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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2016

Architecture of a minimal signalling pathway explains the T cell response to a 1,000,000-fold variation in antigen affinity and dose

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map pMHC affinity onto T cell responses have produced inconsistent patterns of responses preventing formulations of canonical models of T cell signalling. Here, a systematic analysis of T cell responses to 1,000,000-fold variations in both pMHC affinity and dose produced bell-shaped dose-response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signalling incorporating kinetic proofreading with limited signalling coupled to an incoherent feed forward loop (KPL-IFF), that reproduces these observations. We show that the KPL-IFF model correctly predicts the T cell response to antigen co-presentation. Our work offers a general approach for studying cellular signalling that does not require full details of biochemical pathways.\n\nSignificance statementT cells initiate and regulate adaptive immune responses when their T cell antigen receptors recognise antigens. The T cell response is known to depend on the antigen affinity/dose but the precise relationship, and the mechanisms underlying it, are debated. To resolve the debate, we stimulated T cells with antigens spanning a 1,000,000-fold range in affinity/dose. We found that a different antigen (and hence different affinity) produced the largest T cell response at different doses. Using model identification algorithms, we report a simple mechanistic model that can predict the T cell response from the physiological low affinity regime into the high affinity regime applicable to therapeutic receptors.

Immunology↗

bioRxiv2016

Evolution of cell-to-cell variability in stochastic, controlled, heteroplasmic mtDNA populations

Populations of physiologically vital mitochondrial DNA (mtDNA) molecules evolve in cells under control from the nucleus. The evolution of populations of mixed mtDNA types is complicated and poorly understood, and variability of these controlled admixtures plays a central role in the inheritance and onset of genetic disease. Here, we develop a mathematical theory describing the evolution and variability in these stochastic populations for any type of cellular control, showing that cell-to-cell variability in mtDNA, and mutant load, inevitably increases with time, according to rates which we derive and which are notably independent of the mechanistic details of feedback signalling. We show with a set of experimental case studies that this theory explains disparate quantitative results from classical and modern experimental and computational studies on heteroplasmy variance in different species. We demonstrate that our general model provides a host of specific insights, including a modification of the often-used but hard-to-interpret Wright formula to correspond directly to biological observables, the ability to quantify selective and mutational pressure in mtDNA populations, and the pronounced variability inevitably arising from the action of possible mtDNA quality-control mechanisms. Our general theoretical framework, supported by existing experimental results, thus helps understand and predict the evolution of stochastic mtDNA populations in cell biology.

Genetics↗

bioRxiv2016

A REPETITIVE MODULAR OSCILLATION UNDERLIES HUMAN BRAIN ELECTRIC ACTIVITY

The modular function j, central in the assessment of abstract mathematical problems, describes elliptic, intertwined trajectories that move in the planes of both real and complex numbers. Recent clues suggest that the j-function might display a physical counterpart, equipped with a quantifiable real component and a hidden imaginary one, currently undetectable by our senses and instruments. Here we evaluate whether the real part of the modular function can be spotted in the electric activity of the human brain. We assessed EEGs from five healthy males, eyes-closed and resting state, and superimposed the electric traces with the bidimensional curves predicted by the j-function. We found that the two trajectories matched in more than 85% of cases, independent from the subtending electric rhythm and the electrode location. Therefore, the real part of the j-functions peculiar wave is ubiquitously endowed all over normal EEGs paths. We discuss the implications of such correlation in neuroscience and neurology, highlighting how the j-function might stand for the one of the basic oscillations of the brain, and how the still unexplored imaginary part might underlie several physiological and pathological nervous features.\n\nSIGNIFICANCE STATEMENTOur results point towards the brain as ubiquitously equipped with j-functions oscillations, which movements take place on the plane of the complex numbers. It means that there must be, in brain electric activity, also a veiled complex part, which can be assessed with the help of imaginary numbers. The modular j-function provides further dimensions to the real numbers, in order to enlarge their predictive powers: it suggests the possible presence of hidden (functional or spatial) brain extra-dimensions. Furthermore, j-oscillations could be disrupted during pathologies, paving the way to novel approaches to central nervous systems diseases.

Neuroscience↗

bioRxiv2016

Schizophrenia and human self-domestication: a linguistic approach

Schizophrenia (SZ) is a pervasive neurodevelopmental disorder entailing social and cognitive deficits, including marked problems with language. Its complex multifactorial etiopathogenesis, including genetic and environmental factors, is still widely uncertain. SZ incidence has always been high and quite stable in human populations, across time and regardless of cultural implications, due to unclear reasons. It has been hypothesised that SZ pathophysiology may involve the biological components that changed during the recent human evolutionary history and led to our distinctive mode of cognition, which includes language skills. In this paper we explore this possibility, focusing on the self-domestication of the human species. This has been claimed to account for many human-specific distinctive traits, including aspects of our behaviour and cognition, and to favour the emergence of complex languages through cultural evolution. The \"domestication syndrome\" in mammals comprises the constellation of traits exhibited by domesticated strains, seemingly resulting from the hypofunction of the neural crest. It is our intention to show that people with SZ exhibit more marked domesticated traits at the morphological, physiological, and behavioural levels. We also show that genes involved in domestication and neural crest development and function comprise nearly 20% SZ candidates, most of which exhibit altered expression profiles in the brain of SZ patients, specifically in areas involved in language processing. Based on these observations, we conclude that SZ may represent an abnormal ontogenetic itinerary for the human faculty of language, resulting, at least in part, from changes in genes important for the \"domestication syndrome\" and, primarily involving the neural crest.

Neuroscience↗

bioRxiv2016

Major host transitions are modulated through transcriptome-wide reprograming events in Schistocephalus solidus, a threespine stickleback parasite

Parasites with complex life cycles have developed numerous phenotypic strategies, closely associated with developmental events, to enable the exploitation of different ecological niches and facilitate transmission between hosts. How these environmental shifts are regulated from a metabolic and physiological standpoint, however, still remain to be fully elucidated. We examined the transcriptomic response of Schistocephalus solidus, a trophically-transmitted parasite with a complex life cycle, over the course of its development in an intermediate host, the threespine stickleback, and the final avian host. Results from our differential gene expression analysis show major reprogramming events among developmental stages. The final host stage is characterized by a strong activation of reproductive pathways and redox homeostasis. The attainment of infectivity in the fish intermediate host - which precedes sexual maturation in the final host and is associated with host behaviour changes - is marked by transcription of genes involved in neural pathways and sensory perception. Our results suggest that un-annotated and S. solidus-specific genes could play a determinant role in host-parasite molecular interactions required to complete the parasites life cycle. Our results permit future comparative analyses to help disentangle species-specific patterns of infection from conserved mechanisms, ultimately leading to a better understanding of the molecular control and evolution of complex life cycles.

Genomics↗

bioRxiv2016

Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations

The network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease.The striatum is the input nucleus of the basal ganglia that receives massive glutamatergic inputs from the cortex and is highly susceptible to cortical oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, periodic external stimuli propagate through the striatal circuitry. Using a large-scale network model of the striatum and corticostriatal projections, here we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Our results show that fast-spiking interneurons, despite their uncorrelated firing, might have a crucial role in the emergence of high-frequency oscillations in the medium spiny neuron population, even if their activity is kept low. Rather, what matters is the firing time relative to just a few other neurons within an oscillation cycle. Finally, we show how the state of ongoing activity, the strengths of different types of inhibitions, the density of outgoing projections, and the overall activity of striatal cells influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is efficient, if indirect, through fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.\n\nAuthor SummaryThe striatum is the largest and primary gateway component of the BG, receiving glutamatergic inputs from all cortical areas and is highly susceptible to cortical oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. The vast majority of striatal neurons, at least 95% of them, are medium spiny neurons (MSNs) that are also the only source of output from the nucleus. Two of the most examined sources of GABAergic inhibition into MSNs are the feedback inhibition (FB) from the axon collaterals of the MSNs themselves, and the feedforward inhibition (FF) via the small population of fast-spiking interneurons (FSIs) comprising roughly 1-2% of striatal neurons. Using a large-scale network model of the striatum we systematically investigate the propagation of asynchronous periodic cortical inputs, throughout the physiologically relevant range, onto the striatal neurons and their influence on striatal network dynamics. Our results show that FSIs, despite their firing being uncorrelated, may play a crucial role in the efficient propagation of external oscillations onto MSNs. Finally, we show how the state of ongoing activity, the strengths of different types of inhibitions, the density of outgoing projections, and the overall activity of striatal cells influence network activity.

Neuroscience↗

bioRxiv2016

ENVIREM: An expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling

Species distribution modeling is a valuable tool with many applications across ecology and evolutionary biology. The selection of biologically meaningful environmental variables that determine relative habitat suitability is a crucial aspect of the modeling pipeline. The 19 bioclimatic variables from WorldClim are frequently employed, primarily because they are easily accessible and available globally for past, present and future climate scenarios. Yet, the availability of relatively few other comparable environmental datasets potentially limits our ability to select appropriate variables that will most successfully characterize a species distribution. We identified a set of 16 climatic and two topographic variables in the literature, which we call the O_SCPLOWENVIREMC_SCPLOW dataset, many of which are likely to have direct relevance to ecological or physiological processes determining species distributions. We generated this set of variables at the same resolutions as WorldClim, for the present, mid-Holocene, and Last Glacial Maximum (LGM). For 20 North American vertebrate species, we then assessed whether including the O_SCPLOWENVIREMC_SCPLOW variables led to improved species distribution models compared to models using only the existing WorldClim variables. We found that including the ENVIREM dataset in the pool of variables to select from led to substantial improvements in niche modeling performance in 17 out of 20 species. We also show that, when comparing models constructed with different environmental variables, differences in projected distributions were often greater in the LGM than in the present. These variables are worth consideration in species distribution modeling applications, especially as many of the variables have direct links to processes important for species ecology. We provide these variables for download at multiple resolutions and for several time periods at envirem.github.io. Furthermore, we have written the envirem R package to facilitate the generation of these variables from other input datasets.

Ecology↗

bioRxiv2016

Antibiotic susceptibility of bacterial colonies: An assay and experiments with Staphylococcus aureus.

A method is presented to evaluate in vitro the efficacy of antibiotics to treat bacteria growing as discrete colonies on surfaces and the contribution of the colony structure to the antibiotic susceptibility of bacteria. Using this method, we explored the relative efficacy of six bactericidal and three bacteriostatic antibiotics to inhibit the growth and kill Staphylococcus aureus colonies of different sizes, densities and ages. As measured by the reduction in viable cell density relative to untreated controls, of the bactericidal drugs tested ciprofloxacin and gentamicin were most effective. By this criteria, ampicillin was more effective than oxacillin. Daptomycin and vancomycin were virtually ineffective for treating S. aureus growing as colonies. The bacteriostatic antibiotic tested, tetracycline, linezolid and erythromycin were all able to prevent the growth of S. aureus colonies and did so even more effectively than daptomycin, which is highly bactericidal in liquid culture. The results of these experiments and other observations suggest that relative inefficacy of oxacillin, vancomycin and daptomycin to kill S. aureus in colonies is due to the density and physiological state of the bacteria rather than the inability of these drugs to penetrate the colonies. The methods developed here are general and can be used to explore the efficacy of antibiotics to treat bacteria growing in biofilms as well as discrete colonies.

Microbiology↗

bioRxiv2016

Single variant bottleneck in the early dynamics of H. influenzae bacteremia in neonatal rats questions the theory of independent action

There is an abundance of information about the genetic basis, physiological and molecular mechanisms of bacterial pathogenesis. In contrast, relatively little is known about population dynamic processes, by which bacteria colonize hosts and invade tissues and cells and thereby cause disease. In an article published in 1978, Moxon and Murphy presented evidence that, when inoculated intranasally with a mixture streptomycin sensitive and resistant (SmS and SmR) and otherwise isogenic stains of Haemophilus influenzae type b (Hib), neonatal rats develop a bacteremic infection that often is dominated by only one strain, SmS or SmR. After rulling out other possibilities through years of related experiments, the field seems to have settled on a plausible explanation for this phenomenon: the first bacterium to invade the host activates the host immune response that shuts the door on the second invading strain. To explore this hypothesis in a necessarily quantitative way, we modeled this process with a set of mixed stochastic and deterministic differential equations. Our analysis of the properties of this model with realistic parameters suggests that this hypothesis cannot explain the experimental results of Moxon and Murphy, and in particular the observed relationship between the frequency of different types of blood infections (bacteremias) and the inoculum size. We propose modifications to the model that come closer to explaining these data. However, the modified and better fitting model contradicts the common theory of independent action of individual bacteria in establishing infections. We discuss the implications of these results.

Biophysics↗

bioRxiv2016

Bursting deep dorsal horn neurons: the pharmacological target for the anti-spastic effects of Zolmitriptan?

In a recent publication, Thaweerattanasinp and colleagues employed an in vitro preparation and electrophysiology to investigate firing properties of deep dorsal horn neurons following spinal cord injury during NMDA or zolmitriptan application. Deep dorsal horn neurons were classified into bursting, simple or tonic, with bursting neurons showing NMDA and zolmitriptan sensitivity. Here, we discuss the findings in a methodological framework and propose future experiments of importance for translating the results into a physiological setting.

Neuroscience↗

bioRxiv2016

Towards an Open Data Framework for Body Sensor Networks Supporting Bluetooth Low Energy

Major companies, healthcare professionals, the military, and other scientists and innovators are now sensing that fitness and health data from wearable biosensors will likely provide new discoveries and insights into physiological, cognitive, and emotional health status of an individual. Having the ability to collect, process, and correlate data simultaneously from a set of heterogonous biosensor sources may be a key factor in informing the development of new technologies for reducing health risks, improving health status, and possibly preventing and predicting disease. The challenge in achieving this is getting easy access to heterogeneous data from a set of disparate sensors in a single, integrated wearable monitoring system. Often times, the data recorded by commercial biosensing devices are contained within each manufacturers proprietary platform. Summary data is available for some devices as free downloads or included only in annual premium memberships. Access to raw measurements is generally unavailable, especially from a custom developed application that may include prototype biosensors. In this paper, we explore key ideas on how to leverage the design features of Bluetooth Low Energy to ease the integration of disparate biosensors at the sensor communication layer. This component is intended to fit into a larger, multi-layered, open data framework that can provide additional data management and analytics capabilities for consumers and scientists alike at all the layers of a data access model which is typically employed in a body sensor network system.

Bioinformatics↗

bioRxiv2016

Parasitic Infection by Pseudocapillaria tomentosa is Associated with a Longitudinal Restructuring of the Zebrafish Gut Microbiome

Helminth parasites represent a significant threat to wild, domesticated, and research animal health. Pseudocapillaria tomentosa is a common intestinal nematode parasite and an important source of infection in zebrafish. Symptoms of the infection vary widely from no clinical signs to sever emaciation and mortality, however, the reasons underpinning these disparate outcomes are unclear. Components of the microbiome may interact with parasites to influence their success in the gut while parasite infections are also known to influence the composition of the gut microbiome. In this study we evaluated the longitudinal changes in the gut microbiome structure and gut physiology during experimental P. tomentosa infection in adult 5D line zebrafish. We observed less severe signs of infection and less mortality in these fish than previously described in AB line fish. However, inflammation and epithelial hyperplasia in the intestine was still observed in infected 5D line fish. The composition of the microbiome changed rapidly during the infection and these changes were associated with parasite stage of development and burden. Individual taxa covaried with parasite abundance in the intestine intimating the gut microbiome may influence parasite burden. Associations between taxa and parasite abundance in some cases appeared to be phylogenetically patterned. Strong positive associations were observed between OTUs phylotyped to Proteobacteria and abundance of adult parasites and parasite eggs. Together these experiments demonstrate that P. tomentosa infection results in a rapid and temporally dynamic disruption of the zebrafish gut microbiome and clarify how interactions between the gut microbiome and intestinal parasites may impact fish populations.

Microbiology↗

bioRxiv2016

Time to wake up: Studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal

Functional magnetic resonance imaging (fMRI) has allowed the noninvasive study of task-based and resting-state brain dynamics in humans by inferring neural activity from blood-oxygenation-level dependent (BOLD) signal changes. An accurate interpretation of the hemodynamic changes that underlie fMRI signals depends on the understanding of the quantitative relationship between changes in neural activity and changes in cerebral blood flow, oxygenation and volume. While there has been extensive study of neurovascular coupling in anesthetized animal models, anesthesia causes large disruptions of brain metabolism, neural responsiveness and cardiovascular function. Here, we review work showing that neurovascular coupling and brain circuit function in the awake animal are profoundly different from those in the anesthetized state. We argue that the time is right to study neurovascular coupling and brain circuit function in the awake animal to bridge the physiological mechanisms that underlie animal and human neuroimaging signals, and to interpret them in light of underlying neural mechanisms. Lastly, we discuss recent experimental innovations that have enabled the study of neurovascular coupling and brain-wide circuit function in un-anesthetized and behaving animal models.

Neuroscience↗

bioRxiv2016

In−silico studies of facilitated VEGF(s) − VEGFR(s) bindings for assessment of Lysine as an indirect Low−Mol−Wt angiogen: Experimental validation of a potential synthetic Low−Mol−Wt angiogen.

In-vivo angiogenesis process is highly conserved and is mediated through a family of peptides having VEGF-A as the lead member. A respective receptor family comprising of members VEGFR-1, 2, 3 gets expressed on the endothelial cell membrane of the vascular bed in ischemic zone along with parallel expressions of VEGF-A, B, C, D and PlGF. Degree of ischaemia is the main regulator of these coupled expressions of angiogenic peptides/factors (AFs) and respective receptor(s) for a paracrine angiogenic process to take place. Physiological angiogenesis in intrauterine growth phase is the lead process in foetal growth, organogenesis and cellular specialization. Post birth and with aging, this process gets gradually inefficient and slow. In the present in-silico study, all angiogenic factors and receptor species are examined as for their binding stability in basal unaided condition and in presence of a possible Low-Mol-Wt linkage molecule-Lysine. Also a Lysine analogue 1,6-diaminohexanoic acid has been examined for its angiogenic potential both in dry docking experiment and in cell culture assay.

Molecular Biology↗

bioRxiv2016

Transcriptional regulatory logic of the diurnal cycle in the mouse liver

Many organisms exhibit temporal rhythms in gene expression that propel diurnal cycles in physiology. In the liver of mammals, these rhythms are controlled by transcription-translation feedback loops of the core circadian clock and by feeding-fasting cycles. To better understand the regulatory interplay between the circadian clock and feeding rhythms, we mapped DNase I hypersensitive sites (DHSs) in mouse liver during a diurnal cycle. The intensity of DNase I cleavages cycled at a substantial fraction of all DHSs, suggesting that DHSs harbor regulatory elements that control rhythmic transcription. Using ChIP-seq, we found that hypersensitivity cycled in phase with RNA polymerase II (Pol II) loading and H3K27ac histone marks. We then combined the DHSs with temporal Pol II profiles in wild-type (WT) and Bmal1-/- livers to computationally identify transcription factors through which the core clock and feeding-fasting cycles control diurnal rhythms in transcription. While a similar number of mRNAs accumulated rhythmically in Bmal1-/- compared to WT livers, the amplitudes in Bmal1-/- were generally lower. The residual rhythms in Bmal1-/- reflected transcriptional regulators mediating feeding-fasting responses as well as responses to rhythmic systemic signals. Finally, the analysis of DNase I cuts at nucleotide resolution showed dynamically changing footprint consistent with dynamic binding of CLOCK:BMAL1 complexes. Structural modeling suggested that these footprints are driven by a transient hetero-tetramer binding configuration at peak activity. Together, our temporal DNase I mappings allowed us to decipher the global regulation of diurnal transcription rhythms in mouse liver.

Genomics↗

bioRxiv2016

A forward model at Purkinje cell synapses facilitates cerebellar anticipatory motor control

How does our motor system solve the problem of anticipatory control in spite of a wide spectrum of response dynamics from different musculo-skeletal systems, transport delays as well as response latencies throughout the central nervous system? To a great extent, our highly-skilled motor responses are a result of a reactive feedback system, originating in the brain-stem and spinal cord, combined with a feed-forward anticipatory system, that is adaptively fine-tuned by sensory experience and originates in the cerebellum. Based on that interaction we design the counterfactual predictive control (CFPC) architecture, an anticipatory adaptive motor control scheme, in which a feed-forward module, based on the cerebellum, steers an error feedback controller with counterfactual error signals. Those are signals that trigger reactions as actual errors would, but that do not code for any current of forthcoming errors. In order to determine the optimal learning strategy, we derive a novel learning rule for the feed-forward module that involves an eligibility trace and operates at the synaptic level. In particular, our eligibility trace provides a mechanism beyond co-incidence detection in that it convolves a history of prior synaptic inputs with error signals. In the context of cerebellar physiology, this solution implies that Purkinje cell synapses should generate eligibility traces using a forward model of the system being controlled. From an engineering perspective, CFPC provides a general-purpose anticipatory control architecture equipped with a learning rule that exploits the full dynamics of the closed-loop system.

Neuroscience↗

bioRxiv2016

Mitochondrial DNA Density Homeostasis Accounts for the Threshold Effect in Human Mitochondrial Disease

Mitochondrial dysfunction is involved in a wide array of devastating diseases but the heterogeneity and complexity of these diseases symptoms challenges theoretical understanding of their causation. With the explosion of -omics data, we have the unprecedented ability to gain deep understanding of the biochemical mechanisms of mitochondrial dysfunction. However, there is also a need to make such datasets interpretable, and quantitative modelling allows us to translate such datasets into intuition and suggest rational biomedical treatments. Working towards this interdisciplinary goal, we use a recently published large-scale dataset, and develop a mathematical model of progressive increase in mutant load of the MELAS 3243A>G mtDNA mutation to develop a descriptive and predictive biophysical model. The experimentally observed behaviour is surprisingly rich, but we find that a simple, biophysically-motivated model intuitively accounts for this heterogeneity and yields a wealth of biological predictions. Our findings suggest that cells attempt to maintain wild-type mtDNA density through cell volume reduction, and thus energy demand reduction, until a minimum cell volume is reached. Thereafter, cells toggle from demand reduction to supply increase, upregulating energy production pathways. Our analysis provides further evidence for the physiological significance of mtDNA density, and emphasizes the need for performing single-cell volume measurements jointly with mtDNA quantification. We propose novel experiments to verify the hypotheses made here, to further develop our understanding of the threshold effect, and connect with rational choices for mtDNA disease therapies.\n\nAuthor SummaryMitochondria are organelles which produce the major energy currency of the cell: ATP. Mitochondrial dysfunction is associated with a multitude of devastating diseases, from Parkinsons disease to cancer. Large volumes of data related to these diseases are being produced, but translation of these data into rational biomedical treatment is challenged by a lack of theoretical understanding. We develop a mathematical model of progressive increase of mutant load in mitochondrial DNA, for the mutation associated with MELAS (the most common mitochondrial disease), to address this. We predict that cells attempt to maintain the ratio of healthy mtDNA to cell volume by reducing their cell volume until they reach a minimum cell volume. As mutant load continues to increase, cells switch strategy by increasing their energy supply pathways. Our work accounts for large-scale experimental data and makes testable predictions about mitochondrial dysfunction. It also provides support for increasing mitochondrial content, as well as reduction in dependence upon mitochondrial metabolism via the ketogenic diet, as relevant treatments for mitochondrial disease.

Cell Biology↗

bioRxiv2016

Sequencing of small RNAs of the fern Pleopeltis minima (Polypodiaceae) offers insight into the evolution of the microRNA repertoire in land plants

MicroRNAs (miRNAs) are short, single stranded RNA molecules that regulate the stability and translation of messenger RNAs in diverse eukaryotic groups. Several miRNA genes are of ancient origin and have been maintained in the genomes of animal and plant taxa for hundreds of millions of years, and functional studies indicate that ancient miRNAs play key roles in development and physiology. In the last decade, genome and small RNA (sRNA) sequencing of several plant species have helped unveil the evolutionary history of land plant miRNAs. Land plants are divided into bryophytes (liverworts, mosses), lycopods (clubmosses and spikemosses), monilophytes (ferns and horsetails), gymnosperms (cycads, conifers and allies) and angiosperms (flowering plants). Among these, the fern group occupies a key phylogenetic position, since it represents the closest extant cousin taxon of seed plants, i.e. gymno- and angiosperms. However, in spite of their evolutionary, economic and ecological importance, no fern genome has been sequenced yet and few genomic resources are available for this group. Here, we sequenced the small RNA fraction of an epiphytic South American fern, Pleopeltis minima (Polypodiaceae), and compared it to plant miRNA databases, allowing for the identification of miRNA families that are shared by all land plants, shared by all vascular plants (tracheophytes) or shared by euphyllophytes (ferns and seed plants) only. Using the recently described transcriptome of another fern, Lygodium japonicum, we also estimated the degree of conservation of fern miRNA targets in relation to other plant groups. Our results pinpoint the origin of several miRNA families in the land plant evolutionary tree with more precision and are a resource for future genomic and functional studies of fern miRNAs.

Plant Biology↗