RNA: state memory and mediator of cellular phenotype

The Role of Cells in Encoding and Storing Information: A Narrative Review of Cellular Memory

Memory, a fundamental aspect of human cognition and consciousness, is multifaceted and extends beyond traditional conceptualizations of mental recall. This review article explores memory through various lenses, including brain-based, body-based, and cellular mechanisms. At its core, memory involves the encoding, storage, and retrieval of information. Advances in neuroscience reveal that synaptic changes and molecular modifications, particularly in the hippocampus, are crucial for memory consolidation. Additionally, body memory, or somatic memory, highlights how sensory experiences and traumatic events are stored and influence behavior, underscoring the role of implicit memory. Multiple studies have demonstrated that memories can be encoded and stored in cells. Evidence suggests that these memories can then be transferred between individuals through organ transplantation. Additionally, observations in organisms that lack a nervous system, such as bacteria, fungi, and plants, expand traditional memory concepts. This review highlights and compiles novel research from the last few decades that explores information encoding and storage at a cellular level across a wide variety of disciplines. Our aim is to integrate these findings into a cohesive framework that helps explain the role of cellular processes in memory retention and transfer. By compiling research across diverse fields, this review aims to establish a foundation for future investigation into the physiological and psychological significance of cellular memory. Despite substantial progress, critical gaps persist in our understanding of how cellular memory interfaces with neural memory systems and the precise pathways through which information is encoded, stored, retrieved, and transferred at the cellular level. There has been a noticeable lack of research focused on cellular memory, and more rigorous investigations are needed to uncover how cells participate in memory and the extent to which these processes influence human behavior and cognition.

Mapping the transcriptome: Realizing the full potential of spatial data analysis

RNA sequencing in situ allows for whole-transcriptome characterization at high resolution, while retaining spatial information. These data present an analytical challenge for bioinformatics-how to leverage spatial information effectively? Properties of data with a spatial dimension require special handling, which necessitate a different set of statistical and inferential considerations when compared to non-spatial data. The geographical sciences primarily use spatial data and have developed methods to analye them. Here we discuss the challenges associated with spatial analysis and examine how we can take advantage of practice from the geographical sciences to realize the full potential of spatial information in transcriptomic datasets.

Single-cell RNA sequencing reveals homogeneous transcriptome patterns and low variance in a suspension CHO-K1 and an adherent HEK293FT cell line in culture conditions

Recombinant mammalian host cell lines, in particular CHO and HEK293 cells, are used for the industrial production of therapeutic proteins. Despite their well-known genomic instability, the control mechanisms that enable cells to respond to changes in the environmental conditions are not yet fully understood, nor do we have a good understanding of the factors that lead to phenotypic shifts in long-term cultures. A contributing factor could be inherent diversity in transcriptomes within a population. In this study, we used a full-length coverage single-cell RNA sequencing (scRNA-seq) approach to investigate and compare cell-to-cell variability and the impact of standardized and homogenous culture conditions on the diversity of individual cell transcriptomes, comparing suspension CHO-K1 and adherent HEK293FT cells. Our data showed a critical batch effect from the sequencing of four 96-well plates of CHO-K1 single cells stored for different periods of time, which was and may be therefore identified as a technical variable to consider in experimental planning. Besides, in an artificial and controlled culture environment such as used in routine cell culture technology, the gene expression pattern of a given population does not reveal any marker gene capable to disclose relevant cell population substructures, both for CHO-K1 cells and for HEK293FT cells. The variation observed is primarily driven by the cell cycle.

Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Although transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Short-read transcript sequencing has prevented researchers from directly exploring full-length transcripts, forcing them to focus on individual splice sites. Here, we develop a pipeline for Multi-Sample long-read Transcriptome Assembly (MuSTA), which enables construction of a transcriptome from long-read sequence data. Using the constructed transcriptome as a reference, we analyze RNA extracted from 22 clinical breast cancer specimens. We identify a comprehensive set of subtype-specific and differentially used isoforms, which extended our knowledge of isoform regulation to unannotated isoforms including a short form TNS3. We also find that the exon-intron structure of fusion transcripts depends on their genomic context, and we identify double-hop fusion transcripts that are transcribed from complex structural rearrangements. For example, a double-hop fusion results in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and is thought to protect fetus from maternal rejection; expression is elevated in several TCGA samples with ERVFRD-1 fusions. Our analyses provide direct evidence that full-length transcript sequencing of clinical samples can add to our understanding of cancer biology and genomics in general.

ColorCells: a database of expression, classification and functions of lncRNAs in single cells

Although long noncoding RNAs (lncRNAs) have significant tissue specificity, their expression and variability in single cells remain unclear. Here, we developed ColorCells (http://rna.sysu.edu.cn/colorcells/), a resource for comparative analysis of lncRNAs expression, classification and functions in single-cell RNA-Seq data. ColorCells was applied to 167 913 publicly available scRNA-Seq datasets from six species, and identified a batch of cell-specific lncRNAs. These lncRNAs show surprising levels of expression variability between different cell clusters, and has the comparable cell classification ability as known marker genes. Cell-specific lncRNAs have been identified and further validated by in vitro experiments. We found that lncRNAs are typically co-expressed with the mRNAs in the same cell cluster, which can be used to uncover lncRNAs' functions. Our study emphasizes the need to uncover lncRNAs in all cell types and shows the power of lncRNAs as novel marker genes at single cell resolution.

Establishment and transcriptomic analyses of a cattle rumen epithelial primary cells (REPC) culture by bulk and single-cell RNA sequencing to elucidate interactions of butyrate and rumen development

As a critical and high-value tool to study the development of rumen, we established a stable rumen epithelial primary cell (REPC) culture from a two-week-old Holstein bull calf rumen epithelial tissue. The transcriptomic profiling of the REPC and the direct effects of butyrate on gene expression were assessed. Correlated gene networks elucidated the putative roles and mechanisms of butyrate action in rumen epithelial development. The top networks perturbed by butyrate were associated with epithelial tissue development. Additionally, two critical upstream regulators, E2F1 and TGFB1, were identified to play critical roles in the differentiation, development, and growth of epithelial cells. Significant expression changes of upstream regulators and transcription factors provided further evidence in support that butyrate plays a specific and central role in regulating genomic and epigenomic activities influencing rumen development. This work is the essential component to obtain a complete global landscape of regulatory elements in cattle and to explore the dynamics of chromatin states in rumen epithelial cells induced by butyrate at early developmental stages.

Investigating the Effects of Brainstem Neuronal Adaptation on Cardiovascular Homeostasis

Central coordination of cardiovascular function is accomplished, in part, by the baroreceptor reflex, a multi-input multi-output physiological control system that regulates the activity of the parasympathetic and sympathetic nervous systems via interactions among multiple brainstem nuclei. Recent single-cell analyses within the brain revealed that individual neurons within and across brain nuclei exhibit distinct transcriptional states contributing to neuronal function. Such transcriptional heterogeneity complicates the task of understanding how neurons within and across brain nuclei organize and function to process multiple inputs and coordinate cardiovascular functions within the larger context of the baroreceptor reflex. However, prior analysis of brainstem neurons revealed that single-neuron transcriptional heterogeneity reflects an adaptive response to synaptic inputs and that neurons organize into distinct subtypes with respect to synaptic inputs received. Based on these results, we hypothesize that adaptation of neuronal subtypes support robust biological function through graded cellular responses. We test this hypothesis by examining the functional impact of neuronal adaptation on parasympathetic activity within the context of short-term baroreceptor reflex regulation. In this work, we extend existing quantitative closed-loop models of the baroreceptor reflex by incorporating into the model distinct input-driven neuronal subtypes and neuroanatomical groups that modulate parasympathetic activity. We then use this extended model to investigate, via simulation, the functional role of neuronal adaptation under conditions of health and systolic heart failure. Simulation results suggest that parasympathetic activity can be modulated appropriately by the coordination of distinct neuronal subtypes to maintain normal cardiovascular functions under systolic heart failure conditions. Moreover, differing degrees of adaptation of these neuronal subtypes contribute to cardiovascular behaviors corresponding to distinct clinical phenotypes of heart failure, such as exercise intolerance. Further, our results suggest that an imbalance between sympathetic and parasympathetic activity regulating ventricular contractility contributes to exercise intolerance in systolic heart failure patients, and restoring this balance can improve the short-term cardiovascular performance of these patients.

A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs

In late 2012 it was evidenced that most of the human genome is transcribed but only a small percentage of the transcripts are translated. This observation supported the importance of non-coding RNAs and it was confirmed in several organisms. The most abundant non-translated transcripts are long non-coding RNAs (lncRNAs). In contrast to protein-coding RNAs, they show a more cell-specific expression. To understand the function of lncRNAs, it is fundamental to investigate in which cells they are preferentially expressed and to detect their subcellular localization. Recent improvements of techniques that localize single RNA molecules in tissues like single-cell RNA sequencing and fluorescence amplification methods have given a considerable boost in the knowledge of the lncRNA functions. In recent years, single-cell transcription variability was associated with non-coding RNA expression, revealing this class of RNAs as important transcripts in the cell lineage specification. The purpose of this review is to collect updated information about lncRNA classification and new findings on their function derived from single-cell analysis. We also retained useful for all researchers to describe the methods available for single-cell analysis and the databases collecting single-cell and lncRNA data. Tables are included to schematize, describe, and compare exposed concepts.

Avian Primordial Germ Cells Contribute to and Interact With the Extracellular Matrix During Early Migration

During early avian development, primordial germ cells (PGC) are highly migratory, moving from the central area pellucida of the blastoderm to the anterior extra-embryonic germinal crescent. The PGCs soon move into the forming blood vessels by intravasation and travel in the circulatory system to the genital ridges where they participate in the organogenesis of the gonads. This complex cellular migration takes place in close association with a nascent extracellular matrix that matures in a precise spatio-temporal pattern. We first compiled a list of quail matrisome genes by bioinformatic screening of human matrisome orthologs. Next, we used single cell RNA-seq analysis (scRNAseq) to determine that PGCs express numerous ECM and ECM-associated genes in early embryos. The expression of select ECM transcripts and proteins in PGCs were verified by fluorescent in situ hybridization (FISH) and immunofluorescence (IF). Live imaging of transgenic quail embryos injected with fluorescent antibodies against fibronectin and laminin, showed that germinal crescent PGCs display rapid shape changes and morphological properties such as blebbing and filopodia while surrounded by, or in close contact with, an ECM fibril meshwork that is itself in constant motion. Injection of anti-β1 integrin CSAT antibodies resulted in a reduction of mature fibronectin and laminin fibril meshwork in the germinal crescent at HH4-5 but did not alter the active motility of the PGCs or their ability to populate the germinal crescent. These results suggest that integrin β1 receptors are important, but not required, for PGCs to successfully migrate during embryonic development, but instead play a vital role in ECM fibrillogenesis and assembly.

Artificial Gene Regulatory Networks-A Review

In nature, gene regulatory networks are a key mediator between the information stored in the DNA of living organisms (their genotype) and the structural and behavioral expression this finds in their bodies, surviving in the world (their phenotype). They integrate environmental signals, steer development, buffer stochasticity, and allow evolution to proceed. In engineering, modeling and implementations of artificial gene regulatory networks have been an expanding field of research and development over the past few decades. This review discusses the concept of gene regulation, describes the current state of the art in gene regulatory networks, including modeling and simulation, and reviews their use in artificial evolutionary settings. We provide evidence for the benefits of this concept in natural and the engineering domains.

Translation acrobatics: how cancer cells exploit alternate modes of translational initiation

Recent work has brought to light many different mechanisms of translation initiation that function in cells in parallel to canonical cap-dependent initiation. This has important implications for cancer. Canonical cap-dependent translation initiation is inhibited by many stresses such as hypoxia, nutrient limitation, proteotoxic stress, or genotoxic stress. Since cancer cells are often exposed to these stresses, they rely on alternate modes of translation initiation for protein synthesis and cell growth. Cancer mutations are now being identified in components of the translation machinery and in cis-regulatory elements of mRNAs, which both control translation of cancer-relevant genes. In this review, we provide an overview on the various modes of non-canonical translation initiation, such as leaky scanning, translation re-initiation, ribosome shunting, IRES-dependent translation, and m⁶A-dependent translation, and then discuss the influence of stress on these different modes of translation. Finally, we present examples of how these modes of translation are dysregulated in cancer cells, allowing them to grow, to proliferate, and to survive, thereby highlighting the importance of translational control in cancer.

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Single cell transcriptomics of noncoding RNAs and their cell-specificity

Recent developments of single cell transcriptome profiling methods have led to the realization that many seemingly homogeneous cells have surprising levels of expression variability. The biological implications of the high degree of variability is unclear but one possibility is that many genes are restricted in expression to small lineages of cells, suggesting the existence of many more cell types than previously estimated. Noncoding RNA (ncRNA) are thought to be key parts of gene regulatory processes and their single cell expression patterns may help to dissect the biological function of single cell variability. Technology for measuring ncRNA in single cell is still in development and most of the current single cell datasets have reliable measurements for only long noncoding RNA (lncRNA). Most works report that lncRNAs show lineage-specific restricted expression patterns, which suggest that they might determine, at least in part, lineage fates and cell subtypes. However, evidence is still inconclusive as to whether lncRNAs and other ncRNAs are more lineage-specific than protein-coding genes. Nevertheless, measurement of ncRNAs in single cells will be important for studies of cell types and single cell function. WIREs RNA 2017, 8:e1433. doi: 10.1002/wrna.1433 For further resources related to this article, please visit the WIREs website.

Challenges and emerging directions in single-cell analysis

Single-cell analysis is a rapidly evolving approach to characterize genome-scale molecular information at the individual cell level. Development of single-cell technologies and computational methods has enabled systematic investigation of cellular heterogeneity in a wide range of tissues and cell populations, yielding fresh insights into the composition, dynamics, and regulatory mechanisms of cell states in development and disease. Despite substantial advances, significant challenges remain in the analysis, integration, and interpretation of single-cell omics data. Here, we discuss the state of the field and recent advances and look to future opportunities.

Cellular Deconstruction: Finding Meaning in Individual Cell Variation

The advent of single cell transcriptome analysis has permitted the discovery of cell-to-cell variation in transcriptome expression of even presumptively identical cells. We hypothesize that this variability reflects a many-to-one relation between transcriptome states and the phenotype of a cell. In this relation, the molecular ratios of the subsets of RNA are determined by the stoichiometric constraints of the cell systems, which underdetermine the transcriptome state. Furthermore, the variability is, in part, induced by the tissue context and is important for system-level function. This theory is analogous to theories of literary deconstruction, where multiple 'signifiers' work in opposition to one another to create meaning. By analogy, transcriptome phenotypes should be defined as subsets of RNAs comprising selected RNA systems where the system-associated RNAs are balanced with each other to produce the associated cellular function. This idea provides a framework for understanding cellular heterogeneity in phenotypic responses to variant conditions, such as disease challenge.

Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function

There is a growing appreciation of the extent of transcriptome variation across individual cells of the same cell type. While expression variation may be a byproduct of, for example, dynamic or homeostatic processes, here we consider whether single-cell molecular variation per se might be crucial for population-level function. Under this hypothesis, molecular variation indicates a diversity of hidden functional capacities within an ensemble of identical cells, and this functional diversity facilitates collective behavior that would be inaccessible to a homogenous population. In reviewing this topic, we explore possible functions that might be carried by a heterogeneous ensemble of cells; however, this question has proven difficult to test, both because methods to manipulate molecular variation are limited and because it is complicated to define, and measure, population-level function. We consider several possible methods to further pursue the hypothesis that variation is function through the use of comparative analysis and novel experimental techniques.

Inferring cell type innovations by phylogenetic methods-concepts, methods, and limitations

Multicellular organisms are composed of distinct cell types that have specific roles in the body. Each cell type is a product of two kinds of historical processes-development and evolution. Although the concept of a cell type is difficult to define, the cell type concept based on the idea of the core regulatory network (CRN), a gene regulatory network that determines the identity of a cell type, illustrates the essential aspects of the cell type concept. The first step toward elucidating cell type evolution is to reconstruct the evolutionary relationships of cell types, or the cell type tree. The sister cell type model assumes that a new cell type evolves through divergence from a multifunctional ancestral cell type, creating tree-like evolutionary relationships between cell types. The process of generating a cell type tree can also be understood as the sequential addition of a new branching point on an ancestral cell differentiation hierarchy in evolution. A cell type tree thus represents an intertwined history of cell type evolution and development. Cell type trees can be reconstructed from high-throughput sequencing data, and the reconstruction of a cell type tree leads to the discovery of genes that are functionally important for a cell type. Although many issues including the lack of cross-species comparisons and the lack of a proper model for cell type evolution remain, the study of the origin of a new cell type using phylogenetic methods offers a promising new research avenue in developmental evolution. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 653-661, 2015. © 2015 Wiley Periodicals, Inc.

Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation

BACKGROUND

Differentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question.

RESULTS

We present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved.

CONCLUSIONS

Single-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.

Ribonucleic acid (RNA) biosynthesis in human cancer

In many respects, the most remarkable chemical substances within the genome of eukaryotic cells are remarkable proteins which are the critical structural and functional units of living cells. The specifications for everything that goes in the cell are natural digital-to-digital decoding process in an archive sequence by deoxyribonucleic acid (DNA) and an articulate construction by ribonucleic acid (RNA). The products of DNA transcription are long polymers of ribonucleotides rather than deoxyribonucleotides and are termed ribonucleic acids. Certain deoxyribonucleotide sequences, or genes, give rise to transfer RNA (tRNA) and other ribosomal RNA (rRNA) when transcribed. The ribonucleotide sequences fold extensively and rRNA is associated with specific proteins to yield the essential cell components, ribosomes. Transcription of other special sequences yields messenger RNAs (mRNAs) that contain ribonucleotide sequences that will be ultimately translated into new types of amino acid sequences of functional cellular protein molecules. This switch to a different variety of cellular molecular sequences is complex, but each sequence of the three ribonucleotides specifies the insertion of one particular amino acid into the polypeptide chain under production. Whilst mRNA is considered the vehicle by which genetic information is transmitted from the genome and allocated in the appropriate cytoplasmic sites for translation into protein via cap-dependent mechanism, the actual translation depends also on the presence of other so-called household and luxury protein molecules. Recent evidence suggests RNA species are required at initiation, because treatment of cells with antibiotics or drugs that inhibit RNA synthesis cause a decrease in protein synthesis. The rRNA is necessary as a structural constituent of the ribosomes upon which translation takes place, whereas tRNA is necessary as an adaptor in amino acid activation and elongation protein chains to ribosomes. In this article, we review malignant tumor, with stem like properties, and recent technical advances into the phenomenon of micro-particles and micro-vesicles containing cell-free nucleic acids that circulate plasma. New areas of research have been opened into screening tumor telomerase progression, prognosis of aptamers targeting cell surface, monitoring the efficacy of anticancer therapies, oncogenic transformation of host cell, and RNA polymerases role in the cell cycle progression and differentiation.

Eusocial insects as emerging models for behavioural epigenetics

Understanding the molecular basis of how behavioural states are established, maintained and altered by environmental cues is an area of considerable and growing interest. Epigenetic processes, including methylation of DNA and post-translational modification of histones, dynamically modulate activity-dependent gene expression in neurons and can therefore have important regulatory roles in shaping behavioural responses to environmental cues. Several eusocial insect species - with their unique displays of behavioural plasticity due to age, morphology and social context - have emerged as models to investigate the genetic and epigenetic underpinnings of animal social behaviour. This Review summarizes recent studies in the epigenetics of social behaviour and offers perspectives on emerging trends and prospects for establishing genetic tools in eusocial insects.

Aging on a different scale--chronological versus pathology-related aging

In the next decades the elderly population will increase dramatically, demanding appropriate solutions in health care and aging research focusing on healthy aging to prevent high burdens and costs in health care. For this, research targeting tissue-specific and individual aging is paramount to make the necessary progression in aging research. In a recently published study we have attempted to make a step interpreting aging data on chronological as well as pathological scale. For this, we sampled five major tissues at regular time intervals during the entire C57BL/6J murine lifespan from a controlled in vivo aging study, measured the whole transcriptome and incorporated temporal as well as physical health aspects into the analyses. In total, we used 18 different age-related pathological parameters and transcriptomic profiles of liver, kidney, spleen, lung and brain and created a database that can now be used for a broad systems biology approach. In our study, we focused on the dynamics of biological processes during chronological aging and the comparison between chronological and pathology-related aging.

Inputs drive cell phenotype variability

What is the significance of the extensive variability observed in individual members of a single-cell phenotype? This question is particularly relevant to the highly differentiated organization of the brain. In this study, for the first time, we analyze the in vivo variability within a neuronal phenotype in terms of input type. We developed a large-scale gene-expression data set from several hundred single brainstem neurons selected on the basis of their specific synaptic input types. The results show a surprising organizational structure in which neuronal variability aligned with input type along a continuum of sub-phenotypes and corresponding gene regulatory modules. Correlations between these regulatory modules and specific cellular states were stratified by synaptic input type. Moreover, we found that the phenotype gradient and correlated regulatory modules were maintained across subjects. As these specific cellular states are a function of the inputs received, the stability of these states represents “attractor”-like states along a dynamic landscape that is influenced and shaped by inputs, enabling distinct state-dependent functional responses. We interpret the phenotype gradient as arising from analog tuning of underlying regulatory networks driven by distinct inputs to individual cells. Our results change the way we understand how a phenotypic population supports robust biological function by integrating the environmental experience of individual cells. Our results provide an explanation of the functional significance of the pervasive variability observed within a cell type and are broadly applicable to understanding the relationship between cellular input history and cell phenotype within all tissues.

Subcellular RNA sequencing reveals broad presence of cytoplasmic intron-sequence retaining transcripts in mouse and rat neurons

Recent findings have revealed the complexity of the transcriptional landscape in mammalian cells. One recently described class of novel transcripts are the Cytoplasmic Intron-sequence Retaining Transcripts (CIRTs), hypothesized to confer post-transcriptional regulatory function. For instance, the neuronal CIRT KCNMA1i16 contributes to the firing properties of hippocampal neurons. Intronic sub-sequence retention within IL1-β mRNA in anucleate platelets has been implicated in activity-dependent splicing and translation. In a recent study, we showed CIRTs harbor functional SINE ID elements which are hypothesized to mediate dendritic localization in neurons. Based on these studies and others, we hypothesized that CIRTs may be present in a broad set of transcripts and comprise novel signals for post-transcriptional regulation. We carried out a transcriptome-wide survey of CIRTs by sequencing micro-dissected subcellular RNA fractions. We sequenced two batches of 150-300 individually dissected dendrites from primary cultures of hippocampal neurons in rat and three batches from mouse hippocampal neurons. After statistical processing to minimize artifacts, we found a broad prevalence of CIRTs in the neurons in both species (44-60% of the expressed transcripts). The sequence patterns, including stereotypical length, biased inclusion of specific introns, and intron-intron junctions, suggested CIRT-specific nuclear processing. Our analysis also suggested that these cytoplasmic intron-sequence retaining transcripts may serve as a primary transcript for ncRNAs. Our results show that retaining intronic sequences is not isolated to a few loci but may be a genome-wide phenomenon for embedding functional signals within certain mRNA. The results hypothesize a novel source of cis-sequences for post-transcriptional regulation. Our results hypothesize two potentially novel splicing pathways: one, within the nucleus for CIRT biogenesis; and another, within the cytoplasm for removing CIRT sequences before translation. We also speculate that release of CIRT sequences prior to translation may form RNA-based signals within the cell potentially comprising a novel class of signaling pathways.

Life spanning murine gene expression profiles in relation to chronological and pathological aging in multiple organs

Aging and age-related pathology is a result of a still incompletely understood intricate web of molecular and cellular processes. We present a C57BL/6J female mice in vivo aging study of five organs (liver, kidney, spleen, lung, and brain), in which we compare genome-wide gene expression profiles during chronological aging with pathological changes throughout the entire murine life span (13, 26, 52, 78, 104, and 130 weeks). Relating gene expression changes to chronological aging revealed many differentially expressed genes (DEGs), and altered gene sets (AGSs) were found in most organs, indicative of intraorgan generic aging processes. However, only ≤ 1% of these DEGs are found in all organs. For each organ, at least one of 18 tested pathological parameters showed a good age-predictive value, albeit with much inter- and intraindividual (organ) variation. Relating gene expression changes to pathology-related aging revealed correlated genes and gene sets, which made it possible to characterize the difference between biological and chronological aging. In liver, kidney, and brain, a limited number of overlapping pathology-related AGSs were found. Immune responses appeared to be common, yet the changes were specific in most organs. Furthermore, changes were observed in energy homeostasis, reactive oxygen species, cell cycle, cell motility, and DNA damage. Comparison of chronological and pathology-related AGSs revealed substantial overlap and interesting differences. For example, the presence of immune processes in liver pathology-related AGSs that were not detected in chronological aging. The many cellular processes that are only found employing aging-related pathology could provide important new insights into the progress of aging.

Perspectives on cell reprogramming with RNA

Recent advances in cell reprogramming have permitted the development of different stem cell lines and specific differentiated cell types using distinct technologies. Cell reprogramming is largely mediated by DNA and RNA. In this review, we explore the RNA-mediated cell reprogramming to induce specific target cell generation including stem cells, brain cells and cardiac cells. The ability of RNA populations to produce direct cell to cell phenotypic conversion is called Transcriptome Induced PhenotypeRemodeling (TIPeR). The theory and utility of RNA use for cellular reprogramming is explored in this review.

Adaptive transcriptional dynamics of A2 neurons and central cardiovascular control pathways

In order to provide an example of useful interaction between systems biology and computational neuroscience traditions, here we aim to identify the molecular response process through which elevated blood pressure induces a temporal sequence of gene expression changes. This initial response may then continually evolve as an adaptive response, altering central blood pressure set-point control. Our approach involves using a set of 96 quantitative PCR gene assays, which represent the molecular process associated with neuronal responses to angiotensin II type 1 receptor (AT1R) activation. We use this set as a probe to search for the AT1R signalling-triggered expression programme in individual neurons and groups of neurons involved in homeostatic regulation of cardiorespiratory function. Specifically, we focus on tissue samples from the nucleus tractus solitarii, as well as groups of A2 neurons and individual A2 cells within the nucleus tractus solitarii, and in the ventrolateral medulla and central amygdala. We assay these neural samples at rest and in response to elevated blood pressure. Analysis of the resulting high-dimensional data set reveals a remarkable complexity and heterogeneity of the samples and of their response to changes in blood pressure. These results demonstrate differential expression programmes for each anatomically distinct neuronal group and neuronal type. Single-cell expression analysis shows that A2 cells also are variable, and that the subset that responds to blood pressure with elevated Fos expression differs from other A2 cells. We present models of gene regulatory networks and of signalling cascades related to AT1R and broadly discuss the opportunities for valuable interactions between systems biology and computational neuroscience.

Transcriptome transfer provides a model for understanding the phenotype of cardiomyocytes

We show that the transfer of the adult ventricular myocyte (AVM) transcriptome into either a fibroblast or an astrocyte converts the host cell into a cardiomyocyte. Transcriptome-effected cardiomyocytes (tCardiomyocytes) display morphologies, immunocytochemical properties, and expression profiles of postnatal cardiomyocytes. Cell morphology analysis shows that tCardiomyoctes are elongated and have a similar length-to-width ratio as AVMs. These global phenotypic changes occur in a time-dependent manner and confer electroexcitability to the tCardiomyocytes. tCardiomyocyte generation does not require continuous overexpression of specific transcription factors; for example, the expression level of transcription factor Mef2c is higher in tCardiomyocytes than in fibroblasts, but similar in tCardiomyocytes and AVMs. These data highlight the dominant role of the gene expression profile in developing and maintaining cellular phenotype. The transcriptome-induced phenotype remodeling-generated tCardiomyocyte has significant implications for understanding and modulating cardiac disease development.

Review and application of group theory to molecular systems biology

In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this paper we briefly describe possible open problems. In connection with the genetic code we propose that it may be possible to use perturbation theory to explore the adjacent possibilities in the 64-dimensional space-time manifold of the evolving genome. With regards to algebraic graph theory, there are several minor open problems we discuss. In relation to network dynamics and groupoid formalism we suggest that the network graph might not be the main focus for understanding the phenotype but rather the phase space of the network dynamics. We show a simple case of a C6 network and its phase space network. We envision that the molecular network of a cell is actually a complex network of hypercycles and feedback circuits that could be better represented in a higher-dimensional space. We conjecture that targeting nodes in the molecular network that have key roles in the phase space, as revealed by analysis of the automorphism decomposition, might be a better way to drug discovery and treatment of cancer.

Single cell transcriptomics of hypothalamic warm sensitive neurons that control core body temperature and fever response Signaling asymmetry and an extension of chemical neuroanatomy

We report on an 'unbiased' molecular characterization of individual, adult neurons, active in a central, anterior hypothalamic neuronal circuit, by establishing cDNA libraries from each individual, electrophysiologically identified warm sensitive neuron (WSN). The cDNA libraries were analyzed by Affymetrix microarray. The presence and frequency of cDNAs were confirmed and enhanced with Illumina sequencing of each single cell cDNA library. cDNAs encoding the GABA biosynthetic enzyme Gad1 and of adrenomedullin, galanin, prodynorphin, somatostatin, and tachykinin were found in the WSNs. The functional cellular and in vivo studies on dozens of the more than 500 neurotransmitters, hormone receptors and ion channels, whose cDNA was identified and sequence confirmed, suggest little or no discrepancy between the transcriptional and functional data in WSNs; whenever agonists were available for a receptor whose cDNA was identified, a functional response was found. Sequencing single neuron libraries permitted identification of rarely expressed receptors like the insulin receptor, adiponectin receptor 2 and of receptor heterodimers; information that is lost when pooling cells leads to dilution of signals and mixing signals. Despite the common electrophysiological phenotype and uniform Gad1 expression, WSN transcriptomes show heterogeneity, suggesting strong epigenetic influence on the transcriptome. Our study suggests that it is well-worth interrogating the cDNA libraries of single neurons by sequencing and chipping.