Large scale maximum average power multiple inference on time-course count data with application to RNA-seq analysis
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Life Sciences & Biomedicine - Other Topics↗
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RNA‐Seq analysis revealed the molecular mechanisms of photobiomodulation effect on human fibroblasts
Abstract Background The photobiomodulation (PBM) effect has been applied to various clinical therapy for a long time. However, the mechanism related to the PBM effect in terms of wavelengths has been lack of in‐depth study, except that ultraviolet radiation has attracted much attention due to its strong cell‐killing effect. Purpose To clarify the principle behind PBM and the main mechanism of improvement. Methods To carry on this study, we created light equipment using three LED chips, which emit 390 nm ultraviolet radiation, 415 nm blue light and 660 nm red light, respectively. We choose human fibroblasts (HF) to be irradiated by three different wavelengths for PBM test. In this study, we used cell counting kit (CCK‐8) test to show the cell proliferation roughly and reported on a systematic RNA sequencing (RNA‐seq) analysis at transcriptional expression levels from HF, which accepted PBM of different wavelengths of light. Results We found that 415 nm blue light inhibited cell proliferation and 660 nm red light stimulated cell proliferation while 390 nm ultraviolet radiation has little influence on cell proliferation. Furthermore, RNA‐seq results showed that CSF1R, PPP3CC, ITGAL, ITGAM, IL2RB, and several other differentially expressed genes (DEGs) are involved in the cell proliferation. Relative DEGs values for matrix metalloproteinases (MMPs) gene family have shown a great difference in blue and red light radiation especially on MMP25, MMP9, MMP21, and MMP13. Conclusion Taken together, the results provide a valuable resource to describe the variation of HFs under PBM of different light at gene level.
Li, Wenqi↗
A Pipeline for Assessing the Quality of Rna-Seq Datasets in GeneLab
Transcriptome profiling by RNA sequencing (RNA-seq) is a powerful approach to identify gene expression changes in organisms exposed to unique environments such as spaceflight. One of the challenges of evaluating RNA-seq data both within and across different space-relevant studies is the ability to control for technical differences, including the use of different library preparation kits, sequencing platforms, RNA yield, and person-to-person variation. To help address this issue, the National Institute of Standards and Technology (NIST, nist.gov) initiated a consortium, at the request of industry and academia, to develop a set of controls for gene expression measurements. The result was a set of 92 unlabeled, polyadenylated transcripts that range from 250 – 2,000 nucleotides in length to mimic natural eukaryotic mRNAs. These External RNA Controls Consortium (ERCC) genes can be used in any RNA-seq experiment, by adding known concentrations of the ERCC genes to samples after RNA extraction, to offer a standard measurement for data comparison. At NASA GeneLab, we employ these controls as part of our standard operating procedures for every in-house RNA-seq study to assess the limit of detection, dynamic range, and power of differential expression analysis both within and across experiments. Here we will discuss the use, benefits, and limitations of ERCC genes and other types of controls, such as universal RNA references, to generate quality control information for RNA-seq studies conducted at GeneLab.
GeneLab↗
Common 5S rRNA variants are likely to be accepted in many sequence contexts
Over evolutionary time RNA sequences which are successfully fixed in a population are selected from among those that satisfy the structural and chemical requirements imposed by the function of the RNA. These sequences together comprise the structure space of the RNA. In principle, a comprehensive understanding of RNA structure and function would make it possible to enumerate which specific RNA sequences belong to a particular structure space and which do not. We are using bacterial 5S rRNA as a model system to attempt to identify principles that can be used to predict which sequences do or do not belong to the 5S rRNA structure space. One promising idea is the very intuitive notion that frequently seen sequence changes in an aligned data set of naturally occurring 5S rRNAs would be widely accepted in many other 5S rRNA sequence contexts. To test this hypothesis, we first developed well-defined operational definitions for a Vibrio region of the 5S rRNA structure space and what is meant by a highly variable position. Fourteen sequence variants (10 point changes and 4 base-pair changes) were identified in this way, which, by the hypothesis, would be expected to incorporate successfully in any of the known sequences in the Vibrio region. All 14 of these changes were constructed and separately introduced into the Vibrio proteolyticus 5S rRNA sequence where they are not normally found. Each variant was evaluated for its ability to function as a valid 5S rRNA in an E. coli cellular context. It was found that 93% (13/14) of the variants tested are likely valid 5S rRNAs in this context. In addition, seven variants were constructed that, although present in the Vibrio region, did not meet the stringent criteria for a highly variable position. In this case, 86% (6/7) are likely valid. As a control we also examined seven variants that are seldom or never seen in the Vibrio region of 5S rRNA sequence space. In this case only two of seven were found to be potentially valid. The results demonstrate that changes that occur multiple times in a local region of RNA sequence space in fact usually will be accepted in any sequence context in that same local region.
NASA Discipline Exobiology↗
DDX1 regulates alternative splicing and insulin secretion in pancreatic β cells
DEAD-box helicase 1 (DDX1) is a multifunction protein involved in diverse cellular processes including transcription, viral replication, mRNA/miRNA processing, and tRNA splicing. Here, we report a novel function of DDX1 in mRNA alternative splicing in pancreatic β cells. By performing integrated data analysis of high-throughput RNA sequencing (RNA-Seq), and cross-linking and immunoprecipitation coupled with deep sequencing (CLIP-Seq), we identify hundreds of alternative splicing genes that are targeted by DDX1. These DDX1-targeted alternative splicing genes are mainly associated with calcium ion binding, high voltage-gated calcium channel, and transmembrane transporter. Functionally, silencing DDX1 impairs calcium influx and insulin secretion in the pancreatic β cells. These results reveal an important role for DDX1 in the regulation of gene alternative splicing and insulin secretion in pancreatic β cells.
60 APPLIED LIFE SCIENCES↗
Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets
RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.
Lauren M. Sanders↗
The Physcomitrella patens gene atlas project: large-scale RNA-seq based expression data
High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.
59 BASIC BIOLOGICAL SCIENCES↗
Circular RNA expression and circPTPRM promotes proliferation and migration in hepatocellular carcinoma
Circular RNAs (circRNAs) play a critical role during hepatocellular carcinoma (HCC) development. CircRNA PTPRM (circPTPRM) has not been reported to cause disease and its role in HCC is unclear. This study explored circRNA expression and the function of circPTPRM in HCC. RNA sequencing (RNA-seq) was performed on 3 randomly selected pairs of HCC tissues and their corresponding adjacent non-tumor tissues. Three differentially expressed circRNAs, circPTPRM, circSMAD2 and circPTBP3 were selected and verified by real-time quantitative reverse transcription-polymerase chain reactions in 30 pairs of tissue samples, In vitro cultured hepatoma cells, and normal liver cells. Clinical data analysis was performed to select target circRNAs. Anti-target circRNA siRNAs were transfected into hepatoma cell lines, and the biological behavior of hepatoma cells following silencing of the target circRNA were detected by cell proliferation, plate cloning, and transwell assays. There were 86 differentially expressed circRNAs from RNA-seq, of which 53 were significantly upregulated and 33 were significantly downregulated in HCC. CircPTPRM expression was significantly upregulated in HCC tissue (p = 0.023) based on the analysis of 30 paired samples. CircPTPRM expression positively correlated with HCC recurrence and metastasis (p = 0.039). CircPTPRM silencing reduced HCC cell proliferation, migration and invasion. CircRNAs were differentially expressed in HCC samples. CircPTPRM was significantly upregulated in HCC and may function during the tumorigenesis and metastasis of HCC.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Deletion of the GCW13 gene derepresses Gap1-dependent uptake of amino acids in Pichia pastoris grown on methanol as the sole carbon source
Highlights: • Deletion of GCW13 results in an increased growth rate in P. pastoris GS115 on methanol as the sole carbon source. • The intracellular concentrations of various amino acids are increased in the GCW13-deletion P. pastoris strain. • Gcw13 facilitates the endocytosis of Gap1 in P. pastoris GS115 on methanol as the sole carbon source. In Pichia pastoris, most of the Glycosylphosphatidylinositol (GPI)-anchored proteins are of unknown function. Gcw13, one of these GPI-anchored proteins, was found to exert an inhibitory effect on the growth of the histidine auxotrophic P. pastoris strain GS115 on methanol as the sole carbon source. To investigate the biological function of Gcw13, RNA sequencing (RNA-Seq) was performed to compare the difference of gene expression between GS115 and GCW13-deletion strain D13. RNA-Seq analysis showed that, in strain D13, the expression of genes involved in the methanol utilization pathway or peroxisome biogenesis was not changed, and a high proportion of genes involved in the biosynthesis of amino acids were down-regulated, whereas GAP1, which encodes a general amino acid permease, was significantly up-regulated. Besides, the intracellular concentrations of various amino acids were significantly higher in D13 than that in GS115. We also observed that deletion of GCW13 resulted in more Gap1 presented on the cell surface and more active uptake of the toxic proline analogue l-azetidine-2-carboxylate acid (AzC). These results suggest that Gcw13 suppresses the expression of GAP1 and facilitates the endocytosis of Gap1 on methanol, resulting in decreasing Gap1-dependent uptake of amino acids in P. pastoris, which might contribute to the poor growth of GS115 on methanol.
60 APPLIED LIFE SCIENCES↗
Protocol for applying a network-enabled gene discovery pipeline to non-model plant species
Identifying upstream regulators of key genes is essential for understanding gene regulatory mechanisms and translating these insights into functional targets. Here, we present a protocol for applying the network-enabled gene discovery pipeline (NEEDLE) to non-model plant species. We describe steps for environment setup, data preparation, computational analysis, expected outputs, and parameter considerations. NEEDLE integrates RNA sequencing (RNA-seq) processing, weighted gene co-expression analysis (WGCNA), Gene Network Inference with Ensemble of trees (GENIE3), and promoter conservation analysis to prioritize candidate transcriptional regulators.
Plant Sciences↗
Upregulation of a novel LncRNA AC104958.2 stabilized by PCBP2 promotes proliferation and microvascular invasion in hepatocellular carcinoma
Highlights: • AC104958.2 is a novel lncRNA identified to be upregulated in HCC tissues and associated with MVI. • Knockout of AC104958.2 inhibited cell proliferation, invasion, migration and EMT. • AC104958.2 interacted with PCBP2. • PCBP2 was upregulated in HCC and enhanced the RNA stability of AC104958.2. Long non-coding RNAs (lncRNAs) were reported to be involved in tumorigenesis and progression of hepatocellular carcinoma (HCC). Microvascular invasion (MVI) is an independent predictor for early recurrence and overall survival in postoperative patients with HCC. However, the mechanisms how lncRNAs affect HCC and MVI remain elusive. By RNA sequencing (RNA-seq) in a series of 65 HCC samples and 30 paired adjacent non-tumor liver tissue, we identified a novel lncRNA AC104958.2 that was significantly upregulated in HCC tissues and associated with MVI. Overexpression of AC104958.2 obviously elevated cell viability, metastasis, invasion and epithelial-mesenchymal transition (EMT), while knockout of AC104958.2 mediated by CRISPR/Cas9 technique showed the opposite effects. In addition, the interaction between AC104958.2 and Poly (rC) binding protein 2 (PCBP2) was identified by RNA pull down and mass spectrometry (MS), which was further validated by RNA immunoprecipitation (RIP). PCBP2 was also upregulated in HCC and associated with MVI. High expression of both AC104958.2 and PCBP2 was correlated with tumor size, TNM stage and MVI in HCC. Overexpression of PCBP2 greatly increased the cell viability, metastasis, invasion and EMT. Moreover, actinomycin D assay showed that overexpression of PCBP2 enhanced the RNA stability of AC104958.2. In conclusion, our study showed that a novel lncRNA AC104958.2 exerted oncogenic roles in HCC and might be a promising biomarker and therapeutic target.
60 APPLIED LIFE SCIENCES↗
An expanded transcriptome atlas for Bacteroides thetaiotaomicron reveals a small RNA that modulates tetracycline sensitivity
Plasticity in gene expression allows bacteria to adapt to diverse environments. This is particularly relevant in the dynamic niche of the human intestinal tract; however, transcriptional networks remain largely unknown for gut-resident bacteria. Here we apply differential RNA sequencing (RNA-seq) and conventional RNA-seq to the model gut bacterium Bacteroides thetaiotaomicron to map transcriptional units and profile their expression levels across 15 in vivo-relevant growth conditions. We infer stress- and carbon source-specific transcriptional regulons and expand the annotation of small RNAs (sRNAs). Integrating this expression atlas with published transposon mutant fitness data, we predict conditionally important sRNAs. These include MasB, which downregulates tetracycline tolerance. Using MS2 affinity purification and RNA-seq, we identify a putative MasB target and assess its role in the context of the MasB-associated phenotype. These data—publicly available through the Theta-Base web browser (http://micromix.helmholtz-hiri.de/bacteroides/)—constitute a valuable resource for the microbiome community.
59 BASIC BIOLOGICAL SCIENCES↗
Psychosocial experiences are associated with human brain mitochondrial biology
Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these “mind-mitochondria” associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.
59 BASIC BIOLOGICAL SCIENCES↗
Deficiency in transmitter release triggers homeostatic transcriptional changes that increase presynaptic excitability
Weakening of synaptic transmission at theDrosophilalarval neuromuscular junction triggers two forms of homeostatic compensation, one that increases the probability of glutamate release per action potential (P r ) and another that increases motoneuron (MN) activity. We investigated the molecular changes in MNs that underlie the increase in MN activity. RNA sequencing (RNA-seq) analysis on MNs whose glutamate release is weakened by knockdown of components of the MN transmitter release machinery reveals a reduction in expression of a group of genes that encode potassium channels and their positive modulators. These results identify a mechanism of compensation for weakened synaptic transmission by MNs, which engages a transcriptional program in those cells to increase firing and, thereby, ensure sufficient locomotory drive.
Science & Technology - Other Topics↗
Multi-omic Analyses of Extensively Decayed Pinus contorta Reveal Expression of a Diverse Array of Lignocellulose-Degrading Enzymes
Fungi play a key role cycling nutrients in forest ecosystems, but the mechanisms remain uncertain. To clarify the enzymatic processes involved in wood decomposition, the metatranscriptomics and metaproteomics of extensively decayed lodgepole pine were examined by RNA sequencing (RNA-seq) and liquid chromatography-tandem mass spectrometry (LC-MS/MS), respectively. Following de novo metatranscriptome assembly, 52,011 contigs were searched for functional domains and homology to database entries. Contigs similar to basidiomycete transcripts dominated, and many of these were most closely related to ligninolytic white rot fungi or cellulolytic brown rot fungi. A diverse array of carbohydrate-active enzymes (CAZymes) representing a total of 132 families or subfamilies were identified. Among these were 672 glycoside hydrolases, including highly expressed cellulases or hemicellulases. The CAZymes also included 162 predicted redox enzymes classified within auxiliary activity (AA) families. Eighteen of these were manganese peroxidases, which are key components of ligninolytic white rot fungi. The expression of other redox enzymes supported the working of hydroquinone reduction cycles capable of generating reactive hydroxyl radicals. These have been implicated as diffusible oxidants responsible for cellulose depolymerization by brown rot fungi. Finally, enzyme diversity and the coexistence of brown and white rot fungi suggest complex interactions of fungal species and degradative strategies during the decay of lodgepole pine.
59 BASIC BIOLOGICAL SCIENCES↗
Transcriptional Control of hgcAB by an ArsR-Like Regulator in Pseudodesulfovibrio mercurii ND132
The hgcAB gene pair encodes mercury (Hg) methylation capability in a diverse group of microorganisms, but its evolution and transcriptional regulation remain unknown. Working from the possibility that the evolutionary function of HgcAB may not be Hg methylation, we test a possible link to arsenic resistance. Using model Hg methylator Pseudodesulfovibrio mercurii ND132, we evaluated transcriptional control of hgcAB by a putative ArsR encoded upstream and cotranscribed with hgcAB. This regulator shares homology with ArsR repressors of arsenic resistance and S-adenosylhomocysteine (SAH)- responsive regulators of methionine biosynthesis but is distinct from other ArsR/SahR proteins in P. mercurii. Using quantitative PCR (qPCR) and RNA sequencing (RNA-seq) transcriptome analyses, we confirmed this ArsR regulates hgcAB transcription and is responsive to arsenic and SAH. Additionally, RNA-seq indicated a possible link between hgcAB activity and arsenic transformations, with significant upregulation of other ArsRregulated arsenic resistance operons alongside hgcAB. Interestingly, wild-type ND132 was less sensitive to As(V) (but not As(III)) than an hgcAB knockout strain, supporting the idea that hgcAB may be linked to arsenic resistance. Arsenic significantly impacted rates of Hg methylation by ND132; however, responses varied with culture conditions. Differences in growth and metabolic activity did not account for arsenic impacts on methylation. While arsenic significantly increased hgcAB expression, hgcAB gene and transcript abundance was not a good predictor of Hg methylation rates. Taken together, these results support the idea that Hg and As cycling are linked in P. mercurii ND132. Our results may hold clues to the evolution of hgcAB and the controls on Hg methylation in nature. This work reveals a link between microbial mercury methylation and arsenic resistance and may hold clues to the evolution of mercury methylation genes (hgcAB). Microbes with hgcAB produce methylmercury, a strong neurotoxin that readily accumulates in the food web. This study addresses a critical gap in our understanding about the environmental factors that control hgcAB expression. We show that hgcAB expression is controlled by an ArsR-like regulator responsive to both arsenic and S-adenosylhomocysteine in our model organism, Pseudodesulfovibrio mercurii ND132. Exposure to arsenic also significantly impacted Pseudodesulfovibrio mercurii ND132 mercury methylation rates. However, expression of hgcAB was not always a good predictor of Hg methylation rates, highlighting the roles of Hg bioavailability and other biochemical mechanisms in methylmercury production. This study improves our understanding of the controls on hgcAB expression, which is needed to better predict environmental methylmercury production
RNA-seq↗
High throughput single cell multiomics platform [Abstract]
In this collaborative project, PNNL and Scienion will co-develop an integrated microfluidic technology to co-measure the transcriptome and proteome in single cells. The technology will enable us to efficiently separate proteins from mRNA transcripts between two microchips, barcode the molecules, and measure them separately with next-generation sequencing and mass spectrometry, respectively. Multicellular organisms contain diverse cell types and tremendous cell-to-cell heterogeneity that dictates a multitude of biological functions in both physiological and pathological environments. Even in the case of microbes, these genetically identical organisms can randomly differentiate into many subpopulations that assume different roles for the survival of the community. Bulk-scale measurements are insufficient to resolve such complexities. The development and applications of high throughput single-cell omics technologies have transformed our understanding of cellular heterogeneities and their differential responses to internal signaling events or external stimulations. Despite these advances, most current single-cell omic technologies provide information on only one type of biomolecule. Perse, such measurements provide incomplete information because the cell phenotype is determined by multiple layers of biomolecules and the interplay between genome, epigenome, transcriptome, and proteome. For example, mRNA abundance in one cell can not be precisely referred to the corresponding DNA and protein in other cells because of the potential subtle difference in genotype (e.g., somatic mutation or copy number variation) or phenotype (external microenvironment and cell-cell interactions). As such, parallel measurement of multiple biomolecules in the same single cells can offer unique advantages compared with measuring them separately in different single cells. Scienion is a world-leading biotech company focusing on precision liquid handling and its application in single-cell whole-genome sequencing and RNA sequencing. PNNL is the leading institution in ultrasensitive mass spectrometry, microfluidics, and untargeted single-cell proteomics (scProteomics). This collaboration will facilitate a unique fusion between scTranscriptomics capability at Scienion and scProteomics capabilities at PNNL to, for the first time, perform both untargeted transcriptomics and proteomics from the same single cells.
59 BASIC BIOLOGICAL SCIENCES↗
Human Host Cellular Response to HCoV-229E Infection Proteomics (ACS-JM-DP2)
The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5) nuclear extracts, immortalized human lung fibroblasts cells (MRC5) (MOI5) nuclear extracts, and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue and processed for proteome analysis. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files and supporting metadata materials. Experimental proteomics samples were prepared using Limited Proteolysis (LiP) methods for Label-free quantification (LFQ) and global proteomic evaluation. Sample data was acquired using a Q-Exactive HF-X mass spectrometer and was processed and compiled using MaxQuant software (v.1.6.17.0). Processed proteomic data downloads include a sample naming key, processed MaxQuant results/parameters, and protein annotated relative abundance files. See corresponding primary data accessions below and Viral Experiment LiP Analysis source code supporting data transparency and reuse. Experimental transcriptomics samples were collected in parallel and processed for RNA sequencing (RNA-Seq) as summarized under ACS-DP1 (https://data.pnnl.gov/group/nodes/dataset/34069).
59 BASIC BIOLOGICAL SCIENCES↗