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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

ACTINN: automated identification of cell types in single cell RNA sequencing

Abstract Motivation Cell type identification is one of the major goals in single cell RNA sequencing (scRNA-seq). Current methods for assigning cell types typically involve the use of unsupervised clustering, the identification of signature genes in each cluster, followed by a manual lookup of these genes in the literature and databases to assign cell types. However, there are several limitations associated with these approaches, such as unwanted sources of variation that influence clustering and a lack of canonical markers for certain cell types. Here, we present ACTINN (Automated Cell Type Identification using Neural Networks), which employs a neural network with three hidden layers, trains on datasets with predefined cell types and predicts cell types for other datasets based on the trained parameters. Results We trained the neural network on a mouse cell type atlas (Tabula Muris Atlas) and a human immune cell dataset, and used it to predict cell types for mouse leukocytes, human PBMCs and human T cell sub types. The results showed that our neural network is fast and accurate, and should therefore be a useful tool to complement existing scRNA-seq pipelines. Availability and implementation The codes and datasets are available at https://figshare.com/articles/ACTINN/8967116. Tutorial is available at https://github.com/mafeiyang/ACTINN. All codes are implemented in python. Supplementary information Supplementary data are available at Bioinformatics online.

Ma, Feiyang (ORCID:0000000262600787)↗
DOE OSTI2018

A method to improve prediction of secondary structure for large single RNA sequences

The function of a particular RNA molecule within an organic system is principally determined by its structure. The current physical methods available for structure determination are time consuming and expensive. Hence, computational methods for structure prediction are often used. }The prediction of the structure of a large single sequence of RNA needs a lot of research work. In the present work, a method is introduced to improve the prediction of large single sequence RNA secondary structure obtained by Mfold program using the concept of minimum free energy. The Mfold program contains a constraint option that allows forcing some helices in the predicted structure. In our method, some of the firstly formed hairpins that are expected, by a statistical study, to be present in the real structure are forced in the Mfold predicted structure. The results show improvement, toward the real structure, in the Mfold predicted structure and this gives evidence to the RNA kinetic folding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Application of small RNA sequencing to identify microRNAs in acute kidney injury and fibrosis

Establishing a microRNA (miRNA) expression profile in affected tissues provides an important foundation for the discovery of miRNAs involved in the development or progression of pathologic conditions. We conducted small RNA sequencing to generate a temporal profile of miRNA expression in the kidneys using a mouse model of folic acid-induced (250 mg/kg i.p.) kidney injury and fibrosis. From the 103 miRNAs that were differentially expressed over the time course (> 2-fold, p < 0.05), we chose to further investigate miR-18a-5p, which is expressed during the acute stage of the injury; miR-132-3p, which is upregulated during transition between acute and fibrotic injury; and miR-146b-5p, which is highly expressed at the peak of fibrosis. Using qRT-PCR, we confirmed the increased expression of these candidate miRNAs in the folic acid model as well as in other established mouse models of acute injury (ischemia/reperfusion injury) and fibrosis (unilateral ureteral obstruction). In situ hybridization confirmed high expression of miR-18a-5p, miR-132-3p and miR-146b-5p throughout the kidney cortex in mice and humans with severe kidney injury or fibrosis. When primary human proximal tubular epithelial cells were treated with model nephrotoxicants such as cadmium chloride (CdCl{sub 2}), arsenic trioxide, aristolochic acid (AA), potassium dichromate (K{sub 2}Cr{sub 2}O{sub 7}) and cisplatin, miRNA-132-3p was upregulated 4.3-fold after AA treatment and 1.5-fold after K{sub 2}Cr{sub 2}O{sub 7} and CdCl{sub 2} treatment. These results demonstrate the application of temporal small RNA sequencing to identify miR-18a, miR-132 and miR-146b as differentially expressed miRNAs during distinct phases of kidney injury and fibrosis progression. - Highlights: • We used small RNA sequencing to identify differentially expressed miRNAs in kidney. • Distinct patterns were found for acute injury and fibrotic stages in the kidney. • Upregulation of miR-18a, -132 and -146b was confirmed in mice and human kidneys.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

RNA Sequencing Identifies New RNase III Cleavage Sites in Escherichia coli and Reveals Increased Regulation of mRNA

ABSTRACT Ribonucleases facilitate rapid turnover of RNA, providing cells with another mechanism to adjust transcript and protein levels in response to environmental conditions. While many examples have been documented, a comprehensive list of RNase targets is not available. To address this knowledge gap, we compared levels of RNA sequencing coverage of Escherichia coli and a corresponding RNase III mutant to expand the list of known RNase III targets. RNase III is a widespread endoribonuclease that binds and cleaves double-stranded RNA in many critical transcripts. RNase III cleavage at novel sites found in aceEF , proP , tnaC , dctA , pheM , sdhC , yhhQ , glpT , aceK , and gluQ accelerated RNA decay, consistent with previously described targets wherein RNase III cleavage initiates rapid degradation of secondary messages by other RNases. In contrast, cleavage at three novel sites in the ahpF , pflB , and yajQ transcripts led to stabilized secondary transcripts. Two other novel sites in hisL and pheM overlapped with transcriptional attenuators that likely serve to ensure turnover of these highly structured RNAs. Many of the new RNase III target sites are located on transcripts encoding metabolic enzymes. For instance, two novel RNase III sites are located within transcripts encoding enzymes near a key metabolic node connecting glycolysis and the tricarboxylic acid (TCA) cycle. Pyruvate dehydrogenase activity was increased in an rnc deletion mutant compared to the wild-type (WT) strain in early stationary phase, confirming the novel link between RNA turnover and regulation of pathway activity. Identification of these novel sites suggests that mRNA turnover may be an underappreciated mode of regulating metabolism. IMPORTANCE The concerted action and overlapping functions of endoribonucleases, exoribonucleases, and RNA processing enzymes complicate the study of global RNA turnover and recycling of specific transcripts. More information about RNase specificity and activity is needed to make predictions of transcript half-life and to design synthetic transcripts with optimal stability. RNase III does not have a conserved target sequence but instead recognizes RNA secondary structure. Prior to this study, only a few RNase III target sites in E. coli were known, so we used RNA sequencing to provide a more comprehensive list of cleavage sites and to examine the impact of RNase III on transcript degradation. With this added information on how RNase III participates in transcript regulation and recycling, a more complete picture of RNA turnover can be developed for E. coli . Similar approaches could be used to augment our understanding of RNA turnover in other bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Long-read RNA sequencing atlas of human microglia isoforms elucidates disease-associated genetic regulation of splicing

Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. Mapping the genetics of gene expression in human microglia has identified several loci associated with disease-associated genetic variants in microglia-specific regulatory elements. However, identifying genetic effects on splicing is challenging because of the use of short sequencing reads. Here, we present the isoform-centric microglia genomic atlas (isoMiGA), which leverages long-read RNA sequencing to identify 35,879 novel microglia isoforms. We show that these isoforms are involved in stimulation response and brain region specificity. We then quantified the expression of both known and novel isoforms in a multi-ancestry meta-analysis of 555 human microglia short-read RNA sequencing samples from 391 donors, and found associations with genetic risk loci in Alzheimer’s and Parkinson’s disease. We nominate several loci that may act through complex changes in isoform and splice-site usage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Analysis of Transcriptome and Epitranscriptome in Plants Using PacBio Iso-Seq and Nanopore-Based Direct RNA Sequencing

Nanopore sequencing from Oxford Nanopore Technologies (ONT) and Pacific BioSciences (PacBio) single-molecule real-time (SMRT) long-read isoform sequencing (Iso-Seq) are revolutionizing the way transcriptomes are analyzed. These methods offer many advantages over most widely used high-throughput short-read RNA sequencing (RNA-Seq) approaches and allow a comprehensive analysis of transcriptomes in identifying full-length splice isoforms and several other post-transcriptional events. In addition, direct RNA-Seq provides valuable information about RNA modifications, which are lost during the PCR amplification step in other methods. Here, we present a comprehensive summary of important applications of these technologies in plants, including identification of complex alternative splicing (AS), full-length splice variants, fusion transcripts, and alternative polyadenylation (APA) events. Furthermore, we discuss the impact of the newly developed nanopore direct RNA-Seq in advancing epitranscriptome research in plants. Additionally, we summarize computational tools for identifying and quantifying full-length isoforms and other co/post-transcriptional events and discussed some of the limitations with these methods. Sequencing of transcriptomes using these new single-molecule long-read methods will unravel many aspects of transcriptome complexity in unprecedented ways as compared to previous short-read sequencing approaches. Analysis of plant transcriptomes with these new powerful methods that require minimum sample processing is likely to become the norm and is expected to uncover novel co/post-transcriptional gene regulatory mechanisms that control biological outcomes during plant development and in response to various stresses.

alternative polyadenylation↗
DOE OSTI2019

A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods

Background: 3’ RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3' method is needed to determine their relative merits. To this end, we used two commercially available library preparation kits, the KAPA Stranded mRNA-Seq kit (traditional method) and the Lexogen QuantSeq 3’ mRNASeq kit (3' method), to prepare libraries from mouse liver RNA. We then sequenced and analyzed the libraries to determine the advantages and disadvantages of these two approaches. Results: We found that the traditional whole transcript method and the 3’ RNA-Seq method had similar levels of reproducibility. As expected, the whole transcript method assigned more reads to longer transcripts, while the 3' method assigned roughly equal numbers of reads to transcripts regardless of their lengths. We found that the 3’ RNA-Seq method detected more short transcripts than the whole transcript method. With regard to differential expression analysis, we found that the whole transcript method detected more differentially expressed genes, regardless of the level of sequencing depth. Conclusions: The 3’ RNA-Seq method was better able to detect short transcripts, while the whole transcript RNA-Seq was able to detect more differentially expressed.

3’ RNA-Seq↗
DOE OSTI2016

RNAcentral: A comprehensive database of non-coding RNA sequences

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

An expanded maize gene expression atlas based on RNA sequencing and its use to explore root development

Comprehensive and systematic transcriptome profiling provides valuable insight into biological and developmental processes that occur throughout the life cycle of a plant. We have enhanced our previously published microarray-based gene atlas of maize ( Zea mays L.) inbred B73 to now include 79 distinct replicated samples that have been interrogated using RNA sequencing (RNA-seq). The current version of the atlas includes 50 original array-based gene atlas samples, a time-course of 12 stalk and leaf samples postflowering, and an additional set of 17 samples from the maize seedling and adult root system. The entire dataset contains 4.6 billion mapped reads, with an average of 20.5 million mapped reads per biological replicate, allowing for detection of genes with lower transcript abundance. As the new root samples represent key additions to the previously examined tissues, we highlight insights into the root transcriptome, which is represented by 28,894 (73.2%) annotated genes in maize. Additionally, we observed remarkable expression differences across both the longitudinal (four zones) and radial gradients (cortical parenchyma and stele) of the primary root supported by fourfold differential expression of 9353 and 4728 genes, respectively. Among the latter were 1110 genes that encode transcription factors, some of which are orthologs of previously characterized transcription factors known to regulate root development in Arabidopsis thaliana (L.) Heynh., while most are novel, and represent attractive targets for reverse genetics approaches to determine their roles in this important organ. As a result, this comprehensive transcriptome dataset is a powerful tool toward understanding maize development, physiology, and phenotypic diversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Global regulatory function of the low oxygen-induced transcriptional regulator LoiA in Salmonella Typhimurium revealed by RNA sequencing

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a major intestinal pathogen that can infect both humans and a variety of animals. LoiA, a novel virulence-regulating protein encoded in Salmonella pathogenicity island (SPI)-14, has been shown to be induced under low oxygen conditions and contribute to S. Typhimurium invasion into intestinal epithetical cells by activating the SPI-1 invasion genes. However, the global regulatory network of LoiA remains unknown. Here, we used high-throughput RNA sequencing (RNA-seq) technology to investigate the regulatory function of LoiA in S. Typhimurium under low oxygen conditions. A total of 1250 genes were differentially expressed between the loiA mutant and the wild-type strain; 413 genes were up-regulated and 837 were down-regulated. SPI-1 gene expression was down-regulated in the loiA mutant, consistent with previous results. SPI-2 gene expression was not affected by deletion of loiA; the expression of most genes involved in flagellar basal body and hook biosynthesis was up-regulated in the loiA mutant, while the expression of genes associated with flagellin, motility, and chemotaxis was down-regulated; the expression of lon, encoding an ATP-dependent protease, was up-regulated in the mutant. This study indicates that LoiA regulates a variety of virulence-associated genes in S. Typhimurium. The negative regulation of Lon protease by LoiA indicates that LoiA can regulates several virulence-associated genes in S. Typhimurium via the Lon protease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Optimal Bayesian supervised domain adaptation for RNA sequencing data

Abstract Motivation When learning to subtype complex disease based on next-generation sequencing data, the amount of available data is often limited. Recent works have tried to leverage data from other domains to design better predictors in the target domain of interest with varying degrees of success. But they are either limited to the cases requiring the outcome label correspondence across domains or cannot leverage the label information at all. Moreover, the existing methods cannot usually benefit from other information available a priori such as gene interaction networks. Results In this article, we develop a generative optimal Bayesian supervised domain adaptation (OBSDA) model that can integrate RNA sequencing (RNA-Seq) data from different domains along with their labels for improving prediction accuracy in the target domain. Our model can be applied in cases where different domains share the same labels or have different ones. OBSDA is based on a hierarchical Bayesian negative binomial model with parameter factorization, for which the optimal predictor can be derived by marginalization of likelihood over the posterior of the parameters. We first provide an efficient Gibbs sampler for parameter inference in OBSDA. Then, we leverage the gene-gene network prior information and construct an informed and flexible variational family to infer the posterior distributions of model parameters. Comprehensive experiments on real-world RNA-Seq data demonstrate the superior performance of OBSDA, in terms of accuracy in identifying cancer subtypes by utilizing data from different domains. Moreover, we show that by taking advantage of the prior network information we can further improve the performance. Availability and implementation The source code for implementations of OBSDA and SI-OBSDA are available at the following link. https://github.com/SHBLK/BSDA. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗
DOE OSTI2011

Identification and removal of ribosomal RNA sequences from metatranscriptomes

Here, we present riboPicker, a robust framework for the rapid, automated identification and removal of ribosomal RNA sequences from metatranscriptomic datasets. The results can be exported for subsequent analysis, and the databases used for the web-based version are updated on a regular basis. riboPicker categorizes rRNA-like sequences and provides graphical visualizations and tabular outputs of ribosomal coverage, alignment results and taxonomic classifications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

An interferon signature identified by RNA-sequencing of mammary tissues varies across the estrous cycle and is predictive of metastasis-free survival

The concept that a breast cancer patient's menstrual stage at the time of tumor surgery influences risk of metastases remains controversial. The scarcity of comprehensive molecular studies of menstrual stage-dependent fluctuations in the breast provides little insight. To gain a deeper understanding of the biological changes in mammary tissue and blood during the menstrual cycle and to determine the influence of environmental exposures, such as low-dose ionizing radiation (LDIR), we used the mouse to characterize estrous-cycle variations in mammary gene transcripts by RNA-sequencing, peripheral white blood cell (WBC) counts and plasma cytokine levels. We identified an estrous-variable and hormone-dependent gene cluster enriched for Type-1 interferon genes. Cox regression identified a 117-gene signature of interferon-associated genes, which correlated with lower frequencies of metastasis in breast cancer patients. LDIR (10cGy) exposure had no detectable effect on mammary transcripts. However, peripheral WBC counts varied across the estrous cycle and LDIR exposure reduced lymphocyte counts and cytokine levels in tumor-susceptible mice. Our finding of variations in mammary Type-1 interferon and immune functions across the estrous cycle provides a mechanism by which timing of breast tumor surgery during the menstrual cycle may have clinical relevance to a patient's risk for distant metastases.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

RNAcentral: a hub of information for non-coding RNA sequences

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences, collating information on ncRNA sequences of all types from a broad range of organisms. We have recently added a new genome mapping pipeline that identifies genomic locations for ncRNA sequences in 296 species. We have also added several new types of functional annotations, such as tRNA secondary structures, Gene Ontology annotations, and miRNA-target interactions. A new quality control mechanism based on Rfam family assignments identifies potential contamination, incomplete sequences, and more. The RNAcentral database has become a vital component of many workflows in the RNA community, serving as both the primary source of sequence data for academic and commercial groups, as well as a source of stable accessions for the annotation of genomic and functional features. These examples are facilitated by an improved RNAcentral web interface, which features an updated genome browser, a new sequence feature viewer, and improved text search functionality.

Sweeney, Blake A.↗
DOE OSTI2017

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↗
DOE OSTI2021

Single-cell RNA sequencing of batch Chlamydomonas cultures reveals heterogeneity in their diurnal cycle phase

The photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of its ease of culture in the laboratory. Genomic and systems biology approaches have previously described transcriptome responses to environmental changes using bulk data, thus representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing by the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample natural algal communities. Second, scRNA-seq successfully separated single cells into nonoverlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest photosynthesis and cell division to economize resources. Notably, these groups of cells not only recapitulated known patterns observed with bulk RNA-seq but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We document experimentally that bulk RNA-seq data represent an average of typically hidden heterogeneity in the population.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus

Single-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover key regulatory elements that determine cell fate during developmental programs. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues’ secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted to Arabidopsis roots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell wall structure, Populus shoot apices, and more lignified stems. Using the 10× Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.

54 ENVIRONMENTAL SCIENCES↗