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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dual-RNA-sequencing to elucidate the interactions between sorghum and Colletotrichum sublineola

In warm and humid regions, the productivity of sorghum is significantly limited by the fungal hemibiotrophic pathogen Colletotrichum sublineola , the causal agent of anthracnose, a problematic disease of sorghum ( Sorghum bicolor (L.) Moench) that can result in grain and biomass yield losses of up to 50%. Despite available genomic resources of both the host and fungal pathogen, the molecular basis of sorghum− C. sublineola interactions are poorly understood. By employing a dual-RNA sequencing approach, the molecular crosstalk between sorghum and C. sublineola can be elucidated. In this study, we examined the transcriptomes of four resistant sorghum accessions from the sorghum association panel (SAP) at varying time points post-infection with C. sublineola . Approximately 0.3% and 93% of the reads mapped to the genomes of C. sublineola and Sorghum bicolor , respectively. Expression profiling of in vitro versus in planta C. sublineola at 1-, 3-, and 5-days post-infection (dpi) indicated that genes encoding secreted candidate effectors, carbohydrate-active enzymes (CAZymes), and membrane transporters increased in expression during the transition from the biotrophic to the necrotrophic phase (3 dpi). The hallmark of the pathogen-associated molecular pattern (PAMP)-triggered immunity in sorghum includes the production of reactive oxygen species (ROS) and phytoalexins. The majority of effector candidates secreted by C. sublineola were predicted to be localized in the host apoplast, where they could interfere with the PAMP-triggered immunity response, specifically in the host ROS signaling pathway. The genes encoding critical molecular factors influencing pathogenicity identified in this study are a useful resource for subsequent genetic experiments aimed at validating their contributions to pathogen virulence. This comprehensive study not only provides a better understanding of the biology of C. sublineola but also supports the long-term goal of developing resistant sorghum cultivars.

Vela, Saddie↗
DOE OSTI2022

Single-cell RNA-Seq reveals changes in immune landscape in post-traumatic osteoarthritis

Osteoarthritis (OA) is the most common joint disease, affecting over 300 million people world-wide. Accumulating evidence attests to the important roles of the immune system in OA pathogenesis. Understanding the role of various immune cells in joint degeneration or joint repair after injury is vital for improving therapeutic strategies for treating OA. Post-traumatic osteoarthritis (PTOA) develops in ~50% of individuals who have experienced an articular trauma like an anterior cruciate ligament (ACL) rupture. Here, using the high resolution of single-cell RNA sequencing, we delineated the temporal dynamics of immune cell accumulation in the mouse knee joint after ACL rupture. Our study identified multiple immune cell types in the joint including neutrophils, monocytes, macrophages, B cells, T cells, NK cells and dendritic cells. Monocytes and macrophage populations showed the most dramatic changes after injury. Further characterization of monocytes and macrophages reveled 9 major subtypes with unique transcriptomics signatures, including a tissue resident Lyve1 hi Folr2 hi macrophage population and Trem2 hi Fcrls + recruited macrophages, both showing enrichment for phagocytic genes and growth factors such as Igf1 , Pdgfa and Pdgfc. We also identified several genes induced or repressed after ACL injury in a cell type-specific manner. This study provides new insight into PTOA-associated changes in the immune microenvironment and highlights macrophage subtypes that may play a role in joint repair after injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine

The domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases. In this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets. We test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas. The results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Metabolome and RNA-seq Analysis of Responses to Nitrogen Deprivation and Resupply in Tea Plant (Camellia sinensis) Roots

Nitrogen (N) is an important contributor in regulating plant growth and development as well as secondary metabolites synthesis, so as to promote the formation of tea quality and flavor. Theanine, polyphenols, and caffeine are important secondary metabolites in tea plant. In this study, the responses of Camellia sinensis roots to N deprivation and resupply were investigated by metabolome and RNA-seq analysis. N deficiency induced content increase for most amino acids (AAs) and reduction for the remaining AAs, polyphenols, and caffeine. After N recovery, the decreased AAs and polyphenols showed a varying degree of recovery in content, but caffeine did not. Meanwhile, theanine increased in content, but its related synthetic genes were down-regulated, probably due to coordination of the whole N starvation regulatory network. Flavonoids-related pathways were relatively active following N stress according to KEGG enrichment analysis. Gene co-expression analysis revealed TCS2 , AMT1;1 , TAT2 , TS , and GOGAT as key genes, and TFs like MYB, bHLH, and NAC were also actively involved in N stress responses in C. sinensis roots. These findings facilitate the understanding of the molecular mechanism of N regulation in tea roots and provide genetic reference for improving N use efficiency in tea plant.

Xu, Wenluan↗
DOE OSTI2024

CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal

In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis. However, generating such multimodal data is technically challenging and expensive, leading to limited availability of single-cell co-assay data. Here, we propose a model for cross-modal prediction between the transcriptome and chromatin profiles in single cells. Our model is based on a deep neural network architecture that learns the latent representations from the source modality and then predicts the target modality. It demonstrates reliable performance in accurately translating between these modalities across multiple paired human scATAC-seq and scRNA-seq datasets. Additionally, we developed CrossMP, a web-based portal allowing researchers to upload their single-cell modality data through an interactive web interface and predict the other type of modality data, using high-performance computing resources plugged at the backend.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Coupling Environmental Whole Mixture Toxicity Screening with Unbiased RNA-Seq Reveals Site-Specific Biological Responses in Zebrafish

Passive sampling device (PSD) extracts paired with developmental toxicity assays in Danio Rerio (zebrafish) are excellent sensors for whole mixture toxicity associated with the bioavailable non-polar organics at environmental sites. We expand this concept by incorporating RNA-Seq in 48-h post fertilization zebrafish statically exposed to PSD extracts from two Portland Harbor Superfund Site locations: river mile 6.5W (RM 6.5W) and river mile 7W (RM 7W). RM 6.5W contained higher concentrations of polycyclic aromatic hydrocarbons (PAHs), but the diagnostic ratios of both extracts indicated similar PAH sourcing and composition. Developmental screens determined RM 6.5W to be more toxic with the most sensitive endpoint being a “wavy” notochord malformation. Differential gene expression from exposure to both extracts was largely parallel, although more pronounced for RM 6.5W. When compared to the gene expression associated with individual chemical exposures, PSD extracts produced some gene signatures parallel to PAHs but were more closely matched by oxygenated-PAHs. Additionally, differential expression, reminiscent of the wavy notochord phenotype, was not accounted for by either class of chemical, indicating the potential of other contaminants driving mixture toxicity. These techniques offer a compelling method for non-targeted hazard characterization of whole mixtures in an in vivo vertebrate system without requiring complete chemical characterization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Deletion of an African Swine Fever Virus ATP-Dependent RNA Helicase QP509L from the Highly Virulent Georgia 2010 Strain Does Not Affect Replication or Virulence

African swine fever virus (ASFV) produces a lethal disease (ASF) in domestic pigs, which is currently causing a pandemic deteriorating pig production across Eurasia. ASFV is a large and structurally complex virus with a large genome harboring more than 150 genes. ASFV gene QP509L has been shown to encode for an ATP-dependent RNA helicase, which appears to be important for efficient virus replication. Here, we report the development of a recombinant virus, ASFV-G-ΔQP509L, having deleted the QP509L gene in the highly virulent field isolate ASFV Georgia 2010 (ASFV-G). It is shown that ASFV-G-ΔQP509L replicates in primary swine macrophage cultures as efficiently as the parental virus ASFV-G. In addition, the experimental inoculation of pigs with 10 2 HAD 50 by the intramuscular route produced a slightly protracted but lethal clinical disease when compared to that of animals inoculated with virulent parental ASFV-G. Viremia titers in animals infected with ASFV-G-ΔQP509L also had slightly protracted kinetics of presentation. Therefore, ASFV gene QP509L is not critical for the processes of virus replication in swine macrophages, nor is it clearly involved in virus replication and virulence in domestic pigs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Natural variation in the consequences of gene overexpression during osmotic stress [RNA-Seq]

RNA-seq and transcriptome analysis of 4 strains (BY4743, BC187, NCYC3290, and YPS128) that were grown in YPD+ 0.7M NaCl. For each strain, 3 samples were collected: T0 (unstressed cells), T30 (30 mins after cells placed in 0.7M NaCl), and T3h (3 hours after cells placed in NaCl). These strains were collected in 3 biological replicates. The library for sample YPS128 Rep 3 T30 failed so this sample is missing and there are a total of 35 samples in the dataset.

copy-number variation↗
NASA NTRS1971

GLC analysis of base composition of RNA and DNA hydrolysates

Various methods used for the analysis of the base composition of RNA and DNA hydrolysates are presented. The methods discussed are: (1) ion-exchange chromatography, (2) paper chromatography, (3) paper electrophoresis, (4) thin layer chromatography, (5) paper chromatography and time of flight mass spectrometry, and (6) gas-liquid chromatography. The equipment required and the conditions for obtaining the best results with each method are described.

Lakings, D. B.↗