Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “transcriptomics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42

A Complex Interplay between Nitric Oxide, Quorum Sensing, and the Unique Secondary Metabolite Tundrenone Constitutes the Hypoxia Response in Methylobacter

Methylobacter species, members of the Methylococcales, have recently emerged as some of the globally widespread, cosmopolitan species that play a key role in the environmental consumption of methane across gradients of dioxygen tensions. In this work, we approached the question of howMethylobacter copes with hypoxia, via laboratory manipulation. Through comparative transcriptomics of cultures grown under high dioxygen partial pressure versus cultures exposed to hypoxia, we identified a gene cluster encoding a hybrid cluster protein along with sensing and regulatory functions. Through mutant analysis, we demonstrated that this gene cluster is involved in the hypoxia stress response. Through additional transcriptomic analyses, we uncovered a complex interconnection between the NO-mediated stress response, quorum sensing, the secondary metabolite tundrenone, and methanol dehydrogenase functions. This novel and complex hypoxia stress response system is so far unique to Methylobacter species, and it may play a role in the environmental fitness of these organisms and in their cosmopolitan environmental distribution.Here, we describe a novel and complex hypoxia response system in a methanotrophic bacterium that involves modules of central carbon metabolism, denitrification, quorum sensing, and a secondary metabolite, tundrenone. This intricate stress response system, so far unique to Methylobacter species, may be responsible for the persistence and activity of these species across gradients of dioxygen tensions and for the cosmopolitan distribution of these organisms in freshwater and soil environments in the Northern Hemisphere, including the fast-melting permafrosts.

59 BASIC BIOLOGICAL SCIENCES↗

A Genome-Scale Atlas Reveals Complex Interplay of Transcription and Translation in an Archaeon

The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation in environmental acclimation are underexplored for organisms of the domain Archaea. Here, we have investigated the scale of post-transcriptional regulation in the extremely halophilic archaeon Halobacterium salinarum NRC-1 by integrating the transcriptome-wide locations of transcript processing sites (TPSs) and SmAP1 binding, the genome-wide locations of antisense RNAs (asRNAs), and the consequences of RNase_2099C knockout on the differential expression of all genes. This integrated analysis has discovered that 54% of all protein-coding genes in the genome of this haloarchaeon are likely targeted by multiple mechanisms for putative post-transcriptional processing and regulation, with about 20% of genes likely being regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (transcriptome sequencing [RNA-Seq]) and protein levels (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry [SWATH-MS]) for 2,579 genes over four phases of batch culture growth in complex medium generated additional evidence for the conditional post-transcriptional regulation of 7% of all protein-coding genes. We demonstrate that post-transcriptional regulation may act to fine-tune specialized and rapid acclimation to stressful environments, e.g., as a switch to turn on gas vesicle biogenesis to promote vertical relocation under anoxic conditions and modulate the frequency of transposition by insertion sequence (IS) elements of the IS200/IS605, IS4, and ISH3 families. Findings from this study are provided as an atlas in a public Web resource (https://halodata.systemsbiology.net).

59 BASIC BIOLOGICAL SCIENCES↗

RNAseq analysis of Cellvibrio japonicus during starch utilization differentiates between genes encoding carbohydrate active enzymes controlled by substrate detection or growth rate

ABSTRACT Bacterial utilization of starch is increasingly of interest as the importance and contributions of animal gut microbiomes become more defined. Consequently, identifying and characterizing the bacterial enzymes responsible for the degradation, transport, and metabolism of starch will enable developments in pharmaceutical, biotechnological, and culinary industries searching for novel prebiotics, carrier molecules, and low glycemic index sweeteners. The current challenge is that bacteria proficient at starch utilization often have hundreds of carbohydrate active enzymes, and it is unclear which are essential for starch utilization using only homology-based bioinformatics or computational methods. Complementary experimental data are also needed, especially to understand the regulation of bacterial starch utilization. We have completed an RNAseq analysis of the Gram-negative bacterium Cellvibrio japonicus and found that it has sophisticated regulation that includes substrate sensing and growth rate components for genes that encode starch-degrading enzymes. Among the 22 genes predicted to encode starch-active enzymes, C. japonicus has 10 alpha-amylases, 4 alpha-glucosidases, 2 pullulnases, and 2 cyclomaltodextrin glucanotransferases, 15 of which were up-regulated during exponential growth on starch and 8 up-regulated in stationary phase. Growth analyses with an enzyme secretion deficient mutant of C. japonicus suggested that secreted amylases are essential for this bacterium to degrade starch. Our approach of coupling a physiological growth assay with transcriptomic data provides a platform to identify targets for further genetic or biochemical analysis that can be broadly applied to other starch-utilizing bacteria. IMPORTANCE Understanding the bacterial metabolism of starch is important as this polysaccharide is a ubiquitous ingredient in foods, supplements, and medicines, all of which influence gut microbiome composition and health. Our RNAseq and growth data set provides a valuable resource to those who want to better understand the regulation of starch utilization in Gram-negative bacteria. These data are also useful as they provide an example of how to approach studying a starch-utilizing bacterium that has many putative amylases by coupling transcriptomic data with growth assays to overcome the potential challenges of functional redundancy. The RNAseq data can also be used as a part of larger meta-analyses to compare how C. japonicus regulates carbohydrate active enzymes, or how this bacterium compares to gut microbiome constituents in terms of starch utilization potential.

59 BASIC BIOLOGICAL SCIENCES↗

How do deer respiratory epithelial cells weather the initial storm of SARS-CoV-2 WA1/2020 strain?

The potential infectivity of severe acute respiratory syndrome associated coronavirus-2 (SARS-CoV-2) in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with the SARS-CoV-2 WA1/2020 strain was assessed throughout 48 h post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to virus infection, with significantly ( P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via interleukin-17 (IL-17) and nuclear factor-κB (NF-κB) signaling pathways. Inhibition of the NF-κB signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans. IMPORTANCE. This study demonstrated that human and white-tailed deer primary respiratory epithelial cells are susceptible to the SARS-CoV-2 WA1/2020 strain infection. However, the comparative transcriptomic analysis revealed that deer cells could limit viral replication without causing hypercytokinemia by downregulating IL-17 and NF-κB signaling pathways. Identifying differentially expressed genes in human and deer cells that modulate key innate immunity pathways during the early infection will lead to developing targeted therapies toward preventing or mitigating the “cytokine storm” often associated with severe cases of coronavirus disease 19 (COVID-19). Moreover, results from this study will aid in identifying novel prognostic biomarkers in predicting SARS-CoV-2 adaption and transmission in deer and associated cervids.

60 APPLIED LIFE SCIENCES↗

A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan–Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment.

60 APPLIED LIFE SCIENCES↗

Metabolites Annotations and Genes Integrated (MAGI) v1.0

With the benefit of hindsight, it is easy to see that the readout of the human genome, spectacular milestone that it was, represents only the beginning of the "omics" information explosion. The technical side of the 'omics explosion--enabling researchers to efficiently readout terabytes of information spelling out whole genomes, transcriptomes, proteomes and metabolomes, does not per se provide a clear picture of how life works. Nor does it show us how we can engineer biology to solve the grand challenges of the 21st century: feeding 10 billion people with declining per capita supplies of arable land and clean water, sustaining biological diversity and slowing the increase in greenhouse gas formation, primarily carbon dioxide and methane. The 2017-063 invention--Metabolites and Genes Integration Technology--proposes an integrated approach to correcting and connecting the dots of the 'omics explosion: linking genes to proteins, proteins to pathways, pathways to biochemical reactions and metabolites. The '063 invention is potentially transformational in that it can generate testable hypotheses across thousands of genes to predict their chemical and metabolic products. It can also do the reverse; i.e., starting from chemical and metabolic products it can generate testable hypotheses about which genes and pathways those molecules are linked to. Since we know that genomic, transcriptomic, proteomic and metabolomic databases are chock full or erroneous information, MAGI also has the unique benefit of correcting these errors through its own independent pathway of bidirectional hypothesis generation (genes=>proteins=>metabolites + metabolites=>proteins=>genes). Perfectly amenable to high-throughput hypothesis generation and experimentation, MAGI can transform our understanding of human, animal, plant and microbial biology over several decades, laying the essential knowledge foundation to addressing the grand scientific challenges of the 21st century.

Bowen, Benjamin↗

Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AML

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemic cells with diverse mutation spectra, which eventually leads to disease relapse. This genetic heterogeneity drives the activation of complex signaling pathways that is reflected at the protein level. This diversity makes it difficult to treat AML with targeted therapy, requiring custom patient treatment protocols tailored to each individual’s leukemia. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify genomic signatures that could predict patient-specific drug responses. However, there are inherent weaknesses in using only genetic and transcriptomic measurements as surrogates of drug response, particularly the absence of direct information about phosphorylation-mediated signal transduction. As a member of the Clinical Proteomic Tumor Analysis Consortium, we have extended the molecular characterization of this cohort by collecting proteomic and phosphoproteomic measurements from a subset of these patient samples (38 in total) to evaluate the hypothesis that proteomic signatures can improve the ability to predict response to 26 drugs in AML ex vivo samples. In this work we describe our systematic, multi-omic approach to evaluate proteomic signatures of drug response and compare protein levels to other markers of drug response such as mutational patterns. We explore the nuances of this approach using two drugs that target key pathways activated in AML: quizartinib (FLT3) and trametinib (Ras/MEK), and show how patient-derived signatures can be interpreted biologically and validated in cell lines. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to assess drug sensitivity in AML.

60 APPLIED LIFE SCIENCES↗

Transplatformer: translating toxicogenomic profiles between generations of platforms

Background Transcriptomic profiling technologies have advanced the analysis of biological and toxicological responses. However, substantial differences in probe design, dynamic range, gene coverage, and preprocessing pipelines across platforms introduce artifacts that limit cross-study integration and hinder the reuse of historical datasets. We aim to develop computational methods for accurate cross-platform translation to maximize the value of legacy resources. Results We present TransPlatformer a deep learning framework for translating gene expression profiles across heterogeneous toxicogenomics platforms. TransPlatformer employs a novel attention-based architecture to map high-dimensional fold-change vectors from legacy microarray technologies to current platforms. Models are trained and evaluated using DrugMatrix, spanning three technological generations. We investigate mixed-tissue, single-tissue, and cross-tissue training paradigms and benchmark performance against multilayer perceptron and matrix-completion baselines. In mixed-tissue training, TransPlatformer achieves a greater than 50% reduction in mean absolute error (0.043 vs. 0.09) and nearly doubles Pearson correlation ( ≈ 0.71 vs. 0.37) relative to baseline methods. Importantly, TransPlatformer preserves rare but biologically meaningful over- and under-expressed signals, with mean absolute error below 0.22. Single-tissue models yield further improvements for well-represented organs, such as a 10% reduction in liver mean absolute error, while underscoring the need for data augmentation strategies in low-sample tissues.ra Conclusions TransPlatformer provides an effective and scalable computational solution for cross-platform transcriptomic translation. By enabling biologically faithful harmonization of gene expression data, the proposed approach facilitates the reuse of legacy toxicogenomics datasets, enhances downstream biomarker discovery, and supports more reproducible predictive modeling in toxicology.

59 BASIC BIOLOGICAL SCIENCES↗

Deletion of either the regulatory gene ara1 or metabolic gene xki1 in Trichoderma reesei leads to increased CAZyme gene expression on crude plant biomass

Background:Trichoderma reesei is one of the major producers of enzymes for the conversion of plant biomass to sustainable fuels and chemicals. Crude plant biomass can induce the production of CAZymes in T. reesei, but there is limited understanding of how the transcriptional response to crude plant biomass is regulated. In addition, it is unknown whether induction on untreated recalcitrant crude plant biomass (with a large diversity of inducers) can be sustained for longer. We investigated the transcriptomic response of T. reesei to the two industrial feedstocks, corn stover (CS) and soybean hulls (SBH), over time (4 h, 24 h and 48 h), and its regulatory basis using transcription factor deletion mutants (Δxyr1 and Δara1). We also investigated whether deletion of a xylulokinase gene (Δxki1) from the pentose catabolic pathway that converts potential inducers could lead to increased CAZyme gene expression. Results:By analyzing the transcriptomic responses using clustering as well as differential and cumulative expression of plant biomass degrading CAZymes, we found that corn stover induced a broader range and higher expression of CAZymes in T. reesei, while SBH induced more pectinolytic and mannanolytic transcripts. XYR1 was the major TF regulating CS utilization, likely due to the significant amount of d-xylose in this substrate. In contrast, ARA1 had a stronger effect on SBH utilization, which correlates with a higher abundance of l-arabinose in SBH that activates ARA1. Blocking pentose catabolism by deletion of xki1 led to higher expression of CAZyme encoding genes on both substrates at later time points. Surprisingly, this was also observed for Δara1 at later time points. Many of these genes were XYR1 regulated, suggesting that inducers for this regulator accumulated over time on both substrates. Conclusion:Our data demonstrates the complexity of the regulatory system related to plant biomass degradation in T. reesei and the effect the feedstock composition has on this. Furthermore, this dataset provides leads to improve the efficiency of a T. reesei enzyme cocktail, such as by the choice of substrate or by deleting xki1 to obtain higher production of plant biomass degrading CAZymes.

09 BIOMASS FUELS↗

Data for Development of Vegetative Oil Sorghum: From Lab-to-Field

Biomass crops engineered to accumulate energy-dense triacylglycerols (TAG or ‘vegetable oils’) in their vegetative tissues have emerged as potential feedstocks to meet the growing demand for renewable diesel and sustainable aviation fuel (SAF). Unlike oil palm and oilseed crops, the current commercial sources of TAG, vegetative tissues, such as leaves and stems, only transiently accumulate TAG. In this report, we used grain (Texas430 or TX430) and sugar-accumulating ‘sweet’ (Ramada) genotypes of sorghum, a high-yielding, environmentally resilient biomass crop, to accumulate TAG in leaves and stems. We initially tested several gene combinations for a ‘push-pull-protect’ strategy. The top TAG-yielding constructs contained five oil transgenes for a sorghum WRINKLED1 transcription factor (‘push’), a Cuphea viscosissima diacylglycerol acyltransferase (DGAT; ‘pull’), a modified sesame oleosin (‘protect’) and two combinations of specialized Cuphea lysophosphatidic acid acyltransferases and medium-chain acyl-acyl carrier protein thioesterases. Though intended to generate oils with medium-chain fatty acids, engineered lines accumulated oleic acid-rich oil to amounts of up to 2.5% DW in leaves and 2.0% DW in stems in the greenhouse, 36-fold and 49-fold increases relative to wild-type (WT) plants, respectively. Under field conditions, the top-performing event accumulated TAG to amount to 5.5% DW in leaves and 3.5% DW in stems, 78-fold and 58-fold increases, respectively, relative to WT TX430. Transcriptomic and fluxomic analyses revealed potential bottlenecks for increased TAG accumulation. Overall, our studies highlight the utility of a lab-to-field pipeline coupled with systems biology studies to deliver high vegetative oil sorghum for SAF and renewable diesel production.

Biofuels↗

Data for Creating Yellow Seed Camelina sativa with Enhanced Oil Accumulation by CRISPR-Mediated Disruption of Transparent Testa 8

Camelina ( Camelina sativa L.), a hexaploid member of the Brassicaceae family, is an emerging oilseed crop being developed to meet the increasing demand for plant oils as biofuel feedstocks. In other Brassicas, high oil content can be associated with a yellow seed phenotype, which is unknown for camelina. We sought to create yellow seed camelina using CRISPR/Cas9 technology to disrupt its Transparent Testa 8 (TT8) transcription factor genes and to evaluate the resulting seed phenotype. We identified three TT8 genes, one in each of the three camelina subgenomes, and obtained independent CsTT8 lines containing frameshift edits. Disruption of TT8 caused seed coat colour to change from brown to yellow reflecting their reduced flavonoid accumulation of up to 44%, and the loss of a well-organized seed coat mucilage layer. Transcriptomic analysis of CsTT8-edited seeds revealed significantly increased expression of the lipid-related transcription factors LEC1, LEC2, FUS3, and WRI1 and their downstream fatty acid synthesis-related targets. These changes caused metabolic remodelling with increased fatty acid synthesis rates and corresponding increases in total fatty acid (TFA) accumulation from 32.4% to as high as 38.0% of seed weight, and TAG yield by more than 21% without significant changes in starch or protein levels compared to parental line. These data highlight the effectiveness of CRISPR in creating novel enhanced-oil germplasm in camelina. The resulting lines may directly contribute to future net-zero carbon energy production or be combined with other traits to produce desired lipid-derived bioproducts at high yields.

Biofuels↗

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. Moreover, we discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

59 BASIC BIOLOGICAL SCIENCES↗

Learning genetic perturbation effects with variational causal inference

Advances in sequencing technologies have enhanced the understanding of gene regulation in cells. In particular, Perturb-seq has enabled high-resolution profiling of the transcriptomic response to genetic perturbations at the single-cell level. This understanding has implications in functional genomics and potentially for identifying therapeutic targets. Various computational models have been developed to predict perturbational effects. While deep learning models excel at interpolating observed perturbational data, they tend to overfit in the lack of enough data and may not generalize well to unseen perturbations. In contrast, mechanistic models, such as linear causal models based on gene regulatory networks, hold greater potential for extrapolation, as they encapsulate regulatory information that can predict responses to unseen perturbations. However, their application has been limited to small studies due to overly simplistic assumptions, making them less effective in handling noisy, large-scale single-cell data. We propose a hybrid approach that combines a mechanistic causal model with variational deep learning, termed Single Cell Causal Variational Autoencoder (SCCVAE). The mechanistic model employs a learned regulatory network to represent perturbational changes as shift interventions that propagate through the learned network. SCCVAE integrates this mechanistic causal model into a variational autoencoder, generating rich, comprehensive transcriptomic responses. Our results indicate that SCCVAE exhibits superior performance over current state-of-the-art baselines for extrapolating to predict unseen perturbational responses. Additionally, for the observed perturbations, the latent space learned by SCCVAE allows for the identification of functional perturbation modules and simulation of single-gene knockdown experiments of varying penetrance, presenting a robust tool for interpreting and interpolating perturbational responses at the single-cell level.

59 BASIC BIOLOGICAL SCIENCES↗

Systems biology analysis of Zymomonas mobilis ZM4 ethanol stress responses

Zymomonas mobilis ZM4 is a capable ethanogenic bacterium with high ethanol productivity and high level of ethanol tolerance. Previous studies indicated that several stress-related proteins and changes in the ZM4 membrane lipid composition may contribute to ethanol tolerance. However, the molecular mechanisms of ethanol stress response have not been elucidated fully. In this study, ethanol stress responses were investigated using systems biology tools. Medium supplementation with an initial 47.3 g/L (6% v/v) ethanol reduced Z. mobilis ZM4 glucose consumption, growth rate and ethanol productivity compared to that of untreated controls. Metabolomic profiling showed that ethanol-treated ZM4 cells accumulated greater amounts of glycerol during the entire fermentation process, which may indicate an important role for this metabolite. A proteomic analysis of early exponential growth identified about one thousand proteins, or approximately 56% of the predicted ZM4 proteome. Proteins related to metabolism and stress response such as chaperones and key regulators were more abundant in the early ethanol stress condition. Transcriptomic studies indicated the response of ZM4 to ethanol is dynamic, complex and involves many genes from all the different functional categories. There were fewer genes significantly differentially expressed in the exponential phase compared to that of stationary phase and early stationary phase. Most down-regulated genes were related to translation and ribosome biogenesis, while the ethanol-upregulated genes were mostly related to cellular processes and metabolism. Correlations among the transcriptomics, proteomics and metabolism were examined and among significantly expressed genes or proteins, we observe higher correlation coefficients when fold-change values are higher. This systems biology study elucidates key Z. mobilis ZM4 metabolites, genes and proteins that form the foundation of its distinctive physiology and its multifaceted response to ethanol stress.

BESC LDRD↗

Deep RNA Sequencing Reveals Hidden Features and Dynamics of Early Gene Transcription in Paramecium bursaria Chlorella Virus 1

Paramecium bursaria chlorella virus 1 (PBCV-1) is the prototype of the genus Chlorovirus (family Phycodnaviridae) that infects the unicellular, eukaryotic green alga Chlorella variabilis NC64A. The 331-kb PBCV-1 genome contains 416 major open reading frames. A mRNA-seq approach was used to analyze PBCV-1 transcriptomes at 6 progressive times during the first hour of infection. The alignment of 17 million reads to the PBCV-1 genome allowed the construction of single-base transcriptome maps. Significant transcription was detected for a subset of 50 viral genes as soon as 7 min after infection. By 20 min post infection (p.i.), transcripts were detected for most PBCV-1 genes and transcript levels continued to increase globally up to 60 min p.i., at which time 41% or the poly (A+)-containing RNAs in the infected cells mapped to the PBCV-1 genome. For some viral genes, the number of transcripts in the latter time points (20 to 60 min p.i.) was much higher than that of the most highly expressed host genes. RNA-seq data revealed putative polyadenylation signal sequences in PBCV-1 genes that were identical to the polyadenylation signal AAUAAA of green algae. Several transcripts have an RNA fragment excised. However, the frequency of excision and the resulting putative shortened protein products suggest that most of these excision events have no functional role but are probably the result of the activity of misled splicesomes.

59 BASIC BIOLOGICAL SCIENCES↗

Transcription Start Site Associated RNAs (TSSaRNAs) Are Ubiquitous in All Domains of Life

A plethora of non-coding RNAs has been discovered using high-resolution transcriptomics tools, indicating that transcriptional and post-transcriptional regulation is much more complex than previously appreciated. Small RNAs associated with transcription start sites of annotated coding regions (TSSaRNAs) are pervasive in both eukaryotes and bacteria. Here, we provide evidence for existence of TSSaRNAs in several archaeal transcriptomes including: Halobacterium salinarum, Pyrococcus furiosus, Methanococcus maripaludis, and Sulfolobus solfataricus. We validated TSSaRNAs from the model archaeon Halobacterium salinarum NRC-1 by deep sequencing two independent small-RNA enriched (RNA-seq) and a primary-transcript enriched (dRNA-seq) strand-specific libraries. We identified 652 transcripts, of which 179 were shown to be primary transcripts (~7% of the annotated genome). Distinct growth-associated expression patterns between TSSaRNAs and their cognate genes were observed, indicating a possible role in environmental responses that may result from RNA polymerase with varying pausing rhythms. This work shows that TSSaRNAs are ubiquitous across all domains of life.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular and Cellular Characterization of a Zebrafish Optic Pathway Tumor Line Implicates Glia-Derived Progenitors in Tumorigenesis

In this study we describe the molecular and cellular characterization of a zebrafish mutant that develops tumors in the optic pathway. Heterozygous Tg(flk1:RFP)is18 transgenic adults develop tumors of the retina, optic nerve and optic tract. Molecular and genetic mapping demonstrate the tumor phenotype is linked to a high copy number transgene array integrated in the lincRNA gene lincRNAis18/ Zv9_00007276 on chromosome 3. TALENs were used to isolate a 147kb deletion allele that removes exons 2–5 of the lincRNAis18 gene. Deletion allele homozygotes are viable and do not develop tumors, indicating loss of function of the lincRNAis18 locus is not the trigger for tumor onset. Optic pathway tumors in the Tg(flk1:RFP)is18 mutant occur with a penetrance of 80–100% by 1 year of age. The retinal tumors are highly vascularized and composed of rosettes of various sizes embedded in a fibrous matrix. Immunohistochemical analysis showed increased expression of the glial markers GFAP and BLBP throughout retinal tumors and in dysplastic optic nerve. We performed transcriptome analysis of pre-tumorous retina and retinal tumor tissue and found changes in gene expression signatures of radial glia and astrocytes (slc1a3), activated glia (atf3, blbp, apoeb), proliferating neural progenitors (foxd3, nestin, cdh2, her9/hes1), and glioma markers (S100b, vim). The transcriptome also revealed activation of cAMP, Stat3 and Wnt signal transduction pathways. qRT-PCR confirmed .10-fold overexpression of the Wnt pathway components hbegfa, ascl1a, and insm1a. Together the data indicate Mu¨ ller glia and/or astrocyte-derived progenitors could contribute to the zebrafish Tg(flk1:RFP)is18 optic pathway tumors.

59 BASIC BIOLOGICAL SCIENCES↗

Persistent Foot-and-Mouth Disease Virus Infection in the Nasopharynx of Cattle; Tissue-Specific Distribution and Local Cytokine Expression

Tissues obtained post-mortem from cattle persistently infected with foot-and-mouth disease virus (FMDV) were analyzed to characterize the tissue-specific localization of FMDV and partial transcriptome profiles for selected immunoregulatory cytokines. Analysis of 28 distinct anatomic sites from 21 steers infected with FMDV serotype A, O or SAT2, had the highest prevalence of overall viral detection in the dorsal nasopharynx (80.95%) and dorsal soft palate (71.43%). FMDV was less frequently detected in laryngeal mucosal tissues, oropharyngeal mucosal sites, and lymph nodes draining the pharynx. Immunomicroscopy indicated that within persistently infected mucosal tissues, FMDV antigens were rarely detectable within few epithelial cells in regions of mucosa-associated lymphoid tissue (MALT). Transcriptome analysis of persistently infected pharyngeal tissues by qRT-PCR for 14 cytokine genes indicated a general trend of decreased mRNA levels compared to uninfected control animals. Although, statistically significant differences were not observed, greatest suppression of relative expression (RE) was identified for IP-10 (RE = 0.198), IFN-β (RE = 0.269), IL-12 (RE = 0.275), and IL-2 (RE = 0.312). Increased relative expression was detected for IL-6 (RE = 2.065). Overall, this data demonstrates that during the FMDV carrier state in cattle, viral persistence is associated with epithelial cells of the nasopharynx in the upper respiratory tract and decreased levels of mRNA for several immunoregulatory cytokines in the infected tissues.

59 BASIC BIOLOGICAL SCIENCES↗