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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2014

The genomic signature of social interactions regulating honey bee caste development

Social evolution theory posits the existence of genes expressed in one individual that affect the traits and fitness of social partners. The archetypal example of reproductive altruism, honey bee reproductive caste, involves strict social regulation of larval caste fate by care-giving nurses. However, the contribution of nurse-expressed genes, which are prime socially-acting candidate genes, to the caste developmental program and to caste evolution remains mostly unknown. We experimentally induced new queen production by removing the current colony queen, and we used RNA sequencing to study the gene expression profiles of both developing larvae and their care-giving nurses before and after queen removal. By comparing the gene expression profiles between both queen-destined larvae and their nurses to worker-destined larvae and their nurses in queen-present and queen-absent conditions, we identified larval and nurse genes associated with larval caste development and with queen presence. Of 950 differentially-expressed genes associated with larval caste development, 82% were expressed in larvae and 18% were expressed in nurses. Behavioral and physiological evidence suggests that nurses may specialize in the short term feeding queen- versus worker-destined larvae. Estimated selection coefficients indicated that both nurse and larval genes associated with caste are rapidly evolving, especially those genes associated with worker development. Of the 1863 differentially-expressed genes associated with queen presence, 90% were expressed in nurses. Altogether, our results suggest that socially-acting genes play important roles in both the expression and evolution of socially-influenced traits like caste.

Genomics↗

bioRxiv2014

Pre-synaptic inhibition of afferent feedback in the macaque spinal cord does not modulate with cycles of peripheral oscillations around 10 Hz

Spinal interneurons are partially phase-locked to physiological tremor around 10Hz. The phase of spinal interneuron activity is approximately opposite to descending drive to motoneurons, leading to partial phase cancellation and tremor reduction. Pre-synaptic inhibition of afferent feedback modulates during voluntary movements, but it is not known whether it tracks more rapid fluctuations in motor output such as during tremor.\n\nIn this study, dorsal root potentials (DRPs) were recorded from the C8 and T1 roots in two macaque monkeys following intra-spinal micro-stimulation (random inter-stimulus interval 1.5-2.5 s, 30-100A), whilst the animals performed an index finger flexion task which elicited peripheral oscillations around 10Hz. Forty one responses were identified with latency <5ms; these were narrow (mean width 0.59 ms), and likely resulted from antidromic activation of afferents following stimulation near terminals. Significant modulation during task performance occurred in 16/41 responses, reflecting terminal excitability changes generated by pre-synaptic inhibition (Walls excitability test). Stimuli falling during large-amplitude 8-12Hz oscillations in finger acceleration were extracted, and sub-averages of DRPs constructed for stimuli delivered at different oscillation phases. Although some apparent phase-dependent modulation was seen, this was not above the level expected by chance.\n\nWe conclude that although terminal excitability reflecting pre-synaptic inhibition of afferents modulates over the timescale of a voluntary movement, it does not follow more rapid changes in motor output. This suggests that pre-synaptic inhibition is not part of the spinal systems for tremor reduction described previously, and that it plays a role in overall - but not moment-by-moment - regulation of feedback gain.

Neuroscience↗

bioRxiv2014

Model checking to assess T-helper cell plasticity

Computational modeling constitutes a crucial step towards the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant to convey external stimuli, or environmental cues. In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors (e.g. stable states). The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity.\n\nIn this article, we present a multivalued logical framework along with computational methods recently developed to efficiently analyze large models. We mainly focus on a symbolic model checking approach to investigate switches between attractors subsequent to changes of input conditions.\n\nAs a case study, we consider the cellular network regulating the differentiation of T-helper cells, which orchestrate many physiological and pathological immune responses. To account for novel cellular subtypes, we present an extended version of a published model of T-helper cell differentiation. We then use symbolic model checking to analyze reachability properties between T-helper subtypes upon changes of environmental cues. This allows for the construction of a synthetic view of T-helper cell plasticity in terms of a graph connecting subtypes with arcs labeled by input conditions. Finally, we explore novel strategies enabling specific T-helper cell polarizing or reprograming events.

Systems Biology↗

bioRxiv2015

Animal Models of Epilepsy: Legacies and New Directions

Human epilepsies encompass a wide variety of clinical, behavioral and electrical manifestations. Correspondingly, studies of this disease in nonhuman animals have brought forward an equally wide array of animal models, i.e. species and acute or chronic seizure induction protocols. Epilepsy research has a long history of comparative anatomical and physiological studies on a range of mostly mammalian species. Nonetheless, a relatively limited number of rodent models emerged as the primary choices for most epilepsy-related investigations. In many cases these animal models are selected based on convenience or tradition, though technical or experimental rationale does, and should, factor into these decisions. More complex mammalian brains and, especially, genetic model organisms including zebrafish have been studied less but offer significant advantages that are being widely recognized.

Neuroscience↗

bioRxiv2015

Asynchronous Rate Chaos in Spiking Neuronal Circuits

The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results.\n\nAuthor SummaryCortical circuits exhibit complex temporal patterns of spiking and are exquisitely sensitive to small perturbations in their ongoing activity. These features are all suggestive of an underlying chaotic dynamics. Theoretical works have indicated that a rich dynamical reservoir can endow neuronal circuits with remarkable computational capabilities. Nevertheless, the mechanisms underlying chaos in circuits of spiking neurons remain unknown. We combine analytical calculations and numerical simulations to investigate this fundamental issue. Our key result is that chaotic firing rate fluctuations on the time scales of the synaptic dynamics emerge generically from the network collective dynamics. Our results pave the way in the study of the physiological mechanisms and computational significance of chaotic states in neuronal networks.

Neuroscience↗

bioRxiv2015

Reprogramming LCLs to iPSCs Results in Recovery of Donor-Specific Gene Expression Signature

Renewable in vitro cell cultures, such as lymphoblastoid cell lines (LCLs), have facilitated studies that contributed to our understanding of genetic influence on human traits. However, the degree to which cell lines faithfully maintain differences in donor-specific phenotypes is still debated. We have previously reported that standard cell line maintenance practice results in a loss of donor-specific gene expression signatures in LCLs. An alternative to the LCL model is the induced pluripotent stem cell (iPSC) system, which carries the potential to model tissue-specific physiology through the use of differentiation protocols. Still, existing LCL banks represent an important source of starting material for iPSC generation, and it is possible that the disruptions in gene regulation associated with long-term LCL maintenance could persist through the reprogramming process. To address this concern, we studied the effect of reprogramming mature LCLs to iPSCs on the ensuing gene expression patterns within and between six unrelated donor individuals. We show that the reprogramming process results in a recovery of donor-specific gene regulatory signatures. Since environmental contributions are unlikely to be a source of individual variation in our system of highly passaged cultured cell lines, our observations suggest that the effect of genotype on gene regulation is more pronounced in the iPSCs than in the LCL precursors. Our findings indicate that iPSCs can be a powerful model system for studies of phenotypic variation across individuals in general, and the genetic association with variation in gene regulation in particular. We further conclude that LCLs are an appropriate starting material for iPSC generation.

Genomics↗

bioRxiv2015

Integrating crop growth models with whole genome prediction through approximate Bayesian computation

Genomic selection, enabled by whole genome prediction (WGP) methods, is revolutionizing plant breeding. Existing WGP methods have been shown to deliver accurate predictions in the most common settings, such as prediction of across environment performance for traits with additive gene effects. However, prediction of traits with non-additive gene effects and prediction of genotype by environment interaction (GxE), continues to be challenging. Previous attempts to increase prediction accuracy for these particularly difficult tasks employed prediction methods that are purely statistical in nature. Augmenting the statistical methods with biological knowledge has been largely overlooked thus far. Crop growth models (CGMs) attempt to represent the impact of functional relationships between plant physiology and the environment in the formation of yield and similar output traits of interest. Thus, they can explain the impact of GxE and certain types of non-additive gene effects on the expressed phenotype. Approximate Bayesian computation (ABC), a novel and powerful computational procedure, allows the incorporation of CGMs directly into the estimation of whole genome marker effects in WGP. Here we provide a proof of concept study for this novel approach and demonstrate its use with synthetic data sets. We show that this novel approach can be considerably more accurate than the benchmark WGP method GBLUP in predicting performance in environments represented in the estimation set as well as in previously unobserved environments for traits determined by non-additive gene effects. We conclude that this proof of concept demonstrates that using ABC for incorporating biological knowledge in the form of CGMs into WGP is a very promising and novel approach to improving prediction accuracy for some of the most challenging scenarios in plant breeding and applied genetics.

Genetics↗

bioRxiv2015

Revisiting Demand Rules for Gene Regulation

Starting with Savageaus pioneering work from 1970s, here, we choose the simplest transcription network and ask: How does the cell choose a regulatory topology from the different available possibilities? We study the natural distribution of topologies at genome, systems, and micro-level in E. coli and perform stochastic simulations to help explain the differences in natural distributions. Analyzing regulation of amino acid biosynthesis and carbon utilization in E. coli and B. subtilis, we observe many deviations from the demand rules, and observe an alternate pattern emerging. Overall, our results indicate that choice of topology is drawn randomly from a pool of all networks which satisfy the kinetic requirements of the cell, as dictated by physiology. In short, simply, the cell picks \"whatever works\".

Systems Biology↗

bioRxiv2015

Ca-activation kinetics modulate successive puff/spark amplitude, duration and inter-event-interval correlations in a Langevin model of stochastic Ca release

Through theoretical analysis of the statistics of stochastic calcium (Ca2+) release (i.e., the amplitude, duration and inter-event interval of simulated Ca2+ puffs and sparks), we show that a Langevin description of the collective gating of Ca2+ channels may be a good approximation to the corresponding Markov chain model when the number of Ca2+ channels per Ca2+ release unit (CaRU) is in the physiological range. The Langevin description of stochastic Ca2+ release facilitates our investigation of correlations between successive puff/spark amplitudes, durations and inter-spark intervals, and how such puff/spark statistics depend on the number of channels per release site and the kinetics of Ca2+-mediated inactivation of open channels. When Ca2+ inactivation/de-inactivation rates are intermediate--i.e., the termination of Ca2+ puff/sparks is caused by the recruitment of inactivated channels--the correlation between successive puff/spark amplitudes is negative, while the correlations between puff/spark amplitudes and the duration of the preceding or subsequent inter-spark interval are positive. These correlations are significantly reduced when inactivation/deinactivation rates are extreme (slow or fast) and puff/sparks terminate via stochastic attrition.

Cell Biology↗

bioRxiv2015

Genomic Diversity and Climate Adaptation in Brachypodium

The Brachypodium genus contains the model grasses B. distachyon, B. stacei and B. hybridum, that are useful for molecular and physiological studies relevant to grain, pasture and bioenergy crops, as well as ecology. In this chapter we discuss the natural variation in climate/geography, genotypic and phenotypic diversity that exists within these species. We describe utilisation of this diversity via two methods, Genome Wide Association Studies and Landscape Genomics, to examine the interaction between specific genetic variants, phenotype, and environment. The aim is to identify adaptive loci that control specific traits in specific environments and understand the contribution of background polygenetic variation shaped by demographic processes. With recent developments in high throughput phenotyping, cheaper genotyping by sequencing and higher spatial/temporal resolution of climate data, these approaches can exploit the diversity of the Brachypodium. Experiments using this toolkit will reveal alleles, genes and pathways underlying agriculturally important and environmentally sensitive traits for use in grass breeding.

Plant Biology↗

bioRxiv2015

Identification of novel transcriptional regulators of PKA subunits in Saccharomyces cerevisiae by Quantitative Promoter–Reporter Screening

The cAMP dependent protein kinase (PKA) signaling is a broad specificity pathway that plays important roles in the transduction of environmental signals triggering precise physiological responses. cAMP-signal transduction specificity is achieved and controlled at several levels. The Saccharomyces cereviciae PKA holoenzyme consists of two catalytic subunits encoded by TPK1, TPK2 and TPK3 genes, and two regulatory subunits encoded by BCY1 gene. In this work we studied the activity of these gene promoters using a reporter-synthetic genetic array screen, with the goal of identifying novel regulators of PKA subunits expression. Gene ontology (GO) analysis of the regulators identified showed that these regulators were enriched for annotations associated with roles in several GO biological process, as lipid and phosphate metabolism or transcription regulation and regulate all or some of the four promoters. Further characterization of the effect of these pathways on promoter activity and mRNA levels pointed to inositol, inositol polyphosphates, choline and phosphate as novel upstream signals that regulate transcription of PKA subunit genes. In addition, within each category there are genes that regulate only one of the promoters and genes that regulate more than one of them at the same time. These results support the role of transcription regulation of each PKA subunit in cAMP specificity signaling. Interestingly, many of the known targets of PKA phosphorylation are associated with the identified pathways, opening the possibility of a reciprocal regulation in which PKA would be coordinating different metabolic pathways and these processes would in turn, regulate expression of the kinase subunits.

Molecular Biology↗

bioRxiv2015

A matter of attention: Crossmodal congruence enhances and impairs performance in a novel trimodal matching paradigm

A novel crossmodal matching paradigm including vision, audition, and somatosensation was developed in order to investigate the interaction between attention and crossmodal congruence in multisensory integration. To that end, all three modalities were stimulated concurrently while a bimodal focus was defined blockwise. Congruence between stimulus intensity changes in the attended modalities had to be evaluated. We found that crossmodal congruence improved performance if both, the attended modalities and the task-irrelevant distractor were congruent. If the attended modalities were incongruent, the distractor impaired performance due to its congruence relation to one of the attended modalities. Between attentional conditions, magnitudes of crossmodal enhancement or impairment differed. Largest crossmodal effects were seen in visual-tactile matching, intermediate effects for audio-visual and smallest effects for audio-tactile matching. We conclude that differences in crossmodal matching likely reflect characteristics of multisensory neural network architecture. We discuss our results with respect to the timing of perceptual processing and state hypotheses for future physiological studies. Finally, etiological questions are addressed.

Neuroscience↗

bioRxiv2015

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown roots systems

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multidimensional amalgam of inputs enables continuous adjustment of root growth rates, direction and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.

Plant Biology↗

bioRxiv2015

Processes driving nocturnal transpiration and implications for estimating land evapotranspiration

Evapotranspiration is a major component of the water cycle, yet only daytime transpiration is currently considered in Earth system and agricultural sciences. This contrasts with physiological studies where 25% or more of water losses have been reported to occur occurring overnight at leaf and plant scales. This gap probably arose from limitations in techniques to measure nocturnal water fluxes at ecosystem scales, a gap we bridge here by using lysimeters under controlled environmental conditions. The magnitude of the nocturnal water losses (12-23% of daytime water losses) in row-crop monocultures of bean (annual herb) and cotton (woody shrub) would be globally an order of magnitude higher than documented responses of global evapotranspiration to climate change (51-98 vs. 7-8 mm yr-1). Contrary to daytime responses and to conventional wisdom, nocturnal transpiration was not affected by previous radiation loads or carbon uptake, and showed a temporal pattern independent of vapour pressure deficit or temperature, because of endogenous controls on stomatal conductance via circadian regulation. Our results have important implications from large-scale ecosystem modelling to crop production: homeostatic water losses justify simple empirical predictive functions, and circadian controls show a fine-tune control that minimizes water loss while potentially increasing posterior carbon uptake.

Plant Biology↗

bioRxiv2015

Genome of octoploid plant maca (Lepidium meyenii) illuminates genomic basis for high altitude adaptation in the central Andes

Maca (Lepidium meyenii Walp, 2n = 8x = 64) of Brassicaceae family is an Andean economic plant cultivated on the 4000-4500 meters central sierra in Peru. Considering the rapid uplift of central Andes occurred 5 to 10 million years ago (Mya), an evolutionary question arises on how plants like maca acquire high altitude adaptation within short geological period. Here, we report the high-quality genome assembly of maca, in which two close-spaced maca-specific whole genome duplications (WGDs, [~] 6.7 Mya) were identified. Comparative genomics between maca and close-related Brassicaceae species revealed expansions of maca genes and gene families involved in abiotic stress response, hormone signaling pathway and secondary metabolite biosynthesis via WGDs. Retention and subsequent evolution of many duplicated genes may account for the morphological and physiological changes (i.e. small leaf shape and loss of vernalization) in maca for high altitude environment. Additionally, some duplicated maca genes under positive selection were identified with functions in morphological adaptation (i.e. MYB59) and development (i.e. GDPD5 and HDA9). Collectively, the octoploid maca genome sheds light on the important roles of WGDs in plant high altitude adaptation in the Andes.

Genomics↗

bioRxiv2015

A Novel Mechanism for Color Vision: Pupil Shape and Chromatic Aberration Can Provide Spectral Discrimination for Color Blind Organisms.

We present a mechanism by which organisms with only a single photoreceptor, that have a monochromatic view of the world, can achieve color discrimination. The combination of an off-axis pupil and the principle of chromatic aberration (where light of different colors focus at different distances behind a lens) can combine to provide \"color-blind\" animals with a way to distinguish colors. As a specific example we constructed a computer model of the visual system of cephalopods, (octopus, squid, and cuttlefish) that have a single unfiltered photoreceptor type. Nevertheless, cephalopods dramatically change color both to produce chromatically-matched camouflage and to signal conspecifics. This presents a paradox - an apparent ability to determine color in organisms with a monochromatic visual system - that has been a long-standing puzzle. We demonstrate that chromatic blurring dominates the visual acuity in these animals, and we quantitatively show how chromatic aberration can be exploited, especially through non-axial pupils that are characteristic of cephalopods, to obtain spectral information. This mechanism is consistent with the extensive suite of visual/behavioral and physiological data that have been obtained from cephalopod studies, and resolves the apparent paradox of vivid chromatic behaviors in \"color-blind\" animals. Moreover, this proposed mechanism has potential applicability in any organisms with limited photoreceptor complements, such as spiders and dolphins.

Biophysics↗

bioRxiv2015

Acute and chronic gregarisation are associated with distinct DNA methylation fingerprints in desert locusts

Desert locusts (Schistocerca gregaria) show a dramatic form of socially induced phenotypic plasticity known as phase polyphenism. In the absence of conspecifics, locusts occur in a shy and cryptic solitarious phase. Crowding with conspecifics drives a behavioural transformation towards gregariousness that occurs within hours and is followed by changes in physiology, colouration and morphology, resulting in the full gregarious phase syndrome. We analysed methylation-sensitive amplified fragment length polymorphisms (MS-AFLP) to compare the effect of acute and chronic crowding on DNA methylation in the central nervous system. We find that crowd-reared and solitary-reared locusts show markedly different neural MS-AFLP fingerprints. However, crowding for a day resulted in neural MS-AFLP fingerprints that were clearly distinct from both crowd-reared and uncrowded solitary-reared locusts. Our results indicate that changes in DNA methylation associated with behavioural gregarisation proceed through intermediate states that are not simply partial realisations of the endpoint states.

Zoology↗

bioRxiv2015

Size Structures Sensory Hierarchy in Ocean Life

Survival in aquatic environments requires organisms to have effective means of collecting information from their surroundings through various sensing strategies. In this study, we explore how sensing mode and range depend on body size. We find a hierarchy of sensing modes determined by body size. With increasing body size, a larger battery of modes becomes available (chemosensing, mechanosensing, vision, hearing, and echolocation, in that order) while the sensing range also increases. This size-dependent hierarchy and the transitions between primary sensory modes are explained on the grounds of limiting factors set by physiology and the physical laws governing signal generation, transmission and reception. We theoretically predict the body size limits for various sensory modes, which align well with size ranges found in literature. The treatise of all ocean life, from unicellular organisms to whales, demonstrates how body size determines available sensing modes, and thereby acts as a major structuring factor of aquatic life.

Ecology↗