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Allada, R.

Publications and source records attributed to Allada, R..

11 recordsLinked to original sources

Brain Transcriptomics Across Diverse Sleep-Wake Manipulations Reveals Multiple Homeostatic Pathways in Drosophila

Sleep is governed by two processes: a circadian process that times sleep and wake and a homeostatic process that drives sleep as a function of prior wake history. Discovered in the fruit fly Drosophila, the period (per) gene is a "universal" cornerstone of the circadian clock, robustly oscillating at the transcript level, in all organs and tissues and in essentially all animals. We hypothesized that there may be a comparable factor (we term "sleeper") for sleep homeostasis. To identify sleeper genes, we performed a wide-ranging transcriptomic analysis to identify genes whose expression tracks sleep-wake history in the Drosophila brain. We analyzed a variety of methods to manipulate sleep-wake and subsequent rebound including mechanical, thermogenetic, optogenetic, pharmacological and baseline sleep across 7 datasets. Using a log2 fold change threshold of 1, we did not identify any gene that was sleep-wake dependent across all datasets, raising the possibility that genes identified with a single method of sleep manipulation are related to the nature of the manipulation and not necessarily to sleep. Nonetheless, we did identify genes whose expression changed with sleep-wake in a consistent direction across at least 2 datasets. These analyses highlight previous processes implicated in sleep homeostasis such as mitochondrial oxidative phosphorylation as well as provide potentially novel pathways such as ribosome biogenesis. In addition, we also examined genes whose expression correlates with prior sleep-wake history and/or predicted subsequent sleep rebound across these datasets. Among significantly correlated genes we observed some that were correlated with recent (<3h) sleep history while others were correlated with much longer (>6h) time frames suggesting temporally distinct pathways for integrating waking experience. This analysis also highlights specific GO pathways for sleep/wake/rebound. Applying a novel GPT based paper search algorithm, we call fl.ai, we identified several sleep-wake regulated genes with demonstrated function in sleep regulation consistent with an in vivo homeostatic function. These include those involved in immunity, neuropeptide signaling, glucose transport, and neuronal excitability. Collectively, these studies suggest that sleep homeostasis is a much more molecularly distributed process than the core circadian clock.

neuroscience↗

Binding profiles for 954 Drosophila and C. elegans transcription factors revealtissue specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource, which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.

genomics↗

Temperature-driven coordination of circadian transcriptome regulation

The circadian rhythm is an evolutionarily-conserved molecular oscillator that enables species to anticipate rhythmic changes in their environment. At a molecular level, the core clock genes induce a circadian oscillation in thousands of genes in a tissue-specific manner, orchestrating myriad biological processes. While studies have investigated how the core clock circuit responds to environmental perturbations such as temperature, the downstream effects of such perturbations on circadian regulation remain poorly understood. By analyzing bulk-RNA sequencing of Drosophila fat bodies harvested from flies subjected to different environmental conditions, we demonstrate a highly condition-specific circadian transcriptome. Further employing a reference-based gene regulatory network (Reactome), we find evidence of increased gene-gene coordination at low tem-peratures and synchronization of rhythmic genes that are network neighbors. Our results point to the mechanisms by which the circadian clock mediates the flys response to seasonal changes in temperature. Significance StatementThe circadian rhythm enables organisms to anticipate and adapt to changes in their environment. While behavioral changes have been observed in Drosophila melanogaster subjected to low temperatures, little is known regarding how these changes are enacted at a molecular level. By conducting bulk RNA sequencing from fruit flies, we observe that genome-wide circadian oscillation patterns are temperature dependent. Intriguingly, we find that morning and evening peaks of transcriptomic activity shift closer together, consistent with anticipation of a shorter photoperiod in cooler winter weather. We further find that the low-temperature dynamics are highly coordinated with respect to a reference-based gene regulatory network. Our findings provide insights into the mechanisms by which flies adapt to environmental temperature changes.

bioinformatics↗

Dietary Restriction Impacts Peripheral Circadian Clock Output Important for Longevity in Drosophila

Circadian clocks may mediate lifespan extension by caloric or dietary restriction (DR). We find that the core clock transcription factor Clock is crucial for a robust longevity and fecundity response to DR in Drosophila. To identify clock-controlled mediators, we performed RNA-sequencing from abdominal fat bodies across the 24 h day after just 5 days under control or DR diets. In contrast to more chronic DR regimens, we did not detect significant changes in the rhythmic expression of core clock genes. Yet we discovered that DR induced de novo rhythmicity or increased expression of rhythmic clock output genes. Network analysis revealed that DR increased network connectivity in one module comprised of genes encoding proteasome subunits. Adult, fat body specific RNAi knockdown demonstrated that proteasome subunits contribute to DR-mediated lifespan extension. Thus, clock control of output links DR-mediated changes in rhythmic transcription to lifespan extension.

genetics↗

PRL1 and CK2 collaborate to time morning and evening phase in short photoperiods

The TIMELESS (TIM) phosphatase, Phosphatase of Regenerating Liver-1 (PRL-1), is required for setting behavioral phase especially under short photoperiod conditions. Yet the circadian clock neurons and underlying mechanisms important for these effects are unknown. Here we demonstrate that PRL-1 function in PDF neurons is necessary and sufficient for timing morning and evening phase under short photoperiod (6:18) conditions. In standard (12:12) photoperiod, we find that PRL-1 rescue or blocking PRL-1 knockdown in PDF neurons restores wild-type morning phase. Expression of the TIM kinase shaggy (sgg) in PDF neurons suppresses in an additive manner PRL-1 period lengthening and delayed morning phase further underscoring the role of PDF neurons. In contrast to knockdown in all clock neurons, knockdown of PRL-1 selectively in PDF clock neurons does not alter the timing of morning or evening phase under standard photoperiod conditions, suggesting PRL-1 function in non-PDF neurons may also be important. In contrast to SGG effects, we find that phase delay of evening onset due to expression of a dominant negative version of the TIM kinase CK2 (CK2alphaTik) requires PRL-1. Given that TIM is a substrate of both the PRL-1 phosphatase and CK2 kinase, we hypothesize that PRL-1 dephosphorylation at specific sites may be necessary for subsequent CK2 phosphorylation to time behavior.

neuroscience↗

period Translation as a Core Mechanism Controlling Temperature Compensation in an Animal Circadian Clock

The most enigmatic of the canonical properties of circadian clocks is temperature compensation where circadian period length is stable across a wide temperature range despite the temperature dependence of most biochemical reactions. While the core mechanisms of circadian clocks have been well described, the molecular mechanisms of temperature compensation are poorly understood especially in animals. A major gap is the lack of temperature compensation mutants that do not themselves unambiguously affect the temperature dependence of the encoded protein. Here we show that null alleles of two genes encoding components of a complex important for translation of the core clock component period in circadian pacemaker neurons robustly alter the temperature dependence of circadian behavioral period length. These changes are accompanied by parallel temperature dependent changes in oscillations of the PER protein and are consistent with the model that these translation factors mediate the temperature-dependence of PER translation. Consistent with findings from modeling studies, we find that translation of the key negative feedback factor PER plays an instrumental role in temperature compensation.

genetics↗

SleepMat: A New Behavioral Analysis Software Program for Sleep and Circadian Rhythms

Drosophila is a premier model for the study of circadian rhythms and sleep, revealing molecular mechanisms that are conserved with vertebrates, including humans. The Drosophila Activity Monitoring (DAM) system has been employed for automated, high throughput analyses, enabling measures of a wide range of measures of circadian and sleep, including period, rhythmicity, anticipation, sleep amount, bout length, and bout number. Yet there are no publicly available programs that capture the full breadth of these measures. Here we develop a new program SleepMat that analyzes a uniquely broader range of circadian and sleep parameters. The program is built on a Matlab platform, employs an easy-to-use graphic user interface, and is highly flexible to customize data inputs. This program will enable a user-friendly high throughput analysis of a broad range of sleep and circadian parameters that can be coupled to the power of Drosophila genetics.

bioinformatics↗

Circadian programming of the ellipsoid body sleep homeostat in Drosophila

Homeostatic and circadian processes collaborate to appropriately time and consolidate sleep and wake. To understand how these processes are integrated, we scheduled brief sleep deprivation at different times of day in Drosophila and find elevated morning rebound compared to evening. These effects depend on discrete morning and evening clock neurons, independent of their roles in circadian locomotor activity. In the R5 ellipsoid body sleep homeostat, we identified elevated morning expression of activity dependent and presynaptic gene expression as well as the presynaptic protein BRUCHPILOT consistent with regulation by clock circuits. These neurons also display elevated calcium levels in response to sleep loss in the morning, but not the evening consistent with the observed time-dependent sleep rebound. These studies reveal the circuit and molecular mechanisms by which discrete circadian clock neurons program a homeostatic sleep center.

neuroscience↗

TimeTrial: An Interactive Application for Optimizing the Design and Analysis of Transcriptomic Times-Series Data in CircadianBiology Research

The circadian rhythm drives the oscillatory expression of thousands of genes across all tissues, coordinating physiological processes. The effect of this rhythm on health has generated increasing interest in discovering genes under circadian control by searching for periodic patterns in transcriptomic time-series experiments. While algorithms for detecting cycling transcripts have advanced, there remains little guidance quantifying the effect of experimental design and analysis choices on cycling detection accuracy. We present TimeTrial, a user-friendly benchmarking framework using both real and synthetic data to investigate cycle detection algorithms performance and improve circadian experimental design. Results show that the optimal choice of analysis method depends on the sampling scheme, noise level, and shape of the waveform of interest; and provides guidance on the impact of sampling frequency and duration on cycling detection accuracy. The TimeTrial software is freely available for download and may also be accessed through a web interface. By supplying a tool to vary and optimize experimental design considerations, TimeTrial will enhance circadian transcriptomics studies.

bioinformatics↗

Glial immune-related pathways as mediators of closed head TBI effects on behavior in Drosophila

In traumatic brain injury (TBI) the initial injury phase is followed by a secondary phase that contributes to neurodegeneration. Yet the mechanisms leading to neuropathology in vivo remain to be elucidated. To address this question, we developed a Drosophila head-specific model for TBI, which we term Drosophila Closed Head Injury (dCHI), where well-controlled, non-penetrating strikes are directly delivered to the head of unanesthetized flies. This assay recapitulates many TBI phenotypes, including increased mortality, impaired motor control, fragmented sleep, and increased neuronal cell death. To discover novel mediators of TBI, we used glial targeted translating ribosome affinity purification in combination with RNA sequencing. We detected significant changes in the transcriptome at various times after TBI including in genes involved in innate immunity within 24 hours after TBI. To test the in vivo functional role of these changes, we examined TBI-dependent behavior and lethality in mutants of the master immune regulator NF-{kappa}B and found that while lethality effects were still evident, changes in sleep and motor function were substantially reduced. These studies validate a new head-specific model for TBI in Drosophila and identify glial immune pathways as candidate in vivo mediators of TBI effects.\n\nTraumatic brain injury (TBI) is one of the leading causes of death and disability in the developed world [1-3]. Yet the underlying mechanisms that lead to long term physical, emotional, and cognitive impairment remain unclear.\n\nUnlike in most forms of trauma, a large percentage of people killed by traumatic brain injuries do not die immediately but rather days or weeks after the insult [4]. TBI consists of a primary and a secondary phase. The primary brain injury is the result of an external mechanical force, resulting in damaged blood vessels, axonal shearing [5], cell death, disruption of the blood- brain barrier, edema, and the release of damage associated molecular patterns (DAMPs) and excitotoxic agents [6]. In response, local glia and infiltrating immune cells upregulate cytokines (tumor necrosis factor ) and interleukins (IL-6 and IL-1{beta}) that drive post-traumatic neuroinflammation [7-10]. This secondary injury develops over a much longer time course, ranging from hours to months after the initial injury and is the result of a complex cascade of metabolic, cellular and molecular processes [11-13]. Neuroinflammation is beneficial when it is promoting clearance of debris and regeneration [14] but can become harmful, mediating neuronal death, progressive neurodegeneration, and neurodegenerative disorders [15-18]. The mechanisms underlying these opposing outcomes are largely unknown, but are thought to depend of the location and timing of the neuroinflammatory response [19, 20]. It remains to be determined what the relative roles of TBI-induced neuroinflammation and other TBI-induced changes are in mediating short and long-term impairments in brain function in vivo.\n\nTo study the mechanisms that mediate TBI pathology in vivo over time, we employ the fruit fly Drosophila melanogaster, a model organism well suited to understanding the in vivo genetics of brain injury. Despite considerable morphological differences between flies and mammals, the fly brain operates on similar principles through a highly conserved repertoire of neuronal signaling proteins, including a large number of neuronal cell adhesion receptors, synapse-organizing proteins, ion channels and neurotransmitter receptors, and synaptic vesicle-trafficking proteins [21]. This homology makes Drosophila a fruitful model to study neurodegenerative disorders [22], including ALS [23], Alzheimers disease [24], Huntingtons disease [25] and Parkinsons disease [26].\n\nTrauma-induced changes in glial gene expression are a highly conserved feature of both mammalian [27, 28] and Drosophila glia [29-32] (reviewed in [33]). In Drosophila, glia are able to perform immune-related functions [32, 34]. Ensheathing glia can act as phagocytes and contribute to the clearance of degenerating axons from the fly brain [29, 31, 35]. The Drosophila innate immune system is highly conserved with that of mammals and consists primarily of the Toll, Immunodeficiency (Imd) and Janus Kinase protein and the Signal Transducer and Activator of Transcription (JAK-STAT) pathways, which together combat fungal and bacterial infections [36, 37]. Dysregulation of cerebral innate immune signaling in Drosophila glial cells can lead to neuronal dysfunction and degeneration [38, 39], suggesting that changes in glia cells could underlie secondary injury mechanisms in our Drosophila model of TBI.\n\nExisting Drosophila TBI models [40, 41] deliver impacts to the entire body, not just the head, and thus, one cannot definitively attribute ensuing phenotypes to TBI. To remove the confound of bodily injury, we have developed a novel, head-specific Drosophila model for TBI, Drosophila Closed Head Injury (dCHI). Here we show that by delivering precisely controlled, non-penetrating strikes to an unanesthetized flys head, we can induce cell death and increased mortality in a dose-dependent manner. In addition, TBI results in impaired motor control and decreased, fragmented sleep. Impaired motor control persists for many days after TBI while the sleep phenotype disappears after three days. These TBI-induced behavioral phenotypes do not occur in mutants lacking the master immune regulator NF-{kappa}B Relish (Rel), even though TBI-induced mortality is greatly induced in these mutants. In wild type flies, TBI results in changes in glial gene expression, where many immune related genes are upregulated 24 hours after injury. Together, these results establish a platform where powerful Drosophila genetics can be utilized to study the complex cascade of secondary injury mechanisms that occur after TBI in order to genetically disentangle its beneficial and detrimental effects.

neuroscience↗

Bootstrapping and Empirical Bayes Methods Improve Rhythm Detection in Sparsely Sampled Data

MotivationThere is much interest in using genome-wide expression time series to identify circadian genes. However, the cost and effort of such measurements often limits data collection. Consequently, it is difficult to assess the experimental uncertainty in the measurements and, in turn, to detect periodic patterns with statistical confidence.\n\nResultsWe show that parametric bootstrapping and empirical Bayes methods for variance shrinkage can improve rhythm detection in genome-wide expression time series. We demonstrate these approaches by building on the empirical JTK_CYCLE method (eJTK) to formulate a method that we term BooteJTK. Our procedure rapidly and accurately detects cycling time series by combining information about measurement uncertainty with information about the rank order of the time series values. We exploit a publicly available genome-wide dataset with high time resolution to show that BooteJTK provides more consistent rhythm detection thanexisting methods at typical sampling frequencies. Then, we apply BooteJTK to genome-wide expression time series from multiple tissues and show that it reveals biologically sensible tissue relationships that eJTK misses.\n\nAvailabilityBootstrap eJTK (BooteJTK) is implemented in Python and is freely available on GitHub at https://github.com/alanlhutchison/BooteJTK.

bioinformatics↗