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At least 235 records · Page 13Linked to original sources

PubMed2002

Reproducibility of oligonucleotide microarray transcriptome analyses. An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae.

Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray analysis in functional genomics and metabolic engineering, we designed a set of experiments to specifically address this issue. Saccharomyces cerevisiae CEN.PK113-7D was grown under defined conditions in glucose-limited chemostats, followed by transcriptome analysis with Affymetrix GeneChip arrays. In each of the laboratories, three independent replicate cultures were grown aerobically as well as anaerobically. Although variations introduced by in vitro handling steps were small and unbiased, greater variation from replicate cultures underscored that, to obtain reliable information, experimental replication is essential. Under aerobic conditions, 86% of the most highly expressed yeast genes showed an average intralaboratory coefficient of variation of 0.23. This is significantly lower than previously reported for shake-flask-culture transcriptome analyses and probably reflects the strict control of growth conditions in chemostats. Using the triplicate data sets and appropriate statistical analysis, the change calls from anaerobic versus aerobic comparisons yielded an over 95% agreement between the laboratories for transcripts that changed by over 2-fold, leaving only a small fraction of genes that exhibited laboratory bias.

Aerobiosis↗

PubMed2003

Use of transcriptome data to unravel the fine structure of genes involved in sepsis.

The sequence of the human genome is providing researchers with the scaffold upon which genes are built. The definition of the boundaries of the genes themselves and of their complex architecture requires a mapping of the transcriptome to the genome. A methodology was developed for generating a detailed transcriptome map and for reconstituting transcripts by using the genome as a template. As a demonstration of the potential of this method, the structure of the human Toll-like receptor (TLR) genes was reevaluated. For all TLR genes for which a genomic sequence was available (i.e., all except TLR10), novel features of the gene structure were discovered. These features include multiple alternative polyadenylation sites, additional exons or splice variants, and overlaps with other genes. These findings have implications for the analysis of TLR gene expression and for the diversity of the proteins encoded by these genes.

Gene Expression Profiling↗

PubMed2026

jsPCA: fast, scalable, and interpretable identification of spatial domains and variable genes across multi-slice and multi-sample spatial transcriptomics data.

MOTIVATION: Spatial transcriptomics technologies record genome-wide measurements of gene expression with high spatial resolution. These technologies generate large and high-dimensional datasets requiring efficient automated methods for their analysis. We introduce joint spatial PCA (jsPCA), a novel, fast, scalable and interpretable method for the automatic identification of spatial domains and variable genes in multi-slice and multi-sample spatial transcriptomics data. RESULTS: jsPCA relies on a simple mathematical formulation of a spatial covariance defined as the product of the gene expression covariance with the spatial autocorrelation. The principal components of this spatial covariance yield a biologically meaningful low-dimensional representation. From this representation, spatial domains are derived by simple clustering and spatially variable genes are identified directly from the principal component coefficients. A joint representation of multiple slices and samples without spatial alignment is obtained by computing common principal components via joint diagonalization. By leveraging data sparsity and non-convex manifold optimization, jsPCA leads to computing time in the order of seconds to minutes, substantially outperforming state-of-the-art approaches. We benchmarked jsPCA against 10 state-of-the-art methods on two reference databases. Our approach demonstrated excellent performance, comparable or better than state-of-the-art methods, while being much faster, interpretable, and scalable to very large datasets.

Journal Article↗

PubMed2003

Can transcriptome size be estimated from SAGE catalogs?

MOTIVATION: SAGE (Serial Analysis of Gene Expression) can be used to estimate the number of unique transcripts in a transcriptome. A simple estimator that corrects for sequencing and sampling errors was applied to a SAGE library (137 832 tags) obtained from mouse embryonic stem cells, and also to Monte Carlo simulated libraries generated using assumed distributions of 'true' expression levels consistent with the data. RESULTS: When the corrected data themselves were taken as the underlying model of 'ground truth', the estimator converged to the 'true' value (53 535) only after counting 300 000 simulated tags, more than twice the number in the experiment. The SAGE data could also be well fit by a Monte Carlo model based on a truncated inverse-square distribution of expression levels, with 130 000 'true' transcripts and 10(6) samples needed for convergence. We conclude that the size of a transcriptome is ill-determined from SAGE libraries of even moderately large size. In order to obtain a valid estimate, one must sample a number of tags inversely proportional to the lowest abundance level, which is not known a priori. This constrains the design of SAGE experiments intended to determine biological complexity. AVAILABILITY: The 'homemade' software used for this analysis was not designed for general or 'production' use, but the authors will be happy to share Fortran sourcecode with interested parties. CONTACT: sternm@grc.nia.nih.gov

Algorithms↗

PubMed2002

Transcriptome analysis of human autosomal trisomy.

We present transcriptome analyses of primary cultures of human fetal cells from pregnancies affected with trisomy 21 (t21) and trisomy 13 (t13). Pooled mRNA samples from t21 and t13 cases were used for comparative hybridizations to cDNA arrays with pooled mRNA from normal cells. When the array cDNAs were grouped by chromosomal location the relevant trisomic chromosome could be clearly identified as showing the most significant misregulation. The average level of transcription on the trisomic chromosome was increased only approximately 1.1-fold compared to normal cells on array analysis. Since the karyotype could be accurately predicted by the transcriptome this could provide a novel method of detecting aneusomy of unknown position. Subsequent analysis of individuals cases demonstrated that variation in transcriptional profiles between samples within each class made transcriptional karyotyping difficult without pooling or the use of arrays with a higher proportion of all human cDNAs. Interestingly, consistent differences in the relative expression levels between chromosomes were detected suggesting that genomic control mechanisms may act over larger distances than previously thought. Most (>95%) >+/-2 SD misregulated genes did not map to the trisomic chromosome and significant misregulation was more common in t13 than t21. These data support a model of a subtle primary upregulation of genes on the trisomic chromosome resulting in a secondary, generalized and more extreme transcriptional misregulation. It seems likely that the degree of this misregulation determines the severity of the phenotype in most aneuploidy.

Chromosomes, Human, Pair 13↗

PubMed2026

Admission whole-blood transcriptomic characterization of a neutrophil-predominant systemic immune response in patients with acute traumatic brain injury.

BACKGROUND: Acute traumatic brain injury (TBI) is accompanied by systemic immune responses, but their whole-blood transcriptomic features at hospital arrival remain incompletely characterized. We aimed to characterize these features in patients with acute TBI compared with healthy controls. METHODS: In this single-center prospective observational study, we performed whole-blood RNA sequencing on hospital-arrival samples from 42 patients with acute TBI and 21 healthy controls. Analyses included differential expression (limma-voom; FDR < 0.05, |log2FC| > 0.7), functional enrichment, Ingenuity Pathway Analysis, CIBERSORTx LM22 deconvolution, and per-sample neutrophil degranulation signature scoring. RESULTS: Differential expression analysis identified 996 upregulated and 863 downregulated genes, with marked upregulation of inflammation-, innate immunity-, and neutrophil-related genes including DUSP1, HMGB2, MMP9, and S100A8. Canonical pathways with positive IPA z-scores included Neutrophil degranulation, Neutrophil Extracellular Trap Signaling Pathway, and Toll-like Receptor Signaling; upstream regulators included TNF, IL1B, IFNG, and STAT3. Deconvolution identified 7 of 22 differing subsets (q < 0.05), with relatively higher myeloid and lower lymphoid fractions in TBI. The Neutrophil degranulation signature score correlated with Injury Severity Score within TBI (Spearman ρ = +0.55; q < 0.001). CONCLUSIONS: Admission whole-blood transcriptomics characterized a neutrophil-predominant systemic transcriptional response in patients with acute TBI. This response was also evident among patients without major extracranial injury and was associated with total ISS. However, because the study lacked an appropriately matched non-TBI trauma comparator, the findings should be interpreted as a descriptive characterization of a systemic injury response accompanying TBI and do not establish a TBI-specific molecular signature or mechanism.

gene expression↗

PubMed2025

SpaceBar enables clone tracing in spatial transcriptomic data.

We report a cellular barcoding strategy, SpaceBar, that enables simultaneous clone tracing and spatial transcriptomics profiling. Our approach uses a library of 96 synthetic barcode sequences that can be robustly detected by imaging based spatial transcriptomics (seqFISH), delivered such that each cell is labeled with a combination of barcodes. We used these barcodes to label melanoma cells in a tumor xenograft model and profiled both clone identity and spatial gene expression in situ. We developed a gene scoring metric that quantifies how strongly gene expression is driven by intrinsic cellular cues or extrinsic environmental signals. Our framework distinguishes between clonal dynamics and environmentally-driven transcriptional regulation in complex tissue contexts.

Journal Article↗

PubMed2025

Single-cell-scale spatial transcriptome of the developing and adult mouse ovary.

Mammalian ovary development is essential for female fertility, involving the complex spatial patterning of diverse cell types to establish the finite reserve of ovarian follicles. While single-cell transcriptome analyses have provided important insights into the mechanisms driving specification and developmental trajectories of ovarian cells, they disrupt this crucial spatial context. To overcome this limitation, we used 10X Genomics Visium HD spatial transcriptomics to analyze the developing mouse ovary while maintaining its native cellular architecture. We captured all ovarian cell types at eight key fetal and postnatal timepoints, generating a near single cell resolution library of spatial gene expression across ovarian development. This comprehensive dataset allows analysis of dynamic transcriptional signatures associated with unique spatial patterning throughout development, including the establishment of cortex and medulla and assembly of ovarian follicles in each region. This dataset represents a fundamental resource for the investigation of regulatory mechanisms driving spatial patterning of the ovary and opens new avenues to explore the spatial determinants of female fertility and reproductive longevity.

Journal Article↗

PubMed2025

Comprehensive Transcriptome Annotation of Thousands of HIV-1 Genomes.

Alternative splicing in HIV-1 has been a central focus of decades of research, uncovering key mechanisms of viral gene regulation, immune evasion, and therapeutic response - yet, no reference resource has existed to support transcriptome-wide analysis, limiting adoption of modern computational methods. We present HIV Atlas (https://ccb.jhu.edu/HIV_Atlas), the first reference-quality annotation of HIV-1 and SIV transcriptional diversity. We manually curated transcriptomes for HIV-1HXB2 and SIVmac239 and developed Vira, an automated annotation-transfer method specifically designed to address unique challenges of viral genome biology, to generate high-quality annotations for 2,077 complete HIV-1 genomes. Using the resources presented in our work, we evaluated conservation of splice sites, revealing near-perfect preservation of major donors and acceptors. Furthermore, using several public datasets, we demonstrate how HIV Atlas enhances methodology, improves the quality and novelty of results, and opens novel avenues for research, supporting more accurate and comprehensive analyses of bulk, single-cell, and spatial RNA-seq in HIV-1 studies.

Journal Article↗

PubMed2000

The mouse brain transcriptome by SAGE: differences in gene expression between P30 brains of the partial trisomy 16 mouse model of Down syndrome (Ts65Dn) and normals.

Trisomy 21, or Down syndrome (DS), is the most common genetic cause of mental retardation. Changes in the neuropathology, neurochemistry, neurophysiology, and neuropharmacology of DS patients' brains indicate that there is probably abnormal development and maintenance of central nervous system structure and function. The segmental trisomy mouse (Ts65Dn) is a model of DS that shows analogous neurobehavioral defects. We have studied the global gene expression profiles of normal and Ts65Dn male and normal female mice brains (P30) using the serial analysis of gene expression (SAGE) technique. From the combined sample we collected a total of 152,791 RNA tags and observed 45,856 unique tags in the mouse brain transcriptome. There are 14 ribosomal protein genes (nine under expressed) among the 330 statistically significant differences between normal male and Ts65Dn male brains, which possibly implies abnormal ribosomal biogenesis in the development and maintenance of DS phenotypes. This study contributes to the establishment of a mouse brain transcriptome and provides the first overall analysis of the differences in gene expression in aneuploid versus normal mammalian brain cells.

Animals↗

PubMed2002

Transcriptome changes for Arabidopsis in response to salt, osmotic, and cold stress.

To identify genes of potential importance to cold, salt, and drought tolerance, global expression profiling was performed on Arabidopsis plants subjected to stress treatments of 4 degrees C, 100 mM NaCl, or 200 mM mannitol, respectively. RNA samples were collected separately from leaves and roots after 3- and 27-h stress treatments. Profiling was conducted with a GeneChip microarray with probe sets for approximately 8,100 genes. Combined results from all three stresses identified 2,409 genes with a greater than 2-fold change over control. This suggests that about 30% of the transcriptome is sensitive to regulation by common stress conditions. The majority of changes were stimulus specific. At the 3-h time point, less than 5% (118 genes) of the changes were observed as shared by all three stress responses. By 27 h, the number of shared responses was reduced more than 10-fold (< 0.5%), consistent with a progression toward more stimulus-specific responses. Roots and leaves displayed very different changes. For example, less than 14% of the cold-specific changes were shared between root and leaves at both 3 and 27 h. The gene with the largest induction under all three stress treatments was At5g52310 (LTI/COR78), with induction levels in roots greater than 250-fold for cold, 40-fold for mannitol, and 57-fold for NaCl. A stress response was observed for 306 (68%) of the known circadian controlled genes, supporting the hypothesis that an important function of the circadian clock is to "anticipate" predictable stresses such as cold nights. Although these results identify hundreds of potentially important transcriptome changes, the biochemical functions of many stress-regulated genes remain unknown.

Adaptation, Physiological↗

PubMed2002

Arabidopsis transcriptome profiling indicates that multiple regulatory pathways are activated during cold acclimation in addition to the CBF cold response pathway.

Many plants, including Arabidopsis, increase in freezing tolerance in response to low, nonfreezing temperatures, a phenomenon known as cold acclimation. Previous studies established that cold acclimation involves rapid expression of the CBF transcriptional activators (also known as DREB1 proteins) in response to low temperature followed by induction of the CBF regulon (CBF-targeted genes), which contributes to an increase in freezing tolerance. Here, we present the results of transcriptome-profiling experiments indicating the existence of multiple low-temperature regulatory pathways in addition to the CBF cold response pathway. The transcript levels of approximately 8000 genes were determined at multiple times after plants were transferred from warm to cold temperature and in warm-grown plants that constitutively expressed CBF1, CBF2, or CBF3. A total of 306 genes were identified as being cold responsive, with transcripts for 218 genes increasing and those for 88 genes decreasing threefold or more at one or more time points during the 7-day experiment. These results indicate that extensive downregulation of gene expression occurs during cold acclimation. Of the cold-responsive genes, 48 encode known or putative transcription factors. Two of these, RAP2.1 and RAP2.6, were activated by CBF expression and thus presumably control subregulons of the CBF regulon. Transcriptome comparisons indicated that only 12% of the cold-responsive genes are certain members of the CBF regulon. Moreover, at least 28% of the cold-responsive genes were not regulated by the CBF transcription factors, including 15 encoding known or putative transcription factors, indicating that these cold-responsive genes are members of different low-temperature regulons. Significantly, CBF expression at warm temperatures repressed the expression of eight genes that also were downregulated by low temperature, indicating that in addition to gene induction, gene repression is likely to play an integral role in cold acclimation.

Acclimatization↗

PubMed2002

The dynamics of the Saccharomyces carlsbergensis brewing yeast transcriptome during a production-scale lager beer fermentation.

The transcriptome of a lager brewing yeast (Saccharomyces carlsbergensis, syn. of S. pastorianus), was analysed at 12 different time points spanning a production-scale lager beer fermentation. Generally, the average expression rapidly increased and had a maximum value on day 2, then decreased as the sugar got consumed. Especially genes involved in protein and lipid biosynthesis or glycolysis were highly expressed during the beginning of the fermentation. Similarities as well as significant differences in expression profiles could be observed when comparing to a previous transcriptome analysis of a laboratory yeast grown in YPD. The regional distribution of various expression levels on the chromosomes appeared to be random or near-random and no reduction in expression near telomeres was observed.

Beer↗

PubMed2003

Enhanced production of insulin-like growth factor I fusion protein in Escherichia coli by coexpression of the down-regulated genes identified by transcriptome profiling.

The transcriptome profiles of recombinant Escherichia coli producing human insulin-like growth factor I fusion protein (IGF-I(f)) during the high-cell-density fed-batch culture were analyzed using DNA microarrays. The expression levels of 529 genes were significantly altered after induction. About 200 genes were significantly down-regulated during the production of IGF-I(f) after induction. Among these down-regulated genes, we rationally selected and coexpressed in E. coli producing IGF-I(f) the prsA gene (encoding a phosphoribosyl pyrophosphate synthetase) and the glpF gene (encoding a glycerol transporter), which are involved in an early key step in the biosynthetic pathway of nucleotides and amino acids (Trp and His) and the first step in glycerol utilization, respectively. As a result, the production of IGF-I(f) could be increased from 1.8 +/- 0.13 (+/- standard deviation) to 4.3 +/- 0.24 g/liter. The volumetric productivity was also increased from 0.36 +/- 0.027 to 0.82 +/- 0.048 g/liter/h. These results demonstrate that transcriptome profiling can provide invaluable information in designing engineered strains showing enhanced performance.

Aquaporins↗

PubMed1999

Yeast Upf proteins required for RNA surveillance affect global expression of the yeast transcriptome.

mRNAs are monitored for errors in gene expression by RNA surveillance, in which mRNAs that cannot be fully translated are degraded by the nonsense-mediated mRNA decay pathway (NMD). RNA surveillance ensures that potentially deleterious truncated proteins are seldom made. NMD pathways that promote surveillance have been found in a wide range of eukaryotes. In Saccharomyces cerevisiae, the proteins encoded by the UPF1, UPF2, and UPF3 genes catalyze steps in NMD and are required for RNA surveillance. In this report, we show that the Upf proteins are also required to control the total accumulation of a large number of mRNAs in addition to their role in RNA surveillance. High-density oligonucleotide arrays were used to monitor global changes in the yeast transcriptome caused by loss of UPF gene function. Null mutations in the UPF genes caused altered accumulation of hundreds of mRNAs. The majority were increased in abundance, but some were decreased. The same mRNAs were affected regardless of which of the three UPF gene was inactivated. The proteins encoded by UPF-dependent mRNAs were broadly distributed by function but were underrepresented in two MIPS (Munich Information Center for Protein Sequences) categories: protein synthesis and protein destination. In a UPF(+) strain, the average level of expression of UPF-dependent mRNAs was threefold lower than the average level of expression of all mRNAs in the transcriptome, suggesting that highly abundant mRNAs were underrepresented. We suggest a model for how the abundance of hundreds of mRNAs might be controlled by the Upf proteins.

Adaptor Proteins, Signal Transducing↗

PubMed2003

Transcriptomal analysis of failing and nonfailing human hearts.

Heart failure is a multifactorial disease that may result from different initiating events. To contribute to an improved comprehension of normal cardiac function and the molecular events leading to heart failure, we performed large-scale gene expression analysis of failing and nonfailing human ventricle. Our aim was to define and compare expression profiles of 4 specific pathophysiological cardiac situations: 1) left ventricle (LV) from nonfailing heart; 2) LV from failing hearts affected by dilated cardiomyopathy (DCM); 3) LV from failing hearts affected by ischemic CM (ICM); 4) right ventricle (RV) from failing hearts affected by DCM or ICM. We used oligonucleotide arrays representing approximately 12,000 human genes. After stringent numerical analyses using several statistical tests, we identified 1,306 genes with a similar expression profile in all 4 cardiac situations, therefore representative of part of the human cardiac expression profile. A total of 95 genes displayed differential expression between failing and nonfailing heart samples, reflecting a reversal to developmental gene expression, dedifferentiation of failing cardiomyocytes, and involvement of apoptosis. Twenty genes were differentially expressed between failing LV and failing RV, identifying possible candidates for different functioning of both ventricles. Finally, no genes were found to be significantly differentially expressed between failing DCM and failing ICM LV, emphasizing that transcriptomal analysis of explanted hearts results mainly in identification of expression profiles of end-stage heart failure and less in determination of expression profiles of the underlying etiology. Taken together, our data resulted in identification of putative transcriptomal landmarks for normal and disturbed cardiac function.

Adolescent↗

PubMed2001

Human mast cell transcriptome project.

After draft reading of the human genome sequence, systemic analysis of the transcriptome (the whole transcripts present in a cell) is progressing especially in commonly available cell types. Until recently, human mast cells were not commonly available. We have succeeded to generate a substantial number of human mast cells from umbilical cord blood and from adult peripheral blood progenitors. Then, we have examined messenger RNA selectively transcribed in these mast cells using high-density oligonucleotide probe arrays. Many unexpected but important transcripts were selectively expressed in human mast cells. We discuss the results obtained from transcriptome screening by introducing our data regarding mast-cell-specific genes.

Blood Cells↗

PubMed2002

Analysis of a human brain transcriptome map.

BACKGROUND: Genome wide transcriptome maps can provide tools to identify candidate genes that are over-expressed or silenced in certain disease tissue and increase our understanding of the structure and organization of the genome. Expressed Sequence Tags (ESTs) from the public dbEST and proprietary Incyte LifeSeq databases were used to derive a transcript map in conjunction with the working draft assembly of the human genome sequence. RESULTS: Examination of ESTs derived from brain tissues (excluding brain tumor tissues) suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors. CONCLUSIONS: This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.

Journal Article↗