PancrESS - a meta-analysis resource for understanding cell-type specific expression in the human pancreas.

BACKGROUND: The human pancreas is composed of specialized cell types producing hormones and enzymes critical to human health. These specialized functions are the result of cell type-specific transcriptional programs which manifest in cell-specific gene expression. Understanding these programs is essential to developing therapies for pancreatic disorders. Transcription in the human pancreas has been widely studied by single-cell RNA technologies, however the diversity of protocols and analysis methods hinders their interpretability in the aggregate. RESULTS: In this work, we perform a meta-analysis of pancreatic single-cell RNA sequencing data. We present a database for reference transcriptome abundances and cell-type specificity metrics. This database facilitates the identification and definition of marker genes within the pancreas. Additionally, we introduce a versatile tool which is freely available as an R package, and should permit integration into existing workflows. Our tool accepts count data files generated by widely-used single-cell gene expression platforms in their original format, eliminating an additional pre-formatting step. Although we designed it to calculate expression specificity of pancreas cell types, our tool is agnostic to the biological source of count data, extending its applicability to other biological systems. CONCLUSIONS: Our findings enhance the current understanding of expression specificity within the pancreas, surpassing previous work in terms of scope and detail. Furthermore, our database and tool enable researchers to perform similar calculations in diverse biological systems, expanding the applicability of marker gene identification and facilitating comparative analyses.

Tissue Expression Difference between mRNAs and lncRNAs.

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) are two main subgroups of RNAs participating in transcription regulation. With the development of next generation sequencing, increasing lncRNAs are identified. Many hidden functions of lncRNAs are also revealed. However, the differences in lncRNAs and mRNAs are still unclear. For example, we need to determine whether lncRNAs have stronger tissue specificity than mRNAs and which tissues have more lncRNAs expressed. To investigate such tissue expression difference between mRNAs and lncRNAs, we encoded 9339 lncRNAs and 14,294 mRNAs with 71 expression features, including 69 maximum expression features for 69 types of cells, one feature for the maximum expression in all cells, and one expression specificity feature that was measured as Chao-Shen-corrected Shannon's entropy. With advanced feature selection methods, such as maximum relevance minimum redundancy, incremental feature selection methods, and random forest algorithm, 13 features presented the dissimilarity of lncRNAs and mRNAs. The 11 cell subtype features indicated which cell types of the lncRNAs and mRNAs had the largest expression difference. Such cell subtypes may be the potential cell models for lncRNA identification and function investigation. The expression specificity feature suggested that the cell types to express mRNAs and lncRNAs were different. The maximum expression feature suggested that the maximum expression levels of mRNAs and lncRNAs were different. In addition, the rule learning algorithm, repeated incremental pruning to produce error reduction algorithm, was also employed to produce effective classification rules for classifying lncRNAs and mRNAs, which gave competitive results compared with random forest and could give a clearer picture of different expression patterns between lncRNAs and mRNAs. Results not only revealed the heterogeneous expression pattern of lncRNA and mRNA, but also gave rise to the development of a new tool to identify the potential biological functions of such RNA subgroups.

A novel non-thermostable deuterolysin from Aspergillus oryzae.

Three putative deuterolysin (EC 3.4.24.29) genes (deuA, deuB, and deuC) were found in the Aspergillus oryzae genome database ( http://www.bio.nite.go.jp/dogan/project/view/AO ). One of these genes, deuA, was corresponding to NpII gene, previously reported. DeuA and DeuB were overexpressed by recombinant A. oryzae and were purified. The degradation profiles against protein substrates of both enzymes were similar, but DeuB showed wider substrate specificity against peptidyl MCA-substrates compared with DeuA. Enzymatic profiles of DeuB except for thermostability also resembled those of DeuA. DeuB was inactivated by heat treatment above 80° C, different from thermostable DeuA. Transcription analysis in wild type A. oryzae showed only deuB was expressed in liquid culture, and the addition of the proteinous substrate upregulated the transcription. Furthermore, the NaNO3 addition seems to eliminate the effect of proteinous substrate for the transcription of deuB.

Gene expression and brain imaging association study reveals gene signatures in major depressive disorder.

Major depressive disorder is often characterized by changes in the structure and function of the brain, which are influenced by modifications in gene expression profiles. How the depression-related genes work together within the scope of time and space to cause pathological changes remains unclear. By integrating the brain-wide gene expression data and imaging data in major depressive disorder, we identified gene signatures of major depressive disorder and explored their temporal-spatial expression specificity, network properties, function annotations and sex differences systematically. Based on correlation analysis with permutation testing, we found 345 depression-related genes significantly correlated with functional and structural alteration of brain images in major depressive disorder and separated them by directional effects. The genes with negative effect for grey matter density and positive effect for functional indices are enriched in downregulated genes in the post-mortem brain samples of patients with depression and risk genes identified by genome-wide association studies than genes with positive effect for grey matter density and negative effect for functional indices and control genes, confirming their potential association with major depressive disorder. By introducing a parameter of dispersion measure on the gene expression data of developing human brains, we revealed higher spatial specificity and lower temporal specificity of depression-related genes than control genes. Meanwhile, we found depression-related genes tend to be more highly expressed in females than males, which may contribute to the difference in incidence rate between male and female patients. In general, we found the genes with negative effect have lower network degree, more specialized function, higher spatial specificity, lower temporal specificity and more sex differences than genes with positive effect, indicating they may play different roles in the occurrence and development of major depressive disorder. These findings can enhance the understanding of molecular mechanisms underlying major depressive disorder and help develop tailored diagnostic and treatment strategies for patients of depression of different sex.

Spatiotemporal analysis of mRNA-protein relationships enhances transcriptome-based developmental inference.

Elucidating the complex relationships between mRNA and protein expression at high spatiotemporal resolution is critical for unraveling multilevel gene regulation and enhancing mRNA-based developmental analyses. In this study, we conduct a single-cell analysis of mRNA and protein expression of transcription factors throughout C. elegans embryogenesis. Initially, cellular co-presence of mRNA and protein is low, increasing to a medium-high level (73%) upon factoring in delayed protein synthesis and long-term protein persistence. These factors substantially affect mRNA-protein concordance, leading to potential inaccuracies in mRNA-reliant gene detection and specificity characterization. Building on the learned relationship, we infer protein presence from mRNA expression and demonstrate its utility in identifying tissue-specific genes and elucidating relationships between genes and cells. This approach facilitates identifying the role of sptf-1/SP7 in neuronal lineage development. Collectively, this study provides insights into gene expression dynamics during rapid embryogenesis and approaches for improving the efficacy of transcriptome-based developmental analyses.

Host Defense Peptides in Nutrition and Diseases: A Contributor of Immunology Modulation.

Host defense peptides (HDPs) are primary components of the innate immune system with diverse biological functions, such as antibacterial ability and immunomodulatory function. HDPs are produced and released by immune and epithelial cells against microbial invasion, which are widely distributed in humans, animals, plants, and microbes. Notably, there are great differences in endogenous HDP distribution and expression in humans and animals. Moreover, HDP expression could be regulated by exogenous substances, such as nutrients, and different physiological statuses in health and disease. In this review, we systematically assessed the regulation of expression and mechanism of endogenous HDPs from nutrition and disease perspectives, providing a basis to identify the specificity and regularity of HDP expression. Furthermore, the regulation mechanism of HDP expression was summarized systematically, and the differences in the regulation between nutrients and diseases were explored. From this review, we provide novel ideas targeted the immune regulation of HDPs for protecting host health in nutrition and practical and effective new ideas using the immune regulation theory for further research on protecting host health from pathogenic infection and excessive immunity diseases under the global challenge of the antibiotic-abuse-induced series of problems, including food security and microbial resistance.

Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from A Data-driven Perspective.

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human diseases. Ubiquitously expressed genes (UEGs) refer to the genes expressed across a majority of, if not all, phenotypic and physiological conditions of an organism. It is known that many human genes are broadly expressed across tissues. However, most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns, thus limiting the potential use of UEG information. In this study, we proposed a novel data-driven framework to leverage the extensive collection of ∼ 40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns, which offers a valuable resource to further characterize human transcriptome. Our results suggest that about half (12,234; 49.01%) of the human genes are expressed in at least 80% of human transcriptomes, and the median size of the human transcriptome is 16,342 genes (65.44%). Through gene clustering, we identified a set of UEGs, named LoVarUEGs, which have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement. To further demonstrate the usefulness of this resource, we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns, suggesting that the repression of these genes may not be unique to islet beta cells.

Diversity in Expression Biases of Lineage-Specific Genes During Development and Anhydrobiosis Among Tardigrade Species.

Lineage-specific genes can contribute to the emergence and evolution of novel traits and adaptations. Tardigrades are animals that have adapted to tolerate extreme conditions by undergoing a form of cryptobiosis called anhydrobiosis, a physical transformation to an inactive desiccated state. While studies to understand the genetics underlying the interspecies diversity in anhydrobiotic transitions have identified tardigrade-specific genes and family expansions involved in this process, the contributions of species-specific genes to the variation in tardigrade development and cryptobiosis are less clear. We used previously published transcriptomes throughout development and anhydrobiosis (5 embryonic stages, 7 juvenile stages, active adults, and tun adults) to assess the transcriptional biases of different classes of genes between 2 tardigrade species, Hypsibius exemplaris and Ramazzottius varieornatus. We also used the transcriptomes of 2 other tardigrades, Echiniscoides sigismundi and Richtersius coronifer, and data from 3 non-tardigrade species (Adenita vaga, Drosophila melanogaster, and Caenorhabditis elegans) to help identify lineage-specific genes. We found that lineage-specific genes have generally low and narrow expression but are enriched among biased genes in different stages of development depending on the species. Biased genes tend to be specific to early and late development, but there is little overlap in functional enrichment of biased genes between species. Gene expansions in the 2 tardigrades also involve families with different functions despite homologous genes being expressed during anhydrobiosis in both species. Our results demonstrate the interspecific variation in transcriptional contributions and biases of lineage-specific genes during development and anhydrobiosis in 2 tardigrades.

Lineage-Specific Genes and Family Expansions in Dictyostelid Genomes Display Expression Bias and Evolutionary Diversification during Development.

Gene duplications generate new genes that can contribute to expression changes and the evolution of new functions. Genomes often consist of gene families that undergo expansions, some of which occur in specific lineages that reflect recent adaptive diversification. In this study, lineage-specific genes and gene family expansions were studied across five dictyostelid species to determine when and how they are expressed during multicellular development. Lineage-specific genes were found to be enriched among genes with biased expression (predominant expression in one developmental stage) in each species and at most developmental time points, suggesting independent functional innovations of new genes throughout the phylogeny. Biased duplicate genes had greater expression divergence than their orthologs and paralogs, consistent with subfunctionalization or neofunctionalization. Lineage-specific expansions in particular had biased genes with both molecular signals of positive selection and high expression, suggesting adaptive genetic and transcriptional diversification following duplication. Our results present insights into the potential contributions of lineage-specific genes and families in generating species-specific phenotypes during multicellular development in dictyostelids.

Immune Differentiation Regulator p100 Tunes NF-κB Responses to TNF.

Tumor necrosis factor (TNF) is a pleiotropic cytokine whose primary physiological function involves coordinating inflammatory and adaptive immune responses. However, uncontrolled TNF signaling causes aberrant inflammation and has been implicated in several human ailments. Therefore, an understanding of the molecular mechanisms underlying dynamical and gene controls of TNF signaling bear significance for human health. As such, TNF engages the canonical nuclear factor kappa B (NF-κB) pathway to activate RelA:p50 heterodimers, which induce expression of specific immune response genes. Brief and chronic TNF stimulation produces transient and long-lasting NF-κB activities, respectively. Negative feedback regulators of the canonical pathway, including IκBα, are thought to ensure transient RelA:p50 responses to short-lived TNF signals. The non-canonical NF-κB pathway mediates RelB activity during immune differentiation involving p100. We uncovered an unexpected role of p100 in TNF signaling. Brief TNF stimulation of p100-deficient cells triggered an additional late NF-κB activity consisting of RelB:p50 heterodimers, which modified the TNF-induced gene-expression program. In p100-deficient cells subjected to brief TNF stimulation, RelB:p50 not only sustained the expression of a subset of RelA-target immune response genes but also activated additional genes that were not normally induced by TNF in WT mouse embryonic fibroblasts (MEFs) and were related to immune differentiation and metabolic processes. Despite this RelB-mediated distinct gene control, however, RelA and RelB bound to mostly overlapping chromatin sites in p100-deficient cells. Repeated TNF pulses strengthened this RelB:p50 activity, which was supported by NF-κB-driven RelB synthesis. Finally, brief TNF stimulation elicited late-acting expressions of NF-κB target pro-survival genes in p100-deficient myeloma cells. In sum, our study suggests that the immune-differentiation regulator p100 enforces specificity of TNF signaling and that varied p100 levels may provide for modifying TNF responses in diverse physiological and pathological settings.