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Results for “Gene expression data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Two poplar-associated bacterial isolates induce additive favorable responses in a constructed plant-microbiome system

Here, the biological function of the plant-microbiome system is the result of contributions from the host plant and microbiome members. In this work we study the function of a simplified community consisting of Pseudomonas and Burkholderia bacterial strains isolated from Populus hosts and inoculated on axenic Populus cutting in controlled laboratory conditions. Inoculation individually with either bacterial isolate increased root growth relative to uninoculated controls. Root area, photosynthetic efficiency, gene expression and metabolite expression data in individual and dual inoculated treatments indicate that the effects of these bacteria are unique and additive, suggesting that the function of a microbiome community may be predicted from the additive functions of the individual members.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exact and efficient hybrid Monte Carlo algorithm for accelerated Bayesian inference of gene expression models from snapshots of single-cell transcripts

Single cells exhibit a significant amount of variability in transcript levels, which arises from slow, stochastic transitions between gene expression states. Elucidating the nature of these states and understanding how transition rates are affected by different regulatory mechanisms require state-of-the-art methods to infer underlying models of gene expression from single cell data. A Bayesian approach to statistical inference is the most suitable method for model selection and uncertainty quantification of kinetic parameters using small data sets. However, this approach is impractical because current algorithms are too slow to handle typical models of gene expression. To solve this problem, we first show that time-dependent mRNA distributions of discrete-state models of gene expression are dynamic Poisson mixtures, whose mixing kernels are characterized by a piecewise deterministic Markov process. Here, we combined this analytical result with a kinetic Monte Carlo algorithm to create a hybrid numerical method that accelerates the calculation of time-dependent mRNA distributions by 1000-fold compared to current methods. We then integrated the hybrid algorithm into an existing Monte Carlo sampler to estimate the Bayesian posterior distribution of many different, competing models in a reasonable amount of time. We demonstrate that kinetic parameters can be reasonably constrained for modestly sampled data sets if the model is known a priori. If there are many competing models, Bayesian evidence can rigorously quantify the likelihood of a model relative to other models from the data. We demonstrate that Bayesian evidence selects the true model and outperforms approximate metrics typically used for model selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Oxygenation influences xylose fermentation and gene expression in the yeast genera Spathaspora and Scheffersomyces

Abstract Background Cost-effective production of biofuels from lignocellulose requires the fermentation of d -xylose. Many yeast species within and closely related to the genera Spathaspora and Scheffersomyces (both of the order Serinales) natively assimilate and ferment xylose. Other species consume xylose inefficiently, leading to extracellular accumulation of xylitol. Xylitol excretion is thought to be due to the different cofactor requirements of the first two steps of xylose metabolism. Xylose reductase (XR) generally uses NADPH to reduce xylose to xylitol, while xylitol dehydrogenase (XDH) generally uses NAD + to oxidize xylitol to xylulose, creating an imbalanced redox pathway. This imbalance is thought to be particularly consequential in hypoxic or anoxic environments. Results We screened the growth of xylose-fermenting yeast species in high and moderate aeration and identified both ethanol producers and xylitol producers. Selected species were further characterized for their XR and XDH cofactor preferences by enzyme assays and gene expression patterns by RNA-Seq. Our data revealed that xylose metabolism is more redox balanced in some species, but it is strongly affected by oxygen levels. Under high aeration, most species switched from ethanol production to xylitol accumulation, despite the availability of ample oxygen to accept electrons from NADH. This switch was followed by decreases in enzyme activity and the expression of genes related to xylose metabolism, suggesting that bottlenecks in xylose fermentation are not always due to cofactor preferences. Finally, we expressed XYL genes from multiple Scheffersomyces species in a strain of Saccharomyces cerevisiae . Recombinant S. cerevisiae expressing XYL1 from Scheffersomyces xylosifermentans , which encodes an XR without a cofactor preference, showed improved anaerobic growth on xylose as the primary carbon source compared to S. cerevisiae strain expressing XYL genes from Scheffersomyces stipitis . Conclusion Collectively, our data do not support the hypothesis that xylitol accumulation occurs primarily due to differences in cofactor preferences between xylose reductase and xylitol dehydrogenase; instead, gene expression plays a major role in response to oxygen levels. We have also identified the yeast Sc. xylosifermentans as a potential source for genes that can be engineered into S. cerevisiae to improve xylose fermentation and biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2015

A lincRNA connected to cell mortality and epigenetically-silenced in most common human cancers

Immortality is an essential characteristic of human carcinoma cells. We recently developed an efficient, reproducible method that immortalizes human mammary epithelial cells (HMEC) in the absence of gross genomic changes by targeting 2 critical senescence barriers. Consistent transcriptomic changes associated with immortality were identified using microarray analysis of isogenic normal finite pre-stasis, abnormal finite post-stasis, and immortal HMECs from 4 individuals. A total of 277 genes consistently changed in cells that transitioned from post-stasis to immortal. Gene ontology analysis of affected genes revealed biological processes significantly altered in the immortalization process. These immortalization-associated changes showed striking similarity to the gene expression changes seen in The Cancer Genome Atlas (TCGA) clinical breast cancer data. The most dramatic change in gene expression seen during the immortalization step was the downregulation of an unnamed, incompletely annotated transcript that we called MORT, for mortality, since its expression was closely associated with the mortal, finite lifespan phenotype. We show here that MORT (ZNF667-AS1) is expressed in all normal finite lifespan human cells examined to date and is lost in immortalized HMEC. MORT gene silencing at the mortal/immortal boundary was due to DNA hypermethylation of its CpG island promoter. This epigenetic silencing is also seen in human breast cancer cell lines and in a majority of human breast tumor tissues. The functional importance of DNA hypermethylation in MORT gene silencing is supported by the ability of 5-aza-2'- deoxycytidine to reactivate MORT expression. Analysis of TCGA data revealed deregulation of MORT expression due to DNA hypermethylation in 15 out of the 17 most common human cancers. In conclusion, the epigenetic silencing of MORT in a large majority of the common human cancers suggests a potential fundamental role in cellular immortalization during human carcinogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Design, execution, and interpretation of plant RNA-seq analyses

Genomics has transformed our understanding of the genetic architecture of traits and the genetic variation present in plants. Here, we present a review of how RNA-seq can be performed to tackle research challenges addressed by plant sciences. We discuss the importance of experimental design in RNA-seq, including considerations for sampling and replication, to avoid pitfalls and wasted resources. Approaches for processing RNA-seq data include quality control and counting features, and we describe common approaches and variations. Though differential gene expression analysis is the most common analysis of RNA-seq data, we review multiple methods for assessing gene expression, including detecting allele-specific gene expression and building co-expression networks. With the production of more RNA-seq data, strategies for integrating these data into genetic mapping pipelines is of increased interest. Finally, special considerations for RNA-seq analysis and interpretation in plants are needed, due to the high genome complexity common across plants. By incorporating informed decisions throughout an RNA-seq experiment, we can increase the knowledge gained.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Evidence for a cytokine-sensitive network of iron-associated genes that protects pancreatic islets against ferroptosis

Background/Objectives: The micronutrient iron is closely connected to inflammation and is among the complex factors contributing to beta-cell failure in diabetes. High levels of dietary iron increase the risk of developing type 2 diabetes, and excessive iron uptake by beta-cells can cause oxidative stress and inhibit function. Elevated levels of proinflammatory cytokines in obese individuals, such as interleukin (IL)-1beta and IL-6, increase the risk of developing type 2 diabetes, and there is evidence that these low levels of circulating cytokines can lead to islet dysfunction. Methods: In this study, gene microarray and other data were analyzed for expression differences in islets treated for 48 h with 10 pg/mL IL-1beta + 20 pg/mL IL-6 as a model of low-grade inflammation versus untreated. Results: Three iron-associated genes were among the most cytokine-sensitive in the mouse genome: Hamp, Steap4, and Lcn2. These proteins are all involved with increasing/retaining cellular iron. We hypothesized that increased cellular iron would lead to increased susceptibility to ferroptosis. Surprisingly, 24 h pre-exposure to low-grade inflammation, which upregulates this iron-gene network, prevented subsequent erastin-induced ferroptosis. We also found that Steap4 overexpression reduced islet dysfunction caused by high-dose proinflammatory cytokines (10× low-dose), suggesting an overall protective effect. Steap4 overexpression also upregulated Hamp and Lcn2, suggesting Steap4 regulates these cytokine-sensitive iron genes.; in contrast, ferritin and ferroportin gene expression, which are not sensitive to cytokines, were unchanged. Conclusions: These data suggest an inflammation-induced network of genes involved in cellular iron uptake and retention plays a protective role in islets against oxidative stress and ferroptosis.

IL-1β↗
DOE OSTI2019

Evolution of the Cell Wall Gene Families of Grasses

Grasses and related commelinid monocot species synthesize cell walls distinct in composition from other angiosperm species. With few exceptions, the genomes of all angiosperms contain the genes that encode the enzymes for synthesis of all cell-wall polysaccharide, phenylpropanoid, and protein constituents known in vascular plants. RNA-seq analysis of transcripts expressed during development of the upper and lower internodes of maize (Zea mays) stem captured the expression of cell-wall-related genes associated with primary or secondary wall formation. High levels of transcript abundances were not confined to genes associated with the distinct walls of grasses but also of those associated with xyloglucan and pectin synthesis. Combined with proteomics data to confirm that expressed genes are translated, we propose that the distinctive cell-wall composition of grasses results from sorting downstream from their sites of synthesis in the Golgi apparatus and hydrolysis of the uncharacteristic polysaccharides and not from differential expression of synthases of grass-specific polysaccharides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types

The identification of good targets is a critical step for the development of targeted therapies for cancer treatment. Here, we used a multi-omics approach to delineate potential targets on chromosome 20q, which frequently shows a complex pattern of DNA copy number amplification in many human cancers suggesting the presence of multiple driver genes. By comparing the amounts of individual mRNAs in cancer from 11 different human tissues with those in their corresponding normal tissues, we identified 18 genes that were robustly elevated across human cancers. Moreover, we found that higher expression levels of a majority of these genes were associated with poor prognosis in many human cancer types. Using DNA copy number and expression data for all 18 genes obtained from The Cancer Genome Atlas project, we discovered that amplification is a major mechanism driving overexpression of these 18 genes in the majority of human cancers. Our integrated analysis suggests that 18 genes on chromosome 20q might serve as novel potential molecular targets for targeted cancer therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Influenza A Experiment ICL102

The purpose of this experiment was to evaluate the human host cellular response to wild-type Influenza A/Anhui/1/2013 (H7N9; "AH1-WT") virus and mutant viruses NS1-L103F/I106M ("AH1-F/M") and partially ferret-adapted ("AH1-691") infection. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) and processed for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Influenza A Experiment ICL103

The purpose of this experiment was to evaluate the human host response to Influenza A wild-type (H5N1) virus and mutant viruses. Sample data was obtained for human lung adenocarcinoma cell line (Calu-3) infected with WT Influenza A/Vietnam/1203/2004 (H5N1, VN1203) and mutant viruses PB2-K627E and NS1-trunc124 for mRNA, miRNA, proteomics, lipidomics, and metabolomics data analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Influenza A Experiment ICL104

The purpose of this experiment was to evaluate the host response to Influenza A pandemic wild-type H1N1 (A/California/04/2009), natural isolate virus. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) with wild-type H1N1 virus (A/California/04/2009) and processed for mRNA, miRNA, proteomics, metabolomics, and lipidomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNaIHH001

The purpose of this experiment was to evaluate the host interferon-stimulated cellular response to interferon alpha (IFNα) treatment. Sample data was obtained from human immortalized human hepatocyte cells (IHH) treated with or without IFNα for mRNA and miRNA transcriptome expression analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNFB001

The purpose of this experiment was to evaluate the human host cellular response to interferon alpha/beta (IFNα/β) or interferon gamma (IFNγ) treatment. Sample data was obtained from primary human lung fibroblast (FB) cells inoculated with IFNα/β or IFNγ for transcriptome analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset download have a direct relationship to a primary sample submission corresponding to a specific interferon response to viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNMVE001

The purpose of this experiment was to evaluate the human host interferon-stimulated cellular response to interferon alpha/beta (IFNα/β) or gamma (INFγ) treatment. Sample data was obtained from primary lung microvascular endothelial cells (MVE) treated with or without human IFNαβ or INFγ for mRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset download have a direct relationship to a primary sample submission corresponding to a specific interferon response to viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Influenza A Experiment IM101

The purpose of this experiment was to evaluate the host mouse response to wild-type Influenza A/Vietnam/1203/2004 (H5N1) virus, Influenza A/California/04/2009 (H1N1) virus, and Influenza A/Vietnam/1203/2004 (H5N1; "PB2-627E" and "NS1trunc124") infection. Sample data was obtained from whole mouse lung and processed for transcriptomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus host infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Influenza A Experiment IM102

The purpose of this experiment was to evaluate the host response to wild-type Influenza A/Anhui/1/2013 (H7N9; "AH1-WT") virus and mutant viruses NS1-103F/106M ("AH1-F/M") and partially ferret-adapted ("AH1-691") infection. Sample data was obtained from mouse lung tissue and processed for mRNA, miRNA, proteomics, metabolomics, and lipidomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Influenza A Experiment IM103

The purpose of this experiment was to evaluate the host response to wild-type Influenza A/Vietnam/1203/2004 (H5N1; "VN1203") virus infection and mock infection. Sample data was obtained for mouse lung tissue and processed for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset download each have a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, MERS-CoV Experiment MCL001

The purpose of this experiment was to evaluate the human host response to wild-type Middle Eastern Respiratory Syndrome coronavirus (icMERS) and icMERS-CoV mutants icMERS-CoV-RFP, icMERS-CoV-dNSP16, icMERS-CoV-d4B, and icMERS-CoV-d3 virus infection. Sample data was obtained from human bronchial epithelial cells (Calu-3 clone 2B4) for mRNA and miRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV virus infection.

59 BASIC BIOLOGICAL SCIENCES↗