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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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Post-transcriptional regulation across human tissues

Transcriptional and post-transcriptional regulation shape tissue-type-specific proteomes, but their relative contributions remain contested. Estimates of the factors determining protein levels in human tissues do not distinguish between (i) the factors determining the variability between the abundances of different proteins, i.e., mean-level-variability and, (ii) the factors determining the physiological variability of the same protein across different tissue types, i.e., across-tissues variability. We sought to estimate the contribution of transcript levels to these two orthogonal sources of variability, and found that scaled mRNA levels can account for most of the mean-level-variability but not necessarily for across-tissues variability. The reliable quantification of the latter estimate is limited by substantial measurement noise. However, protein-to-mRNA ratios exhibit substantial across-tissues variability that is functionally concerted and reproducible across different datasets, suggesting extensive post-transcriptional regulation. These results caution against estimating protein fold-changes from mRNA fold-changes between different cell-types, and highlight the contribution of post-transcriptional regulation to shaping tissue-type-specific proteomes.

Systems Biology

Estimating information flow through a memory system: the utility of meta-analytic methods for genetics

Critics of significance testing claim that this statistical framework promotes discrepancies by using arbitrary thresholds () to impose reject/accept dichotomies on continuous data, which is not reflective of the biological reality of quantitative phenotypes. Here we explore this idea and evaluate an alternative approach, demonstrating the potential for meta-analysis and related estimation methods to resolve discordance generated by the use of traditional significance tests. We selected a set of behavioral studies proposing differing models of the physiological basis of Drosophila olfactory memory and used systematic review and meta-analysis approaches to define the true role of lobular specialization within the brain. The mainstream view is that each of the three lobes of the Drosophila mushroom body play specialized roles in short-term aversive olfactory memory [1-5], but a number of studies have made divergent conclusions based on their discordant experimental findings [6-8]. Multivariate meta-regression models revealed that short-term memory lobular specialization is not in fact supported by the data, and identified the cellular extent of a transgenic driver as the major predictor of its effect on short-term memory. Our findings demonstrate that meta-analysis, meta-regression, hierarchical models and estimation methods in general can be successfully harnessed to identify knowledge gaps, synthesize divergent results, accommodate heterogeneous experimental design and quantify genetic mechanisms.

Neuroscience

A novel method to enhance the sensitivity of marker detection using a refined hierarchical prior of tissue similarities

MotivationIdentification of biochemical processes that drive the transformation of a totipotent cell into various cell types is essential to our understanding of living systems. This complex machinery determines how tissues differ in terms of their anatomy, physiology, morphology, and, more importantly, how various cellular control mechanisms contribute to the observed similarities/ differences. Tissue-selective genes orchestrate various aspects of cellular machinery in different tissues, and are known to be implicated in a number of tissue-specific pathologies.\n\nResultsWe propose a novel statistical approach that identifies and removes the effect of universally expressed genes in groups of tissues. This allows us to better characterize tissue similarities, as well as to identify tissue-selective genes. We use our method to construct a reliable hierarchy of tissue similarities. The groupings of tissues in this hierarchy are used to specify successively refined priors for identifying tissue-selective functions and their corresponding genes in the reduced subspace. We show that our refinement process enhances the signal-to-noise ratio in the identification of markers. Using case studies of immune cells and brain tissues, we show that our approach significantly outperforms the state-of-the-art methods, both in terms of coverage and reliability of the predicted tissue-selective genes.\n\nConclusionsOur statistical approach provides a general framework for enhancing the sensitivity of marker detection methods, which can be used in conjunction with other techniques. Even in cases where the number of available expression datasets is limited, we show that our marker detection method outperforms existing techniques. We present detailed validation on immune cells and brain tissues in this paper. Our approach can be applied to construct similar datasets of other human tissues as well, for identifying tissue-specific genes. We demonstrate how these tissue-selective genes enhance our understanding of differentiating biochemical features of brain tissues, shed light on how tissue-selective pathologies progress, and help us identify specific biomarkers and targets for future interventions.

Systems Biology

Sequence evidence for common ancestry of eukaryotic endomembrane coatomers

Eukaryotic cells are defined by compartments through which the trafficking of macromolecules is mediated by large complexes, such as the nuclear pore, transport vesicles and intraflagellar transport. The assembly and maintenance of these complexes is facilitated by endomembrane coatomers, long suspected to be divergently related on the basis of structural and more recently phylogenomic analysis. By performing supervised walks in sequence space across coatomer superfamilies, we uncover subtle sequence patterns that have remained elusive to date, ultimately unifying eukaryotic coatomers by divergent evolution. The conserved residues shared by 3,502 endomembrane coatomer components are mapped onto the solenoid superhelix of nucleoporin and COPII protein structures, thus determining the invariant elements of coatomer architecture. This ancient structural motif can be considered as a universal signature connecting eukaryotic coatomers involved in multiple cellular processes across cell physiology and human disease.

Bioinformatics

Life history evolution in response to changes in metapopulation structure in an arthropod herbivore

O_LIThe persistence and dynamics of populations largely depends on the way they are configured and integrated into space and the ensuing eco-evolutionary dynamics.\nC_LIO_LIWe manipulated spatial and temporal variation in patch size in replicated experimental metapopulations of the herbivore mite Tetranychus urticae and followed evolutionary dynamics over approximately 30 generations.\nC_LIO_LIA significant divergence in life history traits, physiological endpoints and gene expression was recorded in the spatially and spatiotemporally variable metapopulation, but also a remarkable convergence relative to the stable reference metapopulation in traits related to size and fecundity and in its transcriptional regulation.\nC_LIO_LIThe observed evolutionary dynamics are tightly linked to demographic changes, more specifically frequent episodes of resource shortage that increased the reproductive performance of mites on tomato, a challenging host plant. This points towards a general, adaptive stress response in stable spatial variable and spatiotemporal variable metapopulations that pre-adapts a herbivore arthropod to novel environmental stressors.\nC_LI

Evolutionary Biology

Heterogeneous generation of new cells in the adult echinoderm nervous system

Adult neurogenesis, generation of new functional cells in the mature central nervous system (CNS), has been documented in a number of diverse organisms, ranging from humans to invertebrates. However, the origin and evolution of this phenomenon is still poorly understood for many of the key phylogenetic groups. Echinoderms are one such phylum, positioned as a sister group to chordates within the monophyletic clade Deuterostomia. They are well known for the ability of their adult organs, including the CNS, to completely regenerate after injury. Nothing is known, however, about production of new cells in the nervous tissue under normal physiological conditions in these animals. In this study, we show that new cells are continuously generated in the mature radial nerve cord (RNC) of the sea cucumber Holothuria glaberrima. Importantly, this neurogenic activity is not evenly distributed, but is significantly more extensive in the lateral regions of the RNC than along the midline. Some of the new cells generated in the apical region of the ectoneural neuroepithelium leave their place of origin and migrate basally to populate the neural parenchyma. Gene expression analysis showed that generation of new cells in the adult sea cucumber CNS is associated with transcriptional activity of genes known to be involved in regulation of various aspects of neurogenesis in other animals. Further analysis of one of those genes, the transcription factor Myc showed that it is expressed, in some, but not all radial glial cells, suggesting heterogeneity of this CNS progenitor cell population in echinoderms.

Developmental Biology

First-step Mutations during Adaptation to Thermal Stress Shift the Expression of Thousands of Genes Back toward the Pre-stressed State

The temporal change of phenotypes during the adaptive process remain largely unexplored, as do the genetic changes that affect these phenotypic changes. Here we focused on three mutations that rose to high frequency in the early stages of adaptation within 12 Escherichia coli populations subjected to thermal stress (42{degrees}C). All of the mutations were in the rpoB gene, which encodes the RNA polymerase beta subunit. For each mutation, we measured the growth curves and gene expression (mRNAseq) of clones at 42{degrees}C. We also compared growth and gene expression to their ancestor under unstressed (37{degrees}C) and stressed conditions (42{degrees}C). Each of the three mutations changed the expression of hundreds of genes and conferred large fitness advantages, apparently through the restoration of global gene expression from the stressed towards the pre-stressed state. Finally, we compared the phenotypic characteristics of one mutant, I572L, to two high-temperature adapted clones that have this mutation plus additional background mutations. The background mutations increased fitness, but they did not substantially change gene expression. We conclude that early mutations in a global transcriptional regulator cause extensive changes in gene expression, many of which are likely under positive selection for their effect in restoring the pre-stress physiology.

Evolutionary Biology

Nanoscale architecture of the axon initial segment reveals an organized and robust scaffold

The Axon Initial Segment [AIS], located within the first 30 m of the axon, has two essential roles in generating action potentials and maintaining axonal identity. AIS assembly depends on a {beta}IV-spectrin / ankyrin G scaffold, but its macromolecular arrangement is not well understood. Here we quantitatively determined the AIS nanoscale architecture using STo-chastic Optical Reconstruction Microscopy [STORM]. First we directly demonstrate that the 190-nm periodicity of the AIS submembrane lattice results from longitudinal, head-to-head {beta}IV-spectrin molecules connecting actin rings. Using multicolor 3D-STORM, we resolve the nanoscale organization of ankyrin G: its aminoterminus associates with the submembrane lattice, whereas the carboxyterminus radially extends (~32 nm on average) toward the cytosol. This AIS nano-architecture is highly resistant to cytoskeletal perturbations, advocating its role in structural stabilization. Our findings provide a comprehensive view of the AIS molecular architecture, and will help understanding the crucial physiological functions of this compartment.

Neuroscience

Information Processing by Simple Molecular Motifs and Susceptibility to Noise

Biological organisms rely on their ability to sense and respond appropriately to their environment. The molecular mechanisms that facilitate these essential processes are however subject to a range of random effects and stochastic processes, which jointly affect the reliability of information transmission between receptors and e.g. the physiological downstream response. Information is mathematically defined in terms of the entropy; and the extent of information flowing across an information channel or signalling system is typically measured by the \"mutual information\", or the reduction in the uncertainty about the output once the input signal is known. Here we quantify how extrinsic and intrinsic noise affect the transmission of simple signals along simple motifs of molecular interaction networks. Even for very simple systems the effects of the different sources of variability alone and in combination can give rise to bewildering complexity. In particular extrinsic variability is apt to generate \"apparent\" information that can in extreme cases mask the actual information that for a single system would flow between the different molecular components making up cellular signalling pathways. We show how this artificial inflation in apparent information arises and how the effects of different types of noise alone and in combination can be understood.

Systems Biology

A common framework for identifying linkage rules across different types of interactions

Species interactions, ranging from antagonisms to mutualisms, form the architecture of biodiversity and determine ecosystem functioning. Understanding the rules responsible for who interacts with whom, as well as the functional consequences of these interspecific interactions, is central to predicting community dynamics and stability. Species traits sensu lato may affect different ecological processes determining species interactions through a two-step process. First, ecological and life-history traits govern species distributions and abundance, and hence determine species co-occurrence, which is a prerequisite for them to interact. Second, morphological traits between co-occurring potential interaction partners should match for the realization of an interaction. Moreover, inferring functioning from a network of interactions may require the incorporation of interaction efficiency. This efficiency may be also trait-mediated, and can depend on the extent of matching, or on morphological, physiological or behavioural traits. It has been shown that both neutral and trait-based models can predict the general structure of networks, but they rarely accurately predict individual interactions, suggesting that these models may be predicting the right structure for the wrong reason. We propose to move away from testing null models with a framework that explicitly models the probability of interaction among individuals given their traits. The proposed models integrate both neutral and trait-matching constraints while using only information about known interactions, thereby overcoming problems originating from under-sampling of rare interactions (i.e. missing links). They can easily accommodate qualitative or quantitative data, and can incorporate trait variation within species, such as values that vary along developmental stages or environmental gradients. We use three case studies to show that they can detect strong trait matching (e.g. predator-prey system), relaxed trait matching (e.g. herbivore-plant system) and barrier trait matching (e.g. plant-pollinator systems). Only by elucidating which species traits are important in each process, i.e. in determining interaction establishment, frequency, and efficiency, can we advance in explaining how species interact and the consequences for ecosystem functioning.

Ecology

Efficient Disruption and Replacement of an Effector Gene in the Oomycete Phytophthora sojae using CRISPR/Cas9

Phytophthora sojae is a pathogenic oomycete that infects soybean seedlings as well as stems and roots of established plants, costing growers $1-2 billion per year. Due to its economic importance, P. sojae has become a model for the study of oomycete genetics, physiology and pathology. Despite the availability of several genome sequences, the lack of efficient techniques for targeted mutagenesis and gene replacement have long hampered genetic studies of pathogenicity in Phytophthora species. Here, we describe a CRISPR/Cas9 system enabling rapid and efficient genome editing in P. sojae. Using the RXLR effector gene Avr4/6 as target, we observed that in the absence of a homologous template, the repair of Cas9-induced double-strand breaks (DSBs) in P. sojae was mediated by non-homologous end joining (NHEJ), primarily resulting in short indels. Most mutants were homozygous, presumably due to gene conversion triggered by Cas9-mediated cleavage of non-mutant alleles. When donor DNA was present, homology directed repair (HDR) was observed, which resulted in the replacement of the target gene with the donor DNA. By testing the specific virulence of several NHEJ mutants and HDR -mediated gene replacements on soybeans, we have validated the contribution of Avr4/6 to recognition by soybean R gene loci, Rps4 and Rps6, but also uncovered additional contributions to resistance by these two loci. Our results establish a powerful tool for studying functional genomics in Phytophthora, which provides new avenues for better control of this pathogen.

Microbiology

Control of sensory ectopic spike initiation by descending modulatory projection neurons

AO_SCPLOWBSTRACTC_SCPLOWDescending pathways are important modulators of motor networks and allow the dynamic adjustment of behaviors to changing internal and external conditions. Central pattern generating networks (CPG) have been particularly amenable to study the modulation of motor networks and demonstrated that virtually all levels of information processing are controlled by descending projections. CPGs receive sensory feedback and while it is known that sensory activity can be gated by central pathways, we here present for the first time that descending projection neurons modulate action potential initiation in sensory neurons.\n\nWe used the fact that the anterior gastric receptor neuron (AGR), a single-cell bipolar muscle tendon organ in the crustacean stomatogastric nervous system, generates spontaneous ectopic action potentials in its axon. We found that axonal spike initiation is under direct neuromodulatory control by a pair of descending projection neurons. These IV (inferior ventricular) neurons descend from the brain and are known to control CPGs in the stomatogastric ganglion (STG). Activation of the IV neurons elicited a long-lasting decrease in AGR ectopic spike activity. This decrease was only observed when spikes were generated ectopically in the central portion of the axon, i.e. the modulation was specific to the site of spontaneous spike initiation. The decrease could be mimicked by focal application of the IV neuron co-transmitter histamine and IV neuron actions were diminished after blocking H2 receptors, indicating a direct descending modulation of the axonal spike initiation site. In contrast, the propagation dynamics of en-passant action potentials were not affected. Descending modulatory projection neurons therefore control axonal spike initiation in sensory neurons without affecting afferent spike propagation to increase the physiological activity repertoire of sensory pathways.

Neuroscience

Modelizing Drosophila melanogaster longevity curves using a new discontinuous 2-Phases of Aging model

Aging is commonly described as being a continuous process affecting progressively organisms as time passes. This process results in a progressive decrease in individuals fitness through a wide range of both organismal - decreased motor activity, fertility, resistance to stress - and molecular phenotypes - decreased protein and energy homeostasis, impairment of insulin signaling. In the past 20 years, numerous genes have been identified as playing a major role in the aging process, yet little is known about the events leading to that loss of fitness. We recently described an event characterized by a dramatic increase of intestinal permeability to a blue food dye in aging flies committed to die within a few days. Importantly, flies showing this so called Smurf phenotype are the only ones, among a population, to show various age-related changes and exhibit a high-risk of impending death whatever their chronological age. Thus, these observations suggest that instead of being one continuous phenomenon, aging may be a discontinuous process well described by at least two distinguishable phases. In this paper we addressed this hypothesis by implementing a new 2-Phases of Aging mathematiCal model (2PAC model) to simulate longevity curves based on the simple hypothesis of two consecutive phases of lifetime presenting different properties. We first present a unique equation for each phase and discuss the biological significance of the 3 associated parameters. Then we evaluate the influence of each parameter on the shape of survival curves. Overall, this new mathematical model, based on simple biological observations, is able to reproduce many experimental longevity curves, supporting the existence of 2-phases of aging exhibiting specific properties and separated by a dramatic transition that remains to be characterized. Moreover, it indicates that Smurf survival can be approximated by one single constant parameter for a broad range of genotypes that we have tested under our environmental conditions.\n\nAuthor SummaryThe perception we can have of a process directly affects the way we study it. In the literature, aging is generally described as being a continuous process, progressively affecting organisms through a broad range of molecular and physiological changes ultimately leading to a dramatic decrease of individuals life expectancy. As such, aging studies focus on changes occurring in groups of individuals through time, considering individuals taken at a given time as being all equivalent. Instead, the recently described Smurf phenotype [1] suggested that any given time, a population could be divided in two subpopulations each characterized by a significantly different risk of impending death.\n\nBy formalizing here the concept of a discontinuous aging process using a mathematical model based on simple experimental observations, we propose a theoretical framework in which aging is actually separated in two consecutive phases characterized by three parameters easily quantifiable in vivo. Thus, the model we present here brings new tools to assess the events occurring during aging using a novel angle that we hope will open a better understanding of the very processes driving aging.

Bioinformatics

Determination of Ubiquitin Fitness Landscapes Under Different Chemical Stresses in a Classroom Setting

Ubiquitination is an essential post-translational regulatory process that can control protein stability, localization, and activity. Ubiquitin is essential for eukaryotic life and is highly conserved, varying in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies in S. cerevisiae indicate that ubiquitin is highly tolerant to single amino acid mutations. To resolve this paradox, we hypothesized that the set of tolerated substitutions would be reduced when the cultures are not grown in rich media conditions and that chemically induced physiologic perturbations might unmask constraints on the ubiquitin sequence. To test this hypothesis, a class of first year UCSF graduate students employed a deep mutational scanning procedure to determine the fitness landscape of a library of all possible single amino acid mutations of ubiquitin in the presence of one of five small molecule perturbations: MG132, Dithiothreitol (DTT), Hydroxyurea (HU), Caffeine, and DMSO. Our data reveal that the number of tolerated substitutions is greatly reduced by DTT, HU, or Caffeine, and that these perturbations uncover \"shared sensitized positions\" localized to areas around the hydrophobic patch and to the C-terminus. We also show perturbation specific effects including the sensitization of His68 in HU and tolerance to mutation at Lys63 in DTT. Taken together, our data suggest that chemical stress reduces buffering effects in the ubiquitin proteasome system, revealing previously hidden fitness defects. By expanding the set of chemical perturbations assayed, potentially by other classroom-based experiences, we will be able to further address the apparent dichotomy between the extreme sequence conservation and the experimentally observed mutational tolerance of ubiquitin. Finally, this study demonstrates the realized potential of a project lab-based interdisciplinary graduate curriculum.

Systems Biology

An Option Space for Early Neural Evolution

The origin of nervous systems has traditionally been discussed within two conceptual frameworks. Input-output models stress the sensory-motor aspects of nervous systems, while internal coordination models emphasize the role of nervous systems in coordinating multicellular activity, especially muscle-based motility. Here we consider both frameworks and apply them to describe aspects of each of three main groups of phenomena that nervous systems control: behavior, physiology and development. We argue that both frameworks and all three aspects of nervous system function need to be considered for a comprehensive discussion of nervous system origins. This broad mapping of the option space enables an overview of the many influences and constraints that may have played a role in the evolution of the first nervous systems.

Evolutionary Biology

Accelerating gene discovery by phenotyping whole-genome sequenced multi- mutation strains and using the sequence kernel association test (SKAT)

Forward genetic screens represent powerful, unbiased approaches to uncover novel components in any biological process. Such screens suffer from a major bottleneck, however, namely the cloning of corresponding genes causing the phenotypic variation. Reverse genetic screens have been employed as a way to circumvent this issue, but can often be limited in scope. Here we demonstrate an innovative approach to gene discovery. Using C. elegans as a model system, we used a whole-genome sequenced multi-mutation library, from the Million Mutation Project, together with the Sequence Kernel Association Test (SKAT), to rapidly screen for and identify genes associated with a phenotype of interest, namely defects in dye-filling of ciliated sensory neurons. Such anomalies in dye-filling are often associated with the disruption of cilia, organelles which in humans are implicated in sensory physiology (including vision, smell and hearing), development and disease. Beyond identifying several well characterised dye-filling genes, our approach uncovered three genes not previously linked to ciliated sensory neuron development or function. From these putative novel dye-filling genes, we confirmed the involvement of BGNT-1.1 in ciliated sensory neuron function and morphogenesis. BGNT-1.1 functions at the trans-Golgi network of sheath cells (glia) to influence dye-filling and cilium length, in a cell non-autonomous manner. Notably, BGNT-1.1 is the orthologue of human B3GNT1/B4GAT1, a glycosyltransferase associated with Walker-Warburg syndrome (WWS). WWS is a multigenic disorder characterised by muscular dystrophy as well as brain and eye anomalies. Together, our work unveils an effective and innovative approach to gene discovery, and provides the first evidence that B3GNT1-associated Walker-Warburg syndrome may be considered a ciliopathy.\n\nAuthor SummaryModel organisms are useful tools for uncovering new genes involved in a biological process via genetic screens. Such an approach is powerful, but suffers from drawbacks that can slow down gene discovery. In forward genetics screens, difficult-to-map phenotypes present daunting challenges, and whole-genome coverage can be equally challenging for reverse genetic screens where typically only a single genes function is assayed per strain. Here, we show a different approach which includes positive aspects of forward (high-coverage, randomly-induced mutations) and reverse genetics (prior knowledge of gene disruption) to accelerate gene discovery. We paired a whole-genome sequenced multi-mutation C. elegans library with a rare-variant associated test to rapidly identify genes associated with a phenotype of interest: defects in sensory neurons bearing sensory organelles called cilia, via a simple dye-filling assay to probe the form and function of these cells. We found two well characterised dye-filling genes and three genes, not previously linked to ciliated sensory neuron development or function, that were associated with dye-filling defects. We reveal that disruption of one of these (BGNT-1.1), whose human orthologue is associated with Walker-Warburg syndrome, results in abrogated uptake of dye and cilia length defects. We believe that our novel approach is useful for any organism with a small genome that can be quickly sequenced and where many mutant strains can be easily isolated and phenotyped, such as Drosophila and Arabidopsis.

Genomics

Skin transcriptome profiles associated with coat color in goat

Capra hircus, an economically important livestock, plays an indispensable role in the world animal fiber industry. To identify additional genes that may play important roles in coat color regulation, Illumina/Solexa high throughput sequencing technology was used to catalog the global gene expression profiles in the skin of three different coat colors goat (Lubei white goat (white), Jining gray goat (gray) and Jianyang big ear goat (brown)). The RNA-Seq analysis generated 83174342, 70222592 and 52091212 clean reads in white skin, gray skin and brown skin, respectively, which provided abundant data for further analysis. A total of 91 genes were differentially expressed between the gray skin and white skin libraries, with 74 upregulated and 17 genes downregulated. Between the brown skin and white skin libraries, there were 23 upregulated genes and 44 downregulated genes, while there were 33 upregulated genes and 121 downregulated genes between the brown skin and gray skin libraries. To our surprise, MC1R, MITF, TYR, KIT and KITLG showed no significant difference in the skin of three different coat colors and the expression of ASIP was only detected in white skin and not in gray and brown skins. The expression of PMEL, TRPM1, DCT, TYRP1 and ELOVL3 was validated by real-time quantitative polymerase chain reaction (qPCR) and the results of the qPCR were consistent with the RNA-seq except the expression of TYRP1 between the gray skin and white skin libraries. This study provides several candidate genes that may be associated with the development of diferent coat colors goat skin. More importantly, the fact that the ASIP gene was only detected in the white skin and not in the other dark skins and the MC1R gene showed no significant difference in expression between the three different coat colors goat is of particular interest for future studies that aim to elucidate theirs functional role in the regulation of skin color. These results will expand our understanding of the complex molecular mechanisms of skin physiology and melanogenesis in goat and provide a foundation for future studies.

Genetics

3D RNA from evolutionary couplings

Non-protein-coding RNAs are ubiquitous in cell physiology, with a diverse repertoire of known functions. In fact, the majority of the eukaryotic genome does not code for proteins, and thousands of conserved long non-protein-coding RNAs of currently unkown function have been identified. When available, knowledge of their 3D structure is very helpful in elucidating the function of these RNAs. However, despite some outstanding structure elucidation of RNAs using X-ray crystallography, NMR and cryoEM, learning RNA 3D structures remains low-throughput. RNA structure prediction in silico is a promising alternative approach and works well for double-helical stems, but full 3D structure determination requires tertiary contacts outside of secondary structures that are difficult to infer from sequence information. Here, based only on information from RNA multiple sequence alignments, we use a global statistical sequence probability model of co-variation in a pairs of nucleotide positions to detect 3D contacts, in analogy to recently developed breakthrough methods for computational protein folding. In blinded tests on 22 known RNA structures ranging in size from 65 to 1800 nucleotides, the predicted contacts matched physical nucleotide interactions with 65-95% true positive prediction accuracy. Importantly, we infer many long-range tertiary contacts, including non-Watson-Crick interactions, where secondary structure elements assemble in 3D. When used as restraints in molecular dynamics simulations, the inferred contacts improve RNA 3D structure prediction to a coordinate error as low as 6 - 10 [A] rmsd deviation in atom positions, with potential for further refinement by molecular dynamics. These contacts include functionally important interactions, such as those that distinguish the active and inactive conformations of four riboswitches. In blind prediction mode, we present evolutionary couplings suitable for folding simulations for 180 RNAs of unknown structure, available at https://marks.hms.harvard.edu/ev_rna/. We anticipate that this approach can help shed light on the structure and function of non-protein-coding RNAs as well as 3D-structured mRNAs.

Bioinformatics