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Identification of novel lung genes in bronchial epithelium by serial analysis of gene expression.

A description of the transcriptome of human bronchial epithelium should provide a basis for studying lung diseases, including cancer. We have deduced global gene expression profiles of bronchial epithelium and lung parenchyma, based on a vast dataset of nearly two million sequence tags from 21 serial analysis of gene expression (SAGE) libraries from individuals with a history of smoking. Our analysis suggests that the transcriptome of the bronchial epithelium is distinct from that of lung parenchyma and other tissue types. Moreover, our analysis has identified novel bronchial-enriched genes such as MS4A8B, and has demonstrated the use of SAGE for the discovery of novel transcript variants. Significantly, gene expression associated with ciliogenesis is evident in bronchial epithelium, and includes the expression of transcripts specifying axonemal proteins DNAI2, SPAG6, ASP, and FOXJ1 transcription factor. Moreover, expression of potential regulators of ciliogenesis such as MDAC1, NYD-SP29, ARMC3, and ARMC4 were also identified. This study represents a comprehensive delineation of the bronchial and parenchyma transcriptomes, identifying more than 20,000 known and hypothetical genes expressed in the human lung, and constitutes one of the largest human SAGE studies reported to date.

Aged↗

Uncovering the early and conserved molecular mechanisms of root nitrogen foraging in model and crops.

BACKGROUND: Nitrogen (N) foraging, the ability of plants to promote preferential root growth in N-rich patches of soil, is fundamental to the competitiveness and wellbeing of plants. A unique “split-root” system, where a heterogenous N environment stimulates root foraging, provides a powerful experimental model to study the mechanisms underlying root foraging in model (Arabidopsis) and/or crop plants. RESULTS: We used the split-root set up to capture early molecular events involved in systemic N-signaling after exposure to a heterogeneous N signal, through time-course transcriptomic analysis across shoots and roots of Arabidopsis. We found that a histone methyltransferase, SET DOMAIN GROUP 8 (SDG8), is necessary for root N-foraging, suggesting a previously unknown role for chromatin regulation in mediating the preferential root growth response to colonize N-rich patches. To determine if the underlying molecular mechanism is conserved in evolution, we compared the root foraging behavior from model-to-crop (Arabidopsis, tomato and maize). Our analysis showed the model and crop species shared a root N-foraging growth response, with some variation among specific genotypes. Interestingly, we observed both shared and distinct transcriptional responses to heterogenous N environments among these three species. CONCLUSIONS: Our study has generated insights into the molecular basis of root N-foraging, with the potential to improve nutrient use efficiency in crop plants in a heterogeneous field environment.

Crops, Agricultural↗

De novo transcriptome assembly and gene expression analysis of Cnidium officinale under high-temperature conditions.

BACKGROUND: The medicinal plant Cnidium officinale (CO) is widespread in Northeast Asia and vulnerable to heat stress. The naturally occurring composition of pharmacological ingredients of CO results in overall physiological consequences; therefore, it is crucial to have a comprehensive understanding of metabolic response to ambient heat in terms of acclimation to estimate how much CO is exposed to threatening environmental conditions. RESULTS: Transcriptome analysis is critical for understanding the consequences of long-term physiological adaptation of CO to abiotic stress. However, transcriptome analysis on this species, particularly under prolonged stress conditions, has remained limited. We employed a temperature gradient tunnel (TGT) to subject CO to high-temperature exposure for four months, enabling us to observe the cumulative effects of heat and assess its acclimation mechanisms. In the absence of genome sequencing data, we performed de novo transcriptome assembly and compared DEGs from temperature treatment plots of a TGT and a growth chamber (GC). Since interpreting transcriptomic data can be complex, we employed a sequential analytical approach, including DEG clustering, GO enrichment, KEGG pathway mapping, miRNA-target gene analysis, and multiple rounds of RNA sequencing validation. DEGs were classified into two categories: genes exhibiting significant fold changes and genes showing significant count changes rather than fold changes. Then, we analyzed the functional roles of DEGs to determine which pathways respond to ambient and stressful high temperatures and validated the findings through cross-comparison with GC. Additionally, we conducted miRNA analysis to investigate post-transcriptional regulation under high temperatures. CO grown under higher ambient temperatures exhibited slight upregulation of pathways related to protein stability and turnover, ABA biosynthesis, and energy production, such as photosynthesis and oxidative phosphorylation. However, under extreme heat stress, most metabolic pathways were downregulated except for those involved in transcription, translation, oxidative phosphorylation and the biosynthesis of cutin, suberin, and wax. CONCLUSION: This study demonstrated that proper clustering of genes based on expression levels and fold changes in two different experimental conditions, along with pathway mapping, may provide a comprehensive understanding of CO's response to heat stress. These insights could contribute to future research on heat tolerance and crop improvement.

Gene Expression Profiling↗

Microarray analysis of B-cell stimulation.

B-cell development to antibody-producing plasma cells requires the concerted function of a large number of genes and proteins. Genome-level expression profiling during human B-cell maturation was studied in anti-immunoglobulin M-stimulated Ramos cells. cDNA microarrays were used to follow changes in the transcriptome over several days. Close to 1500 genes had significantly altered expression at least at one time point. The genes were organized into clusters based on expression profiles and were further characterized based on the functions of the coded proteins. Several groups of genes important for B cells were analyzed. Here we concentrate on genes involved in signal transduction and cytokines and their receptors. The results provide knowledge on the development of humoral immunity. Several new genes were found to be essential for B-cell development. They can be used as targets for research and possibly for drug development.

Antibody Formation↗

Global analysis of gene expression using GeneChip microarrays.

DNA microarray technology, especially the use of GeneChip microarrays, has become a standard tool for parallel gene expression analysis. Recent improvements in GeneChip microarrays enable whole-genome expression analysis, and thus open a new avenue for studies of the composition, dynamics, and regulation of the transcriptome in plants.

Computational Biology↗

Interpreting the molecular biology and clinical behavior of multiple myeloma in the context of global gene expression profiling.

Multiple myeloma (MM) is a rare but uniformly fatal malignancy of antibody-secreting plasma cells (PCs). Although several key molecular events in disease initiation or progression have been confirmed (e.g. FGFR3/MMSET activation) or implicated (e.g. chromosome 13 deletion), the mechanisms of MM development remain enigmatic. Importantly, although generally being indistinguishable morphologically, MM exhibits a tremendous degree of variability in clinical course, with some patients surviving only months and others many years. However, current laboratory parameters can account for no more than 20% of this outcome variability. Furthermore, the means by which current drugs impart their anti-MM effect are also mostly unknown. In addition, the mechanisms by which MM cells contribute to serious comorbidities, such as osteopenia and/or focal lytic lesions of bone, are also poorly understood. Finally, very little knowledge exists concerning the molecular events leading to benign hyperplasia and/or overt malignancy of PCs. Given that abnormal gene expression lies at the heart of most, if not all, cancers, high-throughput global gene expression profiling has become a powerful tool for investigating molecular biology and clinical behavior of diseases. Here, we discuss recent progress made in addressing many of the above issues through the molecular dissection of the transcriptome of normal PCs and MM.

Cell Differentiation↗

Transcriptome analysis under pecan scab infection reveals the molecular mechanisms of the defense response in pecans.

Pecan scab, caused by the fungal pathogen Venturia effusa, is the most devastating disease of pecan (Carya illinoinensis) in the southeastern United States. Resistance to this pathogen is determined by a complex interaction between host genetics and disease pathotype with even field-susceptible cultivars being resistant to most scab isolates. To understand the underlying molecular mechanisms of scab resistance in pecan, we performed a transcriptome analysis of the pecan cultivar, 'Desirable', in response to inoculation with a pathogenic and a non-pathogenic scab isolate at three different time points (24, 48, and 96 hrs. post-inoculation). Differential gene expression and gene ontology enrichment analyses showed contrasting gene expression patterns and pathway enrichment in response to the contrasting isolates with varying pathogenicity. The weighted gene co-expression network analysis of differentially expressed genes detected 11 gene modules. Among them, two modules had significant enrichment of genes involved with defense responses. These genes were particularly upregulated in the resistant reaction at the early stage of fungal infection (24 h) compared to the susceptible reaction. Hub genes in these modules were predominantly related to receptor-like protein kinase activity, signal reception, signal transduction, biosynthesis and transport of plant secondary metabolites, and oxidoreductase activity. Results of this study suggest that the early response of pathogen-related signal transduction and development of cellular barriers against the invading fungus are likely defense mechanisms employed by pecan cultivars against non-virulent scab isolates. The transcriptomic data generated here provide the foundation for identifying candidate resistance genes in pecan against V. effusa and for exploring the molecular mechanisms of disease resistance.

Carya↗

Parallel analysis of transcript and metabolic profiles: a new approach in systems biology.

The past few years in the medical and biological sciences have been characterized by the advent of systems biology. However, despite the well-known connectivity between the molecules described by transcriptomic, proteomic and metabolomic approaches, few studies have tried to correlate parameters across the various levels of systemic description. When comparing the discriminatory power of metabolic and RNA profiling to distinguish between different potato tuber systems, using the techniques described here suggests that metabolic profiling has a higher resolution than expression profiling. When applying pairwise transcript-metabolite correlation analyses, 571 of the 26,616 possible pairs showed significant correlation, most of which was novel and included several strong correlations to nutritionally important metabolites. We believe this approach to be of high potential value in the identification of candidate genes for modifying the metabolite content of biological systems.

Computational Biology↗

Optimized protocol for linear RNA amplification and application to gene expression profiling of human renal biopsies.

Gene expression analysis using high-density cDNA or oligonucleotide arrays is a rapidly emerging tool for transcriptomics, the analysis of the transcriptional state of a cell or organ. One of the limitations of current methodologies is the requirement of a relatively large amount of total or polyadenylated RNA as starting material. Standard array hybridization protocols require 5-15 micrograms labeled RNA. To obtain these quantities from small amounts of starting RNA material, RNA can be amplified in a linear fashion. Here we introduce an optimized protocol for rapid and easy-to-use amplification of as little as 1 ng total RNA. Our analysis shows that this method is linear and highly reproducible and that it preserves similarities as well as dissimilarities between normal and disease-related samples. We applied this technique to the RNA expression profiling of human renal allograft biopsies with normal histology and compared them to the profiles of renal biopsies with histological evidence of chronic transplant nephropathy or chronic rejection. Among others, complement component C1r was found to be significantly up-regulated in chronic rejection and chronic transplant nephropathy biopsies compared to normal samples, while fructose-1,6-biphosphatase showed lower-than-normal expression.

Gene Expression Profiling↗

Transcriptome analysis of the diseased intervertebral disc tissue in patients with spinal tuberculosis.

OBJECTIVE: To investigate the differential expression genes (DEGs) in spinal tuberculosis using transcriptomics, with the aim of identifying novel therapeutic targets and prognostic indicators for the clinical management of spinal tuberculosis. METHODS: Patients who visited the Department of Orthopedics at the Second Hospital, Lanzhou University from January 2021 to May 2023 were enrolled. Based on the inclusion and exclusion criteria, there were 5 patients in the test group and 5 patients in the control group. Total RNA was extracted and paired-end sequencing was conducted on the sequencing platform. After processing the sequencing data with clean reads and annotating the reference genome, FPKM normalization and differential expression analysis were performed. The DEGs and long non-coding RNAs (LncRNAs) were analyzed for Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment. The cis-regulation of differentially expressed mRNAs (DE mRNAs) by LncRNAs was predicted and analyzed to establish a co-expression network. RESULTS: This study identified 2366 DEGs, with 974 genes significantly upregulated and 1392 genes significantly downregulated. The upregulated genes are associated with cytokine-cytokine receptor interactions, tuberculosis, and TNF-α signaling pathways, primarily enriched in biological processes such as immunity and inflammation. The downregulated genes are related to muscle development, contraction, fungal defense response, and collagen metabolism processes. Analysis of LncRNAs from bone tuberculosis RNA-seq data detected a total of 3652 LncRNAs, with 356 significantly upregulated and 184 significantly downregulated. Further analysis identified 311 significantly different LncRNAs that could cis-regulate 777 target genes, enriched in pathways such as muscle contraction, inflammatory response, and immune response, closely related to bone tuberculosis. There are 51 genes enriched in the immune response pathway regulated by cis-acting LncRNAs. LncRNAs that regulate immune response-related genes, such as upregulated RP11-451G4.2, RP11-701P16.5, AC079767.4, AC017002.1, LINC01094, CTA-384D8.35, and AC092484.1, as well as downregulated RP11-2C24.7, may serve as potential prognostic and therapeutic targets. CONCLUSION: The DE mRNAs and LncRNAs in spinal tuberculosis are both associated with immune regulatory pathways. These pathways promote or inhibit the tuberculosis infection and development at the mechanistic level and play an important role in the process of tuberculosis transferring to bone tissue.

Humans↗

An Integrated Clinical Genomic and Transcriptomic Subgrouping of Central Chondrosarcoma.

Central conventional chondrosarcoma, a malignant cartilage-producing bone tumor, is the second most common bone sarcoma. Chondrosarcomas are histologically graded, which is so far the best predictor of survival. Early mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are frequent, leading to the production of the oncometabolite D-2-hydroxyglutarate, which affects DNA methylation, resulting in a preferred chondrogenic differentiation over osteogenic differentiation of mesenchymal stem cells, which are currently considered the precursor cells of chondrosarcoma. DNA methylation profiling has previously revealed distinct profiles between IDH-mutant and IDH-wild-type chondrosarcomas, but the presence of further DNA methylation subgroups indicates that classification based solely on IDH status is too simplistic. In this study, we aim to identify biological subgroups in a total of 116 chondrosarcomas by integrating clinical data, IDH mutation status, gene expression, and genome-wide loss of heterozygosity (LOH). Clinical associations were observed between several factors, including sex and histological grade, as well as tumor site and IDH mutation status. RNA sequencing and genome-wide LOH confirmed the distinction between IDH-wild-type and IDH-mutant chondrosarcomas, where the number of chromosome arms affected by LOH was significantly higher in IDH-wild-type tumors than in IDH-mutant tumors. However, no clear subgroups emerged within each IDH group. Further clustering on RNA expression of differentiation markers identified subgroups characterized by chondrogenic, osteogenic, resting chondrocyte, or dedifferentiated profiles. These different subgroups showed a specific clinical presentation and suggest different precursor cells. Instead of a simple dichotomy between IDH-mutant and IDH-wild-type, our integrated approach highlights interconnected clinical, genomic, and transcriptomic patterns that offer a more nuanced view of chondrosarcoma biology and might potentially guide treatment stratification.

Humans↗

Gene expression profiles of endothelium, microglia and oligodendrocytes in hippocampus of post-stroke depression rat at single cell resolution.

Post-stroke depression (PSD) is a common but severe mental complication after stroke. However, the cellular and molecular understanding of PSD is still yet to be illustrated. In current study, we prepared PSD rat model (MD) via unilateral middle cerebral artery occlusion (MCAO) and chronic stress stimulation (DEPR), and isolated hippocampal tissues for single cell sequencing of 10x Genomics Chromium. First, we determined the presence of the increased cell population of endothelium and microglia and the compromised oligodendrocytes in MD compared to NC, MCAO and DEPR. The enriched functions of highly variable genes (HVGs) of endothelium and microglia suggested a reinforced blood-brain barrier in MD. Next, cell clusters of endothelium, microglia and oligodendrocytes were individually analyzed, and the subtypes with distinct functions were identified. The presence of expression profiles, intercellular communications and signaling pathways of these three cell populations of PSD displayed a similar but more aggressive appearance with DEPR compared to MCAO and NC. Taken together, this study characterized the specific gene profile of endothelium, microglia and oligodendrocytes of hippocampal PSD by single cell sequencing, emphasizing the crosstalk among them to provide theoretical basis for the in-depth mechanism research and drug therapy of PSD.

Animals↗

Identification and analysis of chromodomain-containing proteins encoded in the mouse transcriptome.

The chromodomain is 40-50 amino acids in length and is conserved in a wide range of chromatic and regulatory proteins involved in chromatin remodeling. Chromodomain-containing proteins can be classified into families based on their broader characteristics, in particular the presence of other types of domains, and which correlate with different subclasses of the chromodomains themselves. Hidden Markov model (HMM)-generated profiles of different subclasses of chromodomains were used here to identify sequences encoding chromodomain-containing proteins in the mouse transcriptome and genome. A total of 36 different loci encoding proteins containing chromodomains, including 17 novel loci, were identified. Six of these loci (including three apparent pseudogenes, a novel HP1 ortholog, and two novel Msl-3 transcription factor-like proteins) are not present in the human genome, whereas the human genome contains four loci (two CDY orthologs and two apparent CDY pseudogenes) that are not present in mouse. A number of these loci exhibit alternative splicing to produce different isoforms, including 43 novel variants, some of which lack the chromodomain. The likely functions of these proteins are discussed in relation to the known functions of other chromodomain-containing proteins within the same family.

Acetyltransferases↗

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

Biomarkers, Tumor↗

Predicting cellular responses to perturbation across diverse contexts with State.

While machine learning models offer potential for predicting transcriptomic effects of perturbation, they currently struggle to generalize across cellular contexts. Here, we introduce State, a machine learning model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. State is trained using single-cell gene expression data to predict perturbation effects across sets of cells. State improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling, and chemical perturbations with significantly improved accuracy compared with baselines. Its cell embeddings trained on observational data from 167 million cells enable the identification of strong perturbations in cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that can be used to evaluate future models. Overall, the performance and flexibility of State set the stage for scaling the development of AI models of cell state.

Machine Learning↗

The Arabidopsis cold-responsive transcriptome and its regulation by ICE1.

To understand the gene network controlling tolerance to cold stress, we performed an Arabidopsis thaliana genome transcript expression profile using Affymetrix GeneChips that contain approximately 24,000 genes. We statistically determined 939 cold-regulated genes with 655 upregulated and 284 downregulated. A large number of early cold-responsive genes encode transcription factors that likely control late-responsive genes, suggesting a multitude of transcriptional cascades. In addition, many genes involved in chromatin level and posttranscriptional regulation were also cold regulated, suggesting their involvement in cold-responsive gene regulation. A number of genes important for the biosynthesis or signaling of plant hormones, such as abscisic acid, gibberellic acid, and auxin, are regulated by cold stress, which is of potential importance in coordinating cold tolerance with growth and development. We compared the cold-responsive transcriptomes of the wild type and inducer of CBF expression 1 (ice1), a mutant defective in an upstream transcription factor required for chilling and freezing tolerance. The transcript levels of many cold-responsive genes were altered in the ice1 mutant not only during cold stress but also before cold treatments. Our study provides a global picture of the Arabidopsis cold-responsive transcriptome and its control by ICE1 and will be valuable for understanding gene regulation under cold stress and the molecular mechanisms of cold tolerance.

Adaptation, Physiological↗

Systems level analysis of protein synthesis patterns associated with bacterial growth and metabolic transitions.

Gene expression databases, acquired by proteomics and transcriptomics, describe physiological and developmental programs at the systems level. Here we analyze proteosynthetic profiles in a bacterium undergoing defined metabolic changes. Streptomyces coelicolor cultured in a defined liquid medium displays four distinct patterns of gene expression associated with growth on glutamate, diauxic transition, and growth on maltose and ammonia that terminates by starvation for nitrogen and entry into stationary phase. Principal component and fuzzy cluster analyses of the proteome database of 935 protein spot profiles revealed principal kinetic patterns. Online linkage of the proteome database (SWICZ) to a protein-function database (KEGG) revealed limited correlations between expression profiles and metabolic pathway activities. Proteins belonging to principal metabolic pathways defined characteristic kinetic profiles correlated with the physiological state of the culture. These analyses supported the concept that metabolic flux was regulated not by individual enzymes but rather by groups of enzymes whose synthesis responded to changes in nutritional conditions. Higher-level regulation is reflected by the distribution of all kinetic profiles into only nine groups. The observation that enzymes representing principal metabolic pathways displayed their own distinctive average kinetic profiles suggested that expression of a "high-flux backbone" may dominate regulation of metabolic flux.

Adaptation, Physiological↗

Ossicle occurrence characteristics and related molecular mechanisms in the sea cucumber Apostichopus japonicus.

To investigate the morphogenetic pattern and molecular mechanism of ossicle formation in the sea cucumber Apostichopus japonicus, this study systematically examined the morphological development and temporal sequence of spicules using the NaClO maceration method, in-situ squash preparation and microscopic observation. Comparative transcriptome sequencing was performed between doliolaria and pentactula larvae to screen differentially expressed genes (DEGs) related to ossicles formation, followed by pathway enrichment analysis. The function of the candidate key gene papilin-like was verified using siRNA-mediated gene silencing. The results were as follows: 1) Ossicles of A. japonicus first appeared at the late auricularia stage, initiating as X-shaped ossicles at the base of the oral tentacles. The number of X-shaped ossicles increased dramatically during the doliolaria stage. X-shaped ossicles were gradually replaced by table-shaped and rosette-shaped ossicles at the pentactula stage, suggesting that X-shaped ossicles may differentiate into these two ossicle types. The morphology of table-shaped ossicles showed a "simple-complex-simple" pattern with development. 2) Key genes related to ossicles formation, including CA1, COL1A2, and papilin-like, were identified by transcriptome analysis. After papilin-like knockdown, abnormal morphologies were observed in table-shaped ossicles of 1-year-old A. japonicus, such as spine-like protrusions on the outer margin of the disc and loss of table legs, confirming its crucial roles in maintaining ossicle morphology. This study clarified the morphological development pattern of ossicles in A. japonicus and identified a key regulatory gene (papilin-like) involved in ossicle morphogenesis, providing preliminary insights into the underlying molecular regulatory mechanism. These findings enrich our understanding on ossicles formation in echinoderms, and provide important morphological and molecular biological information for further studies on the developmental mechanism of ossicles in A. japonicus.

Animals↗