CNet: a multi-omics approach to detecting clinically associated, combinatory genomic signatures

Differential gene expression profiling implicates altered network development in rat postnatal day 4 cortex following 4-Methylimidazole (4-MeI) induced maternal seizures

Compromised maternal health leading to maternal seizures can have adverse effects on the healthy development of offspring. This may be the result of inflammation, hypoxia-ischemia, and altered GABA signaling. The current study examined cortical tissue from F2b (2nd litter of the 2nd generation) postnatal day 4 (PND4) offspring of female Harlan SD rats chronically exposed to the seizuregenic compound, 4-Methylimidazole (0, 750, or 2500 ppm 4-MeI). Maternal seizures were evident only at 2500 ppm 4-MeI. GABA related gene expression as examined by qRT-PCR and whole genome microarray showed no indication of disrupted GABA or glutamatergic signaling. Canonical pathway hierarchical clustering and multi-omics combinatory genomic (CNet) plots of differentially expressed genes (DEG) showed alterations in genes associated with regulatory processes of cell development including neuronal differentiation and synaptogenesis. Functional enrichment analysis showed a similarity of cellular processes across the two exposure groups however, the genes comprising each cluster were primarily unique rather than shared and often showed different directionality. A dose-related induction of cytokine signaling was indicated however, pathways associated with individual cytokine signaling were not elevated, suggesting an alternative involvement of cytokine signaling. Pathways related to growth process and cell signaling showed a negative activation supporting an interpretation of disruption or delay in developmental processes at the 2500 ppm 4-MeI exposure level with maternal seizures. Thus, while GABA signaling was not altered as has been observed with maternal seizures, the pattern of DEG suggested a potential for alteration in neuronal network formation.

Single-cell transcriptomic analysis reveals crucial oncogenic signatures and its associative cell types involved in gastric cancer

The intricate association of oncogenic markers negatively impacts accurate gastric cancer diagnosis and leads to the proliferation of mortality rate. Molecular heterogeneity is inevitable in determining gastric cancer's progression state with multiple cell types involved. Identification of pathogenic gene signatures is imperative to understand the disease's etiology. This study demonstrates a systematic approach to identifying oncogenic gastric cancer genes linked with different cell types. The raw counts of adjacent normal and gastric cancer samples are subjected to a quality control step. The dimensionality reduction and multidimensional clustering are performed using Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) techniques. The adjacent normal and gastric cancer sample cell clusters are annotated with the Human Primary Cell Atlas database using the "SingleR." Cellular state transition between the distinct groups is characterized using trajectory analysis. The ligand-receptor interaction between Vascular Endothelial Growth Factor (VEGF) and cell clusters unveils crucial molecular pathways in gastric cancer progression. Chondrocytes, Smooth muscle cells, and fibroblast cell clusters contain genes contributing to poor survival rates based on hazard ratio during survival analysis. The GC-related oncogenic signatures are isolated by comparing the gene set with the DisGeNET database. Twelve gastric cancer biomarkers (SPARC, KLF5, HLA-DRB1, IGFBP3, TIMP3, LGALS1, IGFBP6, COL18A1, F3, COL4A1, PDGFRB, COL5A2) are linked with gastric cancer and further validated through gene set enrichment analysis. Drug-gene interaction found PDGFRB, interacting with various anti-cancer drugs, as a potential inhibitor for gastric cancer. Further investigations on these molecular signatures will assist the development of precision therapeutics, promising longevity among gastric cancer patients.

Translational Bioinformatics for Human Reproductive Biology Research: Examples, Opportunities and Challenges for a Future Reproductive Medicine

Since 1978, with the first IVF (in vitro fertilization) baby birth in Manchester (England), more than eight million IVF babies have been born throughout the world, and many new techniques and discoveries have emerged in reproductive medicine. To summarize the modern technology and progress in reproductive medicine, all scientific papers related to reproductive medicine, especially papers related to reproductive translational medicine, were fully searched, manually curated and reviewed. Results indicated whether male reproductive medicine or female reproductive medicine all have made significant progress, and their markers have experienced the progress from karyotype analysis to single-cell omics. However, due to the lack of comprehensive databases, especially databases collecting risk exposures, disease markers and models, prevention drugs and effective treatment methods, the application of the latest precision medicine technologies and methods in reproductive medicine is limited.

scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies

BACKGROUND

The rapid accumulation of single-cell RNA sequencing (scRNA-seq) data presents unique opportunities to decode the genetically mediated cell-type specificity in complex diseases. Here, we develop a new method, scGWAS, which effectively leverages scRNA-seq data to achieve two goals: (1) to infer the cell types in which the disease-associated genes manifest and (2) to construct cellular modules which imply disease-specific activation of different processes.

RESULTS

scGWAS only utilizes the average gene expression for each cell type followed by virtual search processes to construct the null distributions of module scores, making it scalable to large scRNA-seq datasets. We demonstrated scGWAS in 40 genome-wide association studies (GWAS) datasets (average sample size N ≈ 154,000) using 18 scRNA-seq datasets from nine major human/mouse tissues (totaling 1.08 million cells) and identified 2533 trait and cell-type associations, each with significant modules for further investigation. The module genes were validated using disease or clinically annotated references from ClinVar, OMIM, and pLI variants.

CONCLUSIONS

We showed that the trait-cell type associations identified by scGWAS, while generally constrained to trait-tissue associations, could recapitulate many well-studied relationships and also reveal novel relationships, providing insights into the unsolved trait-tissue associations. Moreover, in each specific cell type, the associations with different traits were often mediated by different sets of risk genes, implying disease-specific activation of driving processes. In summary, scGWAS is a powerful tool for exploring the genetic basis of complex diseases at the cell type level using single-cell expression data.

Assessing Gq-GPCR-induced human astrocyte reactivity using bioengineered neural organoids

Astrocyte reactivity can directly modulate nervous system function and immune responses during disease and injury. However, the consequence of human astrocyte reactivity in response to specific contexts and within neural networks is obscure. Here, we devised a straightforward bioengineered neural organoid culture approach entailing transcription factor-driven direct differentiation of neurons and astrocytes from human pluripotent stem cells combined with genetically encoded tools for dual cell-selective activation. This strategy revealed that Gq-GPCR activation via chemogenetics in astrocytes promotes a rise in intracellular calcium followed by induction of immediate early genes and thrombospondin 1. However, astrocytes also undergo NF-κB nuclear translocation and secretion of inflammatory proteins, correlating with a decreased evoked firing rate of cocultured optogenetic neurons in suboptimal conditions, without overt neurotoxicity. Altogether, this study clarifies the intrinsic reactivity of human astrocytes in response to targeting GPCRs and delivers a bioengineered approach for organoid-based disease modeling and preclinical drug testing.

Distinct effect of prenatal and postnatal brain expression across 20 brain disorders and anthropometric social traits: a systematic study of spatiotemporal modularity

Different spatiotemporal abnormalities have been implicated in different neuropsychiatric disorders and anthropometric social traits, yet an investigation in the temporal network modularity with brain tissue transcriptomics has been lacking. We developed a supervised network approach to investigate the genome-wide association study (GWAS) results in the spatial and temporal contexts and demonstrated it in 20 brain disorders and anthropometric social traits. BrainSpan transcriptome profiles were used to discover significant modules enriched with trait susceptibility genes in a developmental stage-stratified manner. We investigated whether, and in which developmental stages, GWAS-implicated genes are coordinately expressed in brain transcriptome. We identified significant network modules for each disorder and trait at different developmental stages, providing a systematic view of network modularity at specific developmental stages for a myriad of brain disorders and traits. Specifically, we observed a strong pattern of the fetal origin for most psychiatric disorders and traits [such as schizophrenia (SCZ), bipolar disorder, obsessive-compulsive disorder and neuroticism], whereas increased co-expression activities of genes were more strongly associated with neurological diseases [such as Alzheimer's disease (AD) and amyotrophic lateral sclerosis] and anthropometric traits (such as college completion, education and subjective well-being) in postnatal brains. Further analyses revealed enriched cell types and functional features that were supported and corroborated prior knowledge in specific brain disorders, such as clathrin-mediated endocytosis in AD, myelin sheath in multiple sclerosis and regulation of synaptic plasticity in both college completion and education. Our study provides a landscape view of the spatiotemporal features in a myriad of brain-related disorders and traits.