical interrogation of these data revealed that the predominant determinant of cuticle composition is seedling organ type, whereas the seedling genotype has a smaller effect on this phenotype. Gene-to-metabolite associations assessed by integrated statistical analyses identified three gene networks associated with the deposition of different elements of the cuticle: cuticular waxes; monomers of lipidized cell wall biopolymers, including cutin and suberin; and both of these elements. These gene networks reveal three metabolic programs that appear to support cuticle deposition, including processes of chloroplast biogenesis, lipid metabolism, and molecular regulation (e.g. transcription factors, post-translational regulators, and phytohormones). This study demonstrates the wider physiological metabolic context that can determine cuticle deposition and lays the groundwork for new targets for modulating the properties of this protective barrier.

The shifts in microbial interactions and gene expression caused by temperature and nutrient loading influence Raphidiopsis raciborskii blooms

Climate change and the trophic status of water bodies are important factors in global occurrence of cyanobacterial blooms. The aim of this study was to explore the cyanobacteria‒bacterial interactions that occur during Raphidiopsis raciborskii (R. raciborskii) blooms by conducting microcosm simulation experiments at different temperatures (20 °C and 30 °C) and with different phosphorus concentrations (0.01 mg/L and 1 mg/L) using an ecological model of microbial behavior and by analyzing microbial self-regulatory strategies using weighted gene coexpression network analysis (WGCNA). Three-way ANOVA revealed significant effects of temperature and phosphorus on the growth of R. raciborskii (P < 0.001). The results of a metagenomics-based analysis of bacterioplankton revealed that the synergistic effects of both climate and trophic changes increased the ability of R. raciborskii to compete with other cyanobacteria for dominance in the cyanobacterial community. The antagonistic effects of climate and nutrient changes favored the occurrence of R. raciborskii blooms, especially in eutrophic waters at approximately 20 °C. The species diversity and richness indices differed between the eutrophication treatment group at 20 °C and the other treatment groups. The symbiotic bacterioplankton network revealed the complexity and stability of the symbiotic bacterioplankton network during blooms and identified the roles of key species in the network. The study also revealed a complex pattern of interactions between cyanobacteria and non-cyanobacteria dominated by altruism, as well as the effects of different behavioral patterns on R. raciborskii bloom occurrence. Furthermore, this study revealed self-regulatory strategies that are used by microbes in response to the dual pressures of temperature and nutrient loading. These results provide important insights into the adaptation of microbial communities in freshwater ecosystems to environmental change and provide useful theoretical support for aquatic environmental management and ecological restoration efforts.

Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis

In this study, we aimed to identify an essential blood molecular signature for chacterizing the progression of sepsis-induced acute lung injury using integrated bioinformatic and machine learning analysis. The results showed that a total of 88 functionally related ALI-associated hub genes in sepsis were identified by MCODE analysis and they were enriched in infection and inflammtory responses, lung and cardiovascular disease pathways. These hub genes stratified ALI-sepsis and sepsis and further stratified two subtypes of sepsis-ALI with differential ALI scores, hub gene expression patterns, and levels of immune cells. A seven-gene signature including TNFRSF1A, NFKB1, FCGR2A, NFE2L2, ICAM1 and SOCS3 and PDCD1 was derived from the hub genes. These genes were significantly implicated in immune and metabolism pathways. They were expressed in six circulatory immune cells based on analysis of a single cell RNA sequencing dataset. Furthermore, the seven-gene signature was corrobarated using by integrating 12 machine learning algorithms. A premium three-gene signature NFE2L2, FCGR2A and PDCD1 for differentiating ALI-sepsis from sepsis were also derived from the seven-gene signature based on analysis of the seven core hub genes by the machine learning algorithms. Furthermore, the expressions of hub genes were verified in sepsis mice models. Therefore, our study provided an avenue to develop a molecular tool for identify and characterize progression of acute lung injury associated with sepsis.

Identifying the prognostic significance of mitophagy-associated genes in multiple myeloma: a novel risk model construction

Multiple myeloma (MM) is a highly heterogeneous hematological malignancy that is currently incurable. Individualized therapeutic approaches based on accurate risk assessment are essential for improving the prognosis of MM patients. Nevertheless, current prognostic models for MM exhibit certain limitations and prognosis heterogeneity still an unresolved issue. Recent studies have highlighted the pivotal involvement of mitochondrial autophagy in the development and drug sensitivity of MM. This study seeks to conduct an integrative analysis of the prognostic significance and immune microenvironment of mitophagy-related signature in MM, with the aim of constructing a novel predictive risk model. GSE4581 and GSE47552 datasets were acquired from the Gene Expression Omnibus database. MM-differentially expressed genes (DEGs) were identified by limma between MM samples and normal samples in GSE47552. Mitophagy key module genes were obtained by weighted gene co-expression network analysis in the Cancer Genome Atlas (TCGA)-MM dataset. Mitophagy DEGs were identified by the overlap genes between MM-DEGs and mitophagy key module genes. Prognostic genes were selected through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, and a risk model was subsequently constructed based on these prognostic genes. Subsequently, the MM samples were stratified into high- and low-risk groups based on their median risk scores. The validity of the risk model was further evaluated using the GSE4581 dataset. Moreover, a nomogram was developed using the independent prognostic factors identified from the risk score and various clinical indicators. Additionally, analyses were conducted on immune infiltration, immune scores, immune checkpoint, and chemotherapy drug sensitivity. The 17 mitophagy DEGs were obtained by intersection of 803 MM-DEGs and 1084 mitophagy key module genes. Five prognostic genes (CDC6, PRIM1, SNRPB, TOP2A, and ZNF486) were selected via LASSO and univariate cox regression analyses. The predictive performance of the risk model, which was constructed based on the five prognostic genes, demonstrated favorable results in both TCGA-MM and GSE4581 datasets as indicated by the receiver operating characteristic (ROC) curves. In addition, calibration curve, ROC curve, and decision curve analysis curve corroborated that the nomogram exhibited superior predictive accuracy for MM. Furthermore, immune analysis results indicated a significant difference in stromal scores of two risk groups categorized on median risk scores. And four immune checkpoints (CD274, CTLA4, LAG3, and PDCD1LG2) showed significant differences in different risk groups. The analysis of chemotherapy drug sensitivity revealed that etoposide and doxorubicin, which target TOP2A, exhibited superior treatment outcomes in the high-risk group. A novel prognostic model for MM was developed and validated, demonstrating significant potential in predicting patient outcomes and providing valuable guidance for personalized immunotherapy counseling.

Human-specific protein-coding and lncRNA genes cast sex-biased genes in the brain and their relationships with brain diseases

BACKGROUND

Gene expression shows sex bias in the brain as it does in other organs. Since female and male humans exhibit noticeable differences in emotions, logical thinking, movement, spatial orientation, and even the incidence of neurological disorders, sex biases in the brain are especially interesting, but how they are determined, whether they are conserved or lineage specific, and what the consequences of the biases are, remain poorly explored and understood.

METHODS

Based on RNA-seq datasets from 16  and 14 brain regions in humans and macaques across developmental periods and from patients with brain diseases, we used linear mixed models (LMMs) to differentiate variations in gene expression caused by factors of interest and confounding factors and identify four types of sex-biased genes. Effect size and confidence in each effect were measured upon the local false sign rate (LFSR). We utilized the biomaRt R package to acquire orthologous genes in humans and macaques from the BioMart Ensembl website. Transcriptional regulation of sex-biased genes by sex hormones and lncRNAs were analyzed using the CellOracle, GENIE3, and Longtarget programs. Sex-biased genes' functions were revealed by gene set enrichment analysis using multiple methods.

RESULTS

Lineage-specific sex-biased genes greatly determine the distinct sex biases in human and macaque brains. In humans, those encoding proteins contribute directly to immune-related functions, and those encoding lncRNAs intensively regulate the expression of other sex-biased genes, especially genes with immune-related functions. The identified sex-specific differentially expressed genes (ssDEGs) upon gene expression in disease and normal samples also indicate that protein-coding ssDEGs are conserved in humans and macaques but that lncRNA ssDEGs are not conserved. The results answer the above questions, reveal an intrinsic relationship between sex biases in the brain and sex-biased susceptibility to brain diseases, and will help researchers investigate human- and sex-specific ncRNA targets for brain diseases.

CONCLUSIONS

Human-specific genes greatly cast sex-biased genes in the brain and their relationships with brain diseases, with protein-coding genes contributing to immune response related functions and lncRNA genes critically regulating sex-biased genes. The high proportions of lineage-specific lncRNAs in mammalian genomes indicate that sex biases may have evolved rapidly in not only the brain but also other organs.

ncPlantDB: a plant ncRNA database with potential ncPEP information and cell type-specific interaction

The field of plant non-coding RNAs (ncRNAs) has seen significant advancements in recent years, with many ncRNAs recognized as important regulators of gene expression during plant development and stress responses. Moreover, the coding potential of these ncRNAs, giving rise to ncRNA-encoded peptides (ncPEPs), has emerged as an essential area of study. However, existing plant ncRNA databases lack comprehensive information on ncRNA-encoded peptides (ncPEPs) and cell type-specific interactions. To address this gap, we present ncPlantDB (https://bis.zju.edu.cn/ncPlantDB), a comprehensive database integrating ncRNA and ncPEP data across 43 plant species. ncPlantDB encompasses 353 140 ncRNAs, 3799 ncPEPs and 4 647 071 interactions, sourced from established databases and literature mining. The database offers unique features including translational potential data, cell-specific interaction networks derived from single-cell RNA sequencing and Ribo-seq analyses, and interactive visualization tools. ncPlantDB provides a user-friendly interface for exploring ncRNA expression patterns at the single-cell level, facilitating the discovery of tissue-specific ncRNAs and potential ncPEPs. By integrating diverse data types and offering advanced analytical tools, ncPlantDB serves as a valuable resource for researchers investigating plant ncRNA functions, interactions, and their potential coding capacity. This database significantly enhances our understanding of plant ncRNA biology and opens new avenues for exploring the complex regulatory networks in plant genomics.

IGSF1: a biomarker for predicting prognosis, immunotherapy response, and drug candidates in COVID-19 combined hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor prognosis and a common cause of cancer-related death worldwide, and despite ongoing therapeutic breakthroughs, patient survival benefits are limited. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19) and poses a major threat to humanity worldwide. As the epidemic continues to develop, more and more people are infected with SARS-CoV-2, including patients with HCC. However, the relationship between COVID-19 and HCC has not yet been fully elucidated. Our study aimed to identify the shared genetic characteristics and molecular mechanisms between COVID-19 and HCC. The data involved in this study come from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression(GTEx), and Cancer Cell Line Encyclopedia(CCLE) databases. We used differentially expressed genes to perform enrichment analysis to reveal the biological landscape of COVID-19 combined with HCC. In addition, weighted gene co-expression network analysis (WGCNA) was used to study the co-expression network related to COVID-19 and HCC. We then combined the validation datasets to screen out immunoglobulin superfamily member 1 (IGSF1) as the most important core gene. Finally, we extensively studied the functional expression of IGSF1 in tumor samples, normal tissues, and cancer cell lines. The molecular mechanisms related to COVID-19 and HCC are rarely studied. Our study identifies IGSF1 as a potential therapeutic target and immune-related biomarker for patients with COVID-19 and HCC.

Construction of machine learning models of lipid metabolism-related long non-coding RNA in lung adenocarcinoma is associated with microenvironmental heterogeneity and immunotherapy

Using various bioinformatics tools, we constructed a prognostic model integrating the expression profiles of lipid metabolization-related lncRNAs and clinical features. Our study discovered that various lipid metabolism-related lncRNAs were linked to the prognosis of lung adenocarcinoma. The link between immune cell infiltration in the tumour microenvironment and the expression level of lncRNAs involved with lipid metabolism was also investigated. Our findings suggest that there is a complex interplay between lipid metabolism, microenvironmental heterogeneity, and immunotherapy in lung adenocarcinoma. Furthermore, the study has significant clinical implications for the development of effective therapies for patients with lung adenocarcinoma by investigating the potential of these lncRNAs as biomarkers for anticipating the response to immunotherapy. Finally, our study emphasises the significance of continued analysis of lncRNAs associated with lipid metabolism in tumours to better understand the mechanisms behind the incidence and progression of lung adenocarcinoma. Several of the strengths of our work are the extensive analysis of the relationship between lipid metabolism and lncRNAs in lung adenocarcinoma and the utilization of a sizable sample size from the TCGA-LUAD cohort. However, there are also some limitations. Firstly, the mechanisms of how these lncRNAs interact with lipid metabolism pathways and immune response require further investigation. Secondly, our study was based on bioinformatics analysis and lacked experimental verification. Finally, our study was limited to the TCGA-LUAD cohort and further validation using other independent cohorts is required. In conclusion, our study provides a comprehensive and systematic analysis of lncRNAs associated with lipid metabolism in lung adenocarcinoma. Lung cancer patients may benefit from using identified lncRNAs as therapeutic targets and prognostic biomarkers. Validating these findings and confirming the potential therapeutic applications of these lncRNAs will require more mechanistic research.

Longitudinal transcriptional changes reveal genes from the natural killer cell-mediated cytotoxicity pathway as critical players underlying COVID-19 progression

Patients present a wide range of clinical severities in response severe acute respiratory syndrome coronavirus 2 infection, but the underlying molecular and cellular reasons why clinical outcomes vary so greatly within the population remains unknown. Here, we report that negative clinical outcomes in severely ill patients were associated with divergent RNA transcriptome profiles in peripheral immune cells compared with mild cases during the first weeks after disease onset. Protein-protein interaction analysis indicated that early-responding cytotoxic natural killer cells were associated with an effective clearance of the virus and a less severe outcome. This innate immune response was associated with the activation of select cytokine-cytokine receptor pathways and robust Th1/Th2 cell differentiation profiles. In contrast, severely ill patients exhibited a dysregulation between innate and adaptive responses affiliated with divergent Th1/Th2 profiles and negative outcomes. This knowledge forms the basis of clinical triage that may be used to preemptively detect high-risk patients before life-threatening outcomes ensue.

Using in vivo intact structure for system-wide quantitative analysis of changes in proteins

Mass spectrometry-based methods can provide a global expression profile and structural readout of proteins in complex systems. Preserving the in vivo conformation of proteins in their innate state is challenging during proteomic experiments. Here, we introduce a whole animal in vivo protein footprinting method using perfusion of reagents to add dimethyl labels to exposed lysine residues on intact proteins which provides information about protein conformation. When this approach is used to measure dynamic structural changes during Alzheimer's disease (AD) progression in a mouse model, we detect 433 proteins that undergo structural changes attributed to AD, independent of aging, across 7 tissues. We identify structural changes of co-expressed proteins and link the communities of these proteins to their biological functions. Our findings show that structural alterations of proteins precede changes in expression, thereby demonstrating the value of in vivo protein conformation measurement. Our method represents a strategy for untangling mechanisms of proteostasis dysfunction caused by protein misfolding. In vivo whole-animal footprinting should have broad applicability for discovering conformational changes in systemic diseases and for the design of therapeutic interventions.

New insight into the development of synpolydactyly caused by expansion of HOXD13 polyalanine based on weighted gene co-expression network analysis

BACKGROUND

Synpolydactyly (SPD) is mainly caused by mutations of polyalanine expansion (PAE) in the transcription factor gene HOXD13 and the involved cell types and signal pathway are still not clear possible pathways and single-cell expression characteristics of limb bud in HOXD13 PAE mice was analyzed in this study.

METHOD

We investigated a previous study of a mouse model with SPD and conducted weighted gene co-expression network analysis (WGCNA) using a single-cell RNA sequencing dataset from limb bud cells of SPD mouse model of HOXD13 + 7A heterozygote.

RESULTS

Analysis of WGCNA revealed that synpolydactyly-associated Hoxd13 PAEs alter the immune response and osteoclast differentiation, and enhance DNA replication. Bmp4, Hand2, Hoxd12, Lnp, Prrx1, Gmnn, and Cdc6 were found to play potentially key roles in synpolydactyly.

CONCLUSIONS

These findings evaluated the main genes related to SPD with PAE mutations in HOXD13 and advance our understanding of human limb development.

Integrative Analysis of Acupuncture Targets and Immune Genes in Diabetes, Diabetic Peripheral Neuropathy, and Adjunct Therapy of Cancer

Introduction

Acupuncture may help treat diabetes mellitus (DM), diabetic peripheral neuropathy (DPN), and adjunct therapy for cancer, but the biological mechanisms and immune-related genes involved are unclear; this study aims to clarify these aspects.

Methods

Comprehensive gene expression analysis revealed differentially expressed genes (DEGs) among DM, DPN, and control samples. Key genes from WGCNA were intersected with DEGs and acupuncture targets. Inflammatory responses, immune processes, signaling pathways, immune cell infiltration, and microRNA-gene interactions were studied. Hub immune-related genes' dysregulation was analyzed for copy number variation and gene methylation. A pan-cancer nomogram model was created to predict survival based on various factors, linking hub genes to cancer properties.

Results

Our analysis found 3,217 and 2,191 DEGs in DM/control and DPN/DM comparisons, respectively, and identified 1,830 potential acupuncture targets. We pinpointed 21 key genes in DM and 43 in DPN, involved in inflammatory responses, immune processes, CAMKK2, and cAMP signaling pathways. Distinct immune cell infiltration patterns, including M0 and M2 macrophages, neutrophils, and follicular helper T cells, were noted. Further analysis revealed microRNAs and TF genes interacting with immune hub genes in both conditions. Dysregulation of eight hub immune-related genes was linked to copy number variation and gene methylation, correlating with cancer prognosis. Co-occurrence of single nucleotide variations and oncogenic mutations was observed in these genes. The pan-cancer nomogram model showed strong prognostic capabilities, and a significant association was found between the eight genes and cancer properties like angiogenesis, EMT, and cell cycle progression.

Discussion

Our findings underscore the pivotal roles of MAPK3, IL1RN, SOD2, CTSD, ESR1, SLC1A1, NPY, and CCR2 in the immune response mediated by acupuncture in the context of DM, DPN, and adjunct therapy for cancer.

Experimental and in silico analysis of LINC01279 expression in tumor of patients with breast cancer

Breast cancer (BC) is characterized by the increase of malignant cells in the breast. The malignant cells begin in the lining of the breast milk glands or ducts (ductal epithelium). BC is the most frequent cancer in women, but it may also occur in males. Long non-coding RNAs (lncRNA) have been demonstrated to control the development and incidence of cancer. However, some lncRNAs experience potential changes in BC, but their role has not been well studied. LINC01279 is known as a valuable biomarker in gastric cancer but has not yet been studied in BC. Changes in LINC01279 expression levels in BC samples were investigated by microarray. Q-PCR was also used to evaluate the expression of LINC01279 in the tumor and normal adjacent samples of 30 BC patients. The LINC01279 co-expressed gene module was discovered using weighted gene correlation network analysis (WGCNA) on the relevant dataset. The top ten hub genes were determined using gene ontology (GO) functional enrichments on the co-expressed gene module. The results of the bioinformatics study showed an increase in LINC01279 expression levels (log2FC = 3.228749561, adj.P.Val = 1.69E - 12) in tumor samples compared to normal marginal tissue. Q-PCR results also showed a significant increase in LINC01279 expression (P-value = 0.0005) in tumor samples. WGCNA analysis identified that the black module is the LINC01279 co-expressed module, and functional annotation analysis of black module genes enriched in significant cancer-related pathways and processes, including cell growth and/or maintenance, regulation of immune response, regulation of cell proliferation, and epithelial-to-mesenchymal transition (EMT). Regarding the real-time PCR results, the analysis of expression patterns has illuminated a distinct association between the heightened expression levels of LINC01279, and the stages of cancer progression as well as the metastatic potential of tumors. However, intriguingly, our observations have failed to reveal any statistically significant correlations between the relative expression of LINC01279 and tumor grade classification, or the presence of ER, PR, and HER2 biomarkers. The present study could provide a new perspective on the molecular regulatory. Processes associated with BC pathogenic mechanisms are linked to the LINC01279, although further research is needed on the possible role of this lncRNA in BC.

Transcriptomic Insights into Hub Genes, Immune Infiltration, and Candidate Drugs in Erosive Esophagitis

Purpose

This study aimed to investigate gene expression profiles, identify potential hub genes, and predict drugs for patients with erosive esophagitis (EE). Despite its clinical significance, molecular-level exploration of this condition has been limited.

Patients and Methods

RNA sequencing was performed on clinical biopsy samples from eight EE patients and eight healthy controls. Integrated bioinformatic tools were then utilized to analyze the data, including functional enrichment analysis, protein-protein interaction network analysis, weighted gene co-expression network analysis, immune infiltration analysis, and identification of small-molecule compounds. Additionally, the expressions of the identified hub genes were assessed in clinical samples.

Results

A total of 2801 genes with differential expression were identified, including four potential hub genes: SOX9, SPP1, TIMP1, and TLR4. Moreover, the overexpression of these hub genes was verified in clinical samples. Analysis of Immune infiltration indicated an imbalance in the distribution of immune cell types in patients with EE. Correlation analysis between immune cells and hub genes unveiled noteworthy relationships. Specifically, SOX9 exhibited a negative correlation with CD8 T cells but a positive correlation with resting memory CD4 T cells. SPP1 displayed a positive correlation with naïve B cells, while TIMP1 exhibited a negative correlation with resting dendritic cells. Furthermore, the study identified ten small-molecule drugs with potential therapeutic effects for EE, including loreclezole and mercaptopurine.

Conclusion

This study provides valuable insights into the molecular understanding of EE, offering new perspectives on disease mechanisms. The findings may inspire further research leading to the development of novel treatment strategies for EE.

Oxytocin receptor controls distinct components of pair bonding and development in prairie voles

Oxytocin receptor (Oxtr) signaling influences complex social behaviors in diverse species, including social monogamy in prairie voles. How Oxtr regulates specific components of social attachment behaviors and the neural mechanisms mediating them remains unknown. Here, we examine prairie voles lacking Oxtr and demonstrate that pair bonding comprises distinct behavioral modules: the preference for a bonded partner, and the rejection of novel potential mates. Our longitudinal study of social attachment shows that Oxtr sex-specifically influences early interactions between novel partners facilitating the formation of partner preference. Additionally, Oxtr suppresses promiscuity towards novel potential mates following pair bonding, contributing to rejection. Oxtr function regulates coordinated patterns of gene expression in regions implicated in attachment behaviors and regulates the expression of oxytocin in the paraventricular nucleus of the hypothalamus, a principal source of oxytocin. Thus, Oxtr controls genetically separable components of pair bonding behaviors and coordinates development of the neural substrates of attachment.

Tirzepatide's role in targeting adipose tissue macrophages to reduce obesity-related inflammation and improve insulin resistance

BACKGROUND

Obesity and type 2 diabetes mellitus (T2DM) are significant global health challenges, with adipose tissue inflammation being a pivotal contributor to metabolic dysfunction. The involvement of adipose tissue macrophages (ATMs) in obesity-associated inflammation is well recognized, yet the therapeutic strategies specifically targeting ATM-mediated inflammation remain limited.

OBJECTIVE

This study aims to explore the effects of tirzepatide, a novel dual GLP-1 and GIP receptor agonist, on ATMs, adipose tissue inflammation, and insulin resistance in the context of obesity.

METHODS

Obese mouse models were established through high-fat diet feeding and subsequently treated with tirzepatide at a dose of 1.2 mg/kg twice weekly for 12 weeks. The study assessed the impact on ATM phenotype, inflammatory markers, and key metabolic indicators.

RESULTS

Tirzepatide treatment significantly mitigated the infiltration of pro-inflammatory M1 ATMs within adipose tissue and concurrently reduced levels of inflammatory cytokines, thereby enhancing insulin sensitivity. Tirzepatide demonstrated therapeutic efficacy through its modulation of the ERK signaling pathway and promotion of M1-type macrophage apoptosis.

CONCLUSION

Tirzepatide's potential as a therapeutic strategy for addressing metabolic diseases associated with obesity and T2DM by targeting ATM activity and mitigating obesity-associated inflammation.

Integrative 3D genomics with multi-omics analysis and functional validation of genetic regulatory mechanisms of abdominal fat deposition in chickens

Chickens are the most abundant agricultural animals globally, with controlling abdominal fat deposition being a key objective in poultry breeding. While GWAS can identify genetic variants associated with abdominal fat deposition, the precise roles and mechanisms of these variants remain largely unclear. Here, we use male chickens from two lines divergently selected for abdominal fat deposition as experimental models. Through the integration of genomic, epigenomic, 3D genomic, and transcriptomic data, we build a comprehensive chromatin 3D regulatory network map to identify the genetic regulatory mechanisms that influence abdominal fat deposition in chickens. Notably, we find that the rs734209466 variant functions as an allele-specific enhancer, remotely enhancing the transcription of IGFBP2 and IGFBP5 by the binding transcription factor IRF4. This interaction influences the differentiation and proliferation of preadipocytes, which ultimately affects phenotype. This work presents a detailed genetic regulatory map for chicken abdominal fat deposition, offering molecular targets for selective breeding.

Dynamic Landscapes of Long Noncoding RNAs During Early Root Development and Differentiation in Glycine max and Glycine soja

Soybean (Glycine max) is an important crop for its nutritional value. Its wild relative, Glycine soja, provides a valuable genetic resource for improving soybean productivity. Root development and differentiation are essential for soybean plants to take up water and nutrients, store energy and anchor themselves. Long noncoding RNAs (lncRNAs) have been reported to play critical roles in various biological processes. However, the spatiotemporal landscape of lncRNAs during early root development and differentiation in soybeans is scarcely characterized. Using RNA sequencing and transcriptome assembly, we identified 1578 lncRNAs in G. max and 1454 in G. soja, spanning various root portions and time points. Differential expression analysis revealed 82 and 69 lncRNAs exhibiting spatiotemporally differential expression patterns in G. max and G. soja, respectively, indicating their involvement in the early stage of root architecture formation. By elucidating multiple competitive endogenous RNA (ceRNA) networks involving lncRNAs, microRNAs and protein-coding RNAs, we unveiled intricate regulatory mechanisms of lncRNA in early root development and differentiation. Our efforts significantly expand the transcriptome annotations of soybeans, unravel the dynamic landscapes of lncRNAs during early root development and differentiation, and provide valuable resources into the field of soybean root research.

Exploring Potential Biomarkers and Molecular Mechanisms of Cutaneous Squamous Cell Carcinoma Based on Bioinformatics

Purpose

Cutaneous squamous cell carcinoma (cSCC) ranks as the second most common malignancy in clinical practice and poses a significant threat to public health due to its high malignancy. In this study, we aimed to explore potential biomarkers and molecular mechanisms of cSCC.

Methods

Differentially expressed genes (DEGs) from GSE66359 and GSE117247 datasets were identified using R software. We conducted enrichment analyses and screened hub genes through protein-protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA). To assess the diagnostic performance of these genes, we generated ROC curves using both internal and external datasets (GSE45164) and validated the expression levels of these genes in cSCC tissues through immunohistochemistry. Subsequently, we predicted the target miRNAs and lncRNAs for hub genes using online databases and constructed competing endogenous RNA (ceRNA) networks.

Results

In total, we identified 505 upregulated DEGs and 522 downregulated DEGs. Through PPI and WGCNA analyses, we identified four hub genes exhibiting robust diagnostic performance in internal and external datasets (AUC > 0.9) and selected three previously unreported genes for further analysis. Immunohistochemistry demonstrated significantly elevated CCNA2, CCNB2, and UBE2C expression in cSCC tissues compared to normal skin tissues. Finally, we constructed three ceRNA networks, namely NEAT1/H19-hsa-miR-148a-3p-CCNA2 and NEAT1-hsa-miR-140-3p-UBE2C.

Conclusion

In conclusion, we have identified CCNA2, CCNB2, and UBE2C as novel biomarkers for cSCC, and the NEAT1/H19-hsa-miR-148a-3p-CCNA2 and NEAT1-hsa-miR-140-3p-UBE2C ceRNA networks may represent molecular mechanisms under-lying cSCC progression. The findings of this study offer new diagnostic and therapeutic options for cSCC patients.

Unveiling the genetic link and pathogenesis between psoriasis and IgA nephropathy based on Mendelian randomization and transcriptome data analyses

It has been reported that many people with psoriasis have been diagnosed with secondary IgA nephropathy (IgAN). However, the mechanisms behind the association between psoriasis and IgAN have not been well clarified. The connection between psoriasis and IgAN deserves deeper exploration. Mendelian randomization (MR) analysis would be employed to explore the link of causality between IgAN and psoriasis, psoriasis vulgaris, other and unspecified psoriasis, guttate psoriasis, and arthropathic psoriasis. Transcriptomic analyses were carried out against the Gene Expression Omnibus databases. We identified crosstalk genes through the analysis of Differentially expressed genes and weight gene co-expression network analysis. Functional annotations were enriched for these crosstalk genes. Subsequently, we established a protein-protein interaction network, and candidate genes would be discovered through the utilization of the MCODE and CytoHubba plug-in applications. Lastly, the predictive efficacy of these genes was examined via creating receiver operating characteristic curves. The MR analysis suggested that psoriasis vulgaris patients were at a higher risk for IgAN. [OR = 1.040, 95%CI (1.005,1.076), p = 0.026 < 0.05]. Additionally, arthropathic psoriasis may augment the incidence of IgAN [OR = 1.081, 95%CI (1.040-1.124), p < 0.01] in the European population. Through the analysis of DEGs and WGCNA, we identified 12 significant genes (NETO2, RRM2, SLAMF7, GBP1, KIF20A, CCL4, MMP1, IL1β, NDC80, CXCL9, C15orf48, GSTA3), which may be potential crosstalk genes between the two diseases. Then, the functional annotation results indicated that the crosstalk genes seemed primarily involved in immune and inflammatory responses. By establishing the PPI network, we further discovered that CXCL9, IL1β, CCL4, and MMP1 play a vital part in psoriasis and IgAN, and all have good diagnostic values. Our MR analysis provided evidence that genetic vulnerability to IgAN may be associated with an elevated risk of psoriasis vulgaris and arthropathic psoriasis respectively among Europeans. Doctors should be aware of these associations when patients with psoriasis present with renal dysfunction, especially those with psoriasis vulgaris and arthropathic psoriasis. Chronic inflammation, drug effects, and immunity may contribute to the generation and development of both diseases. IL1β, CXCL9, CCL4, and MMP1 may be core biomarkers for psoriasis and IgAN.

Functional investigation and two-sample Mendelian randomization study of primary biliary cholangitis hub genes

BACKGROUND

The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis (PBC) and finding relevant biomarkers for diagnosis and therapeutic evaluation.

AIM

To determine PBC-associated hub genes and assess their clinical utility for disease prediction.

METHODS

PBC expression data were obtained from the Gene Expression Omnibus database. Overlapping genes from differential expression analysis and weighted gene co-expression network analysis (WGCNA) were identified as key genes for PBC. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes. Hub genes were identified in protein-protein interaction (PPI) networks using the Degree algorithm in Cytoscape software. The relationship between hub genes and immune cells was investigated. Finally, a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.

RESULTS

We identified 71 overlapping key genes using differential expression analysis and WGCNA. These genes were primarily enriched in pathways related to cytokine-cytokine receptor interaction, and Th1, Th2, and Th17 cell differentiation. We utilized Cytoscape software and identified five hub genes (CD247, IL10, CCL5, CCL3, and STAT3) in PPI networks. These hub genes showed a strong correlation with immune cell infiltration in PBC. However, inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.

CONCLUSION

Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment, thereby offering significant clinical utility.

Proteomic analysis of extracellular vesicles derived from canine mammary tumour cell lines identifies protein signatures specific for disease state

BACKGROUND

Canine mammary tumours (CMT) are among the most common types of tumours in female dogs. Diagnosis currently requires invasive tissue biopsies and histological analysis. Tumour cells shed extracellular vesicles (EVs) containing RNAs and proteins with potential for liquid biopsy diagnostics. We aimed to identify CMT subtype-specific proteome profiles by comparing the proteomes of EVs isolated from epithelial cell lines derived from morphologically normal canine mammary tissue, adenomas, and carcinomas.

METHODS

Whole-cell protein lysates (WCLs) and EV-lysates were obtained from five canine mammary cell lines: MTH53A (non-neoplastic); ZMTH3 (adenoma); MTH52C (simple carcinoma); 1305, DT1406TB (complex carcinoma); and their proteins identified by LC-MS/MS analyses. Gene Ontology analysis was performed on differentially abundant proteins from each group to identify up- and down-regulated biological processes. To establish CMT subtype-specific proteomic profiles, weighted gene correlation network analysis (WGCNA) was carried out.

RESULTS

WCL and EVs displayed distinct protein abundance signatures while still showing the same increase in adhesion, migration, and motility-related proteins in carcinoma-derived cell lines, and of RNA processing and RNA splicing factors in the adenoma cell line. WGCNA identified CMT stage-specific co-abundant EV proteins, allowing the identification of adenoma and carcinoma EV signatures not seen in WCLs.

CONCLUSIONS

EVs from CMT cell lines exhibit distinct protein profiles reflecting malignancy state, allowing us to identify potential biomarkers for canine mammary carcinomas, such as biglycan. Our dataset could therefore potentially serve as a basis for the development of a less invasive clinical diagnostic tool for the characterisation of CMT.

Plasma proteomic profiles reveal proteins and three characteristic patterns associated with osteoporosis: A prospective cohort study

INTRODUCTION

Exploration of plasma proteins associated with osteoporosis can offer insights into its pathological development, identify novel biomarkers for screening high-risk populations, and facilitate the discovery of effective therapeutic targets.

OBJECTIVES

The present study aimed to identify potential proteins associated with osteoporosis and to explore the underlying mechanisms from a proteomic perspective.

METHODS

The study included 42,325 participants without osteoporosis in the UK Biobank (UKB), of whom 1,477 developed osteoporosis during the follow-up. We used Cox regression and Mendelian randomization analysis to examine the association between plasma proteins and osteoporosis. Machine learning was utilized to explore proteins with strong predictive power for osteoporosis risk.

RESULTS

Of 2,919 plasma proteins, we identified 134 significantly associated with osteoporosis, with sclerostin (SOST), adiponectin (ADIPOQ), and creatine kinase B-type (CKB) exhibiting strong associations. Twelve of these proteins showed significant associations with bone mineral density (BMD) T-score at the femoral neck, lumbar spine, and total body. Mendelian randomization further supported causal relationships between 17 plasma proteins and osteoporosis. Moreover, follitropin subunit beta (FSHB), SOST, and ADIPOQ demonstrated high importance in predictive modeling. Utilizing a predictive model built with 10 proteins, we achieved relatively accurate prediction of osteoporosis onset up to 5 years in advance (AUC = 0.803). Finally, we identified three osteoporosis-related protein modules associated with immunity, lipid metabolism, and follicle-stimulating hormone (FSH) regulation from a network perspective, elucidating their mediating roles between various risk factors (smoking, sleep, physical activity, polygenic risk score (PRS), and menopause) and osteoporosis.

CONCLUSION

We identified several proteins associated with osteoporosis and highlighted the role of plasma proteins in influencing its progression through three primary pathways: immunity, lipid metabolism, and FSH regulation. This provides further insights into the distinct molecular patterns and pathogenesis of bone loss and may contribute to strengthening early diagnosis and long-term monitoring of the condition.

De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression

STAT3 gain-of-function syndrome, characterized by early-onset autoimmunity and primary immune regulatory disorder, remains poorly understood in terms of its immunological mechanisms. We employed whole-genome sequencing of familial trios to elucidate the pivotal role of de novo mutations in genetic diseases. We identified 37 high-risk pathogenic loci affecting 23 genes, including a novel STAT3 c.508G>A mutation. We also observed significant down-regulation of pathogenic genes in affected individuals, potentially associated with inflammatory responses regulated by PTPN14 via miR378c. These findings enhance our understanding of the pathogenesis of STAT3 gain-of-function syndrome and suggest potential therapeutic strategies. Notably, combined JAK inhibitors and IL-6R antagonists may offer promising treatment avenues for mitigating the severity of STAT3 gain-of-function syndrome.

Integrative transcriptomic profiling uncovers immune and functional responses to bisphenol a across multiple tissues in male mice

Bisphenol A (BPA), an endocrine-disrupting substance commonly found in plastics and receipts, is associated with adverse effects, including endocrine disorders, reduced fertility, and metabolic issues. To gain insights into its effects on biological systems, we observed the adverse effects of BPA in male Institute of Cancer Research (ICR) mice exposed to BPA at the lowest observed adverse effect level for 6 weeks, in comparison with the control groups. We constructed a comprehensive transcriptome profile using 20 different tissues to analyze the changes in the whole-body systems. This involved employing differential gene expression, tissue-specific gene, and gene co-expression network analyses. The study revealed that BPA exposure led to significant differences in the transcriptome in the thymus, suggesting activation of T-cell differentiation and maturation in response to BPA treatment. Furthermore, various tissues exhibited immune response activation, potentially due to the migration of immune cells from the thymus. BPA exposure also caused immune-related functional changes in the colon, liver, and kidney, as well as abnormal signaling responses in the sperm. The transcriptome analysis serves as a valuable resource for understanding the functional impact of BPA, providing profound insights into the effects of BPA exposure and emphasizing the need for further research on potential associated health risks.

Age, sex, and cell type-resolved hypothalamic gene expression across the pubertal transition in mice

BACKGROUND

The hypothalamus plays a central role in regulating puberty. However, our knowledge of the postnatal gene regulatory networks that control the pubertal transition in males and females is incomplete. Here, we investigate the age-, sex- and cell-type-specific gene regulation in the hypothalamus across the pubertal transition.

METHODS

We used RNA-seq to profile hypothalamic gene expression in male and female mice at five time points spanning the onset of puberty (postnatal days (PD) 12, 22, 27, 32, and 37). By combining this data with hypothalamic single nuclei RNA-seq data from pre- and postpubertal mice, we assigned gene expression changes to their most likely cell types of origin. In our colony, pubertal onset occurs earlier in male mice, allowing us to focus on genes whose expression is dynamic across ages and offset between sexes, and to explore the bases of sex effects.

RESULTS

Our age-by-sex pattern of expression enriched for biological pathways involved hormone production, neuronal activation, and glial maturation. Additionally, we inferred a robust expansion of oligodendrocytes precursor cells into mature oligodendrocytes spanning the prepubertal (PD12) to peri-pubertal (PD27) timepoints. Using spatial transcriptomic data from postpubertal mice, we observed the lateral hypothalamic area and zona incerta were the most oligodendrocyte-rich regions and that these cells expressed genes known to be involved in pubertal regulation.

CONCLUSION

Together, by incorporating multiple biological timepoints and using sex as a variable, we identified gene and cell-type changes that may participate in orchestrating the pubertal transition and provided a resource for future studies of postnatal hypothalamic gene regulation.

Gene co-expression analysis reveals conserved and distinct gene networks between resistant and susceptible Lens ervoides challenged by hemibiotrophic and necrotrophic pathogens

As field crops are likely to be challenged by multiple pathogens during their development, the investigation of broad-spectrum resistance in the host is of great interest for crop genetic enhancement. In this study, we attempted to address this question by adopting a weighed gene co-expression approach to study the temporal transcriptome dynamics of resistant and susceptible recombinant inbred lines (RILs) derived from an intraspecific Len ervoides cross during the infection process with either the necrotrophic pathogens Ascochyta lentis or Stemphylium botryosum, or the hemibiotrophic pathogen Colletotrichum lentis. By comparing networks of resistant and susceptible RILs, seven network module pairs were found to possess high correlation coefficients (R > 0.70) and large number of overlapping genes (n > 100). The conserved co-regulation of genes in these network module pairs were involved in plant cell wall synthesis, cell division, cytoskeleton organization, and protein ubiquitin related processes and appeared to be common disease responses against these pathogens. On the other hand, we also identified eight modules with low correlation between resistance and susceptibility networks. Among those, a stronger gene co-expression in R-genes and small RNA processes in the resistant hosts may be enhancing L. ervoides resistance against A. lentis, C. lentis, and S. botryosum, whereas the higher level of synergistic regulation in the synthesis of arginine and glutamine and phospholipid and glycerophospholipids in the susceptible hosts may contribute to increased susceptibility in L. ervoides.

Transcriptome analysis reveals regulatory mechanism of postharvest softening in kiwiberry

BACKGROUND

Kiwiberry is an emerging edible fruit with market potential owing to its advantages of small size, thin and hairless skin, and sweet taste. However, kiwiberry is highly susceptible to softening after harvest, which poses a challenge for storage and transport. To reveal the underlying cause of kiwiberry softening, it is essential to investigate the characteristics of postharvest fruit and the molecular mechanisms that affect changes in fruit firmness.

RESULTS

Morphological observations and analysis of physical parameters showed that the skin of kiwiberry did not change markedly from the 1st to the 7th day after harvest, while the colour of the inner pericarp gradually turned yellow. By the 9th day of room temperature storage, the kiwiberries began to rot. The hardness decreased rapidly from the 1st to the 5th day postharvest, reaching the low level on the 5th day. The starch and pectin contents of kiwiberry showed a downward trend with increasing storage time. Transcriptome sequencing and weighted gene co-expression network analysis identified 29 key genes associated with the changes in the hardness of kiwiberry after harvest. Gene Ontology enrichment analysis indicated that these 29 genes are mainly involved in pectin metabolism, starch synthesis, starch decomposition, and starch metabolism. In addition, three transcription factors, AGL31, HAT14, and ALC, were identified to be strongly positively correlated with the 29 genes that affect the hardness changes of kiwiberry after harvest, and 28 of the 29 key genes were predicted to be regulated by HAT14.

CONCLUSIONS

These results reveal the changes in morphological characteristics and physiological indicators during the postharvest ripening and softening of kiwiberry stored under room temperature conditions. Transcriptome analysis identified 29 key genes and three transcription factors that affect the firmness changes of postharvest kiwiberry. The results of this study thus provide insight into the transcriptional regulatory mechanism of kiwiberry softening during storage to improve the postharvest quality.

The YTHDF Proteins Shape the Brain Gene Signatures of Alzheimer's Disease

The gene signatures of Alzheimer's Disease (AD) brains reflect an output of a complex interplay of genetic, epigenetic, epi-transcriptomic, and post-transcriptional regulations. To identify the most significant factor that shapes the AD brain signature, we developed a machine learning model (DEcode-tree) to integrate cellular and molecular factors explaining differential gene expression in AD. Our model indicates that YTHDF proteins, the canonical readers of N6-methyladenosine RNA modification (m6A), are the most influential predictors of the AD brain signature. We then show that protein modules containing YTHDFs are downregulated in human AD brains, and knocking out YTHDFs in iPSC-derived neural cells recapitulates the AD brain gene signature in vitro . Furthermore, eCLIP-seq analysis revealed that YTHDF proteins influence AD signatures through both m6A-dependent and independent pathways. These results indicate the central role of YTHDF proteins in shaping the gene signature of AD brains.

Sustained carbon import supports sugar accumulation and anthocyanin biosynthesis during fruit development and ripening in blueberry (Vaccinium ashei)

Fruit ripening is a highly coordinated process involving molecular and biochemical changes that collectively determine fruit quality. The underlying metabolic programs and their transitions leading to fruit ripening remain largely under-characterized in blueberry (Vaccinium sp.), which exhibits atypical climacteric behavior. In this study, we focused on sugar, acid and anthocyanin metabolism in two rabbiteye blueberry cultivars, Premier and Powderblue, during fruit development and ripening. Concentrations of the three major sugars, sucrose (Suc), glucose (Glc), and fructose (Fru) increased steadily during fruit development leading up to ripening, and increased dramatically by around 2-fold in 'Premier' and 2- to 3-fold in 'Powderblue' during the final stage of fruit ripening. Starch concentration was very low throughout fruit development in both cultivars indicating that it does not serve the role of a major transitory carbon (C) storage form in blueberry fruit. Together, these patterns indicate continued import of C, likely in the form of Suc, throughout blueberry fruit development. Concentrations of the predominant acids, malate and quinate, decreased during ripening, and may contribute to increased shikimate biosynthesis which, in-turn, allows for downstream phenylpropanoid metabolism leading to anthocyanin synthesis. Consistently, anthocyanin concentrations were highest in fully ripened blue fruit. Weighted gene co-expression network analysis (WGCNA) was performed using a 'Powderblue' fruit ripening transcriptome and targeted fruit metabolite concentration data. A 'dark turquoise' module positively correlated with sugars and anthocyanins, and negatively correlated with acids (malate, quinate), was identified. Gene Ontology (GO) enrichment analysis of this module identified transcripts related to sugar, acid, and phenylpropanoid metabolism pathways. Among these, increased transcript abundance of a VACUOLAR INVERTASE during ripening was consistent with sugar storage in the vacuole. In general, transcript abundance of the glycolysis pathway genes was upregulated during ripening. The transcript abundance of PHOSPHOENOLPYRUVATE (PEP) CARBOXYKINASE increased during fruit ripening and was negatively correlated with malate concentration, suggesting increased malate conversion to PEP, which supports anthocyanin production during fruit ripening. This was further supported by the co-upregulation of several anthocyanin biosynthesis-related genes. Together, this study provides insights into important metabolic programs, and their underlying gene expression patterns during fruit development and ripening in blueberry.

Screening of hub genes for sepsis-induced myopathy by weighted gene co-expression network analysis and protein-protein interaction network construction

Sepsis-induced myopathy is one of the serious complications of sepsis, which severely affects the respiratory and peripheral motor systems of patients, reduces their quality of life, and jeopardizes their lives, as evidenced by muscle atrophy, loss of strength, and impaired regeneration after injury. The pathogenesis of sepsis-induced myopathy is complex, mainly including cytokine action, enhances free radical production in muscle, increases muscle protein hydrolysis, and decreases skeletal muscle protein synthesis, etc. The above mechanisms have been demonstrated in existing studies. However, it is still unclear how the overall pattern of gene co-expression affects the pathological process of sepsis-induced myopathy. Therefore, we intend to identify hub genes and signaling pathways. Weighted gene co-expression network analysis was our main approach to study gene expression profiles: skeletal muscle transcriptome in ICU patients with sepsis-induced multi-organ failure (GSE13205). After data pre-processing, about 15,181 genes were used to identify 13 co-expression modules. Then, 16 genes (FEM1B, KLHDC3, GPX3, NIFK, GNL2, EBNA1BP2, PES1, FBP2, PFKP, BYSL, HEATR1, WDR75, TBL3, and WDR43) were selected as the hub genes including 3 up-regulated genes and 13 down-regulated genes. Then, Gene Set Enrichment Analysis was performed to show that the hub genes were closely associated with skeletal muscle dysfunction, necrotic and apoptotic skeletal myoblasts, and apoptosis in sepsis-induced myopathy. Overall, 16 candidate biomarkers were certified as reliable features for more in-depth exploration of sepsis-induced myopathy in basic and clinical studies.

Phosphoproteomic subtyping of gastric cancer reveals dynamic transformation with chemotherapy and guides targeted cancer treatment

There are only a few effective molecular targeted agents for advanced unresectable or recurrent advanced gastric cancer (AGC), which has a poor prognosis with a median survival time of less than 14 months. Focusing on phosphorylation signaling in cancer cells, we have been developing deep phosphoproteome analysis from minute endoscopic biopsy specimens frozen within 20 s of collection. Phosphoproteomic analysis of 127 fresh-frozen endoscopic biopsy samples from untreated patients with AGC revealed three subtypes reflecting different cellular signaling statuses. Subsequent serial biopsy analysis has revealed the dynamic mesenchymal transitions within cancer cells, along with the concomitant rewiring of the kinome network, ultimately resulting in the conversion to the epithelial-mesenchymal transition (EMT) subtype throughout treatment. We present our investigation of intracellular signaling related to the EMT in gastric cancer and propose therapeutic approaches targeting AXL. This study also provides a wealth of resources for the future development of treatments and biomarkers for AGC.

Stage-specific expression patterns and co-targeting relationships among miRNAs in the developing mouse cerebral cortex

microRNAs are crucial regulators of brain development, however, miRNA regulatory networks are not sufficiently well characterized. By performing small RNA-seq of the mouse embryonic cortex at E14, E17, and P0 as well as in neural progenitor cells and neurons, here we detected clusters of miRNAs that were co-regulated at distinct developmental stages. miRNAs such as miR-92a/b acted as hubs during early, and miR-124 and miR-137 during late neurogenesis. Notably, validated targets of P0 hub miRNAs were enriched for downregulated genes related to stem cell proliferation, negative regulation of neuronal differentiation and RNA splicing, among others, suggesting that miRNAs are particularly important for modulating transcriptional programs of crucial factors that guide the switch to neuronal differentiation. As most genes contain binding sites for more than one miRNA, we furthermore constructed a co-targeting network where numerous miRNAs shared more targets than expected by chance. Using luciferase reporter assays, we demonstrated that simultaneous binding of miRNA pairs to neurodevelopmentally relevant genes exerted an enhanced transcriptional silencing effect compared to single miRNAs. Taken together, we provide a comprehensive resource of miRNA longitudinal expression changes during murine corticogenesis. Furthermore, we highlight several potential mechanisms through which miRNA regulatory networks can shape embryonic brain development.

Gene regulatory network structure informs the distribution of perturbation effects

Gene regulatory networks (GRNs) govern many core developmental and biological processes underlying human complex traits. Even with broad-scale efforts to characterize the effects of molecular perturbations and interpret gene coexpression, it remains challenging to infer the architecture of gene regulation in a precise and efficient manner. Key properties of GRNs, like hierarchical structure, modular organization, and sparsity, provide both challenges and opportunities for this objective. Here, we seek to better understand properties of GRNs using a new approach to simulate their structure and model their function. We produce realistic network structures with a novel generating algorithm based on insights from small-world network theory, and we model gene expression regulation using stochastic differential equations formulated to accommodate modeling molecular perturbations. With these tools, we systematically describe the effects of gene knockouts within and across GRNs, finding a subset of networks that recapitulate features of a recent genome-scale perturbation study. With deeper analysis of these exemplar networks, we consider future avenues to map the architecture of gene expression regulation using data from cells in perturbed and unperturbed states, finding that while perturbation data are critical to discover specific regulatory interactions, data from unperturbed cells may be sufficient to reveal regulatory programs.