Miracle-dz/UniFAR-FTUs huggingface dataset:
powerEQTL: an R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis

Summary Genome-wide association studies (GWAS) have revealed thousands of genetic loci for common diseases. One of the main challenges in the post-GWAS era is to understand the causality of the genetic variants. Expression quantitative trait locus (eQTL) analysis has been proven to be an effective way to address this question by examining the relationship between gene expression and genetic variation in a sufficiently powered cohort. However, it is often tricky to determine the sample size at which a variant with a specific allele frequency will be detected to associate with gene expression with sufficient power. This is particularly demanding with single-cell RNAseq studies. Therefore, a user-friendly tool to perform power analysis for eQTL at both bulk tissue and single-cell level will be critical. Here, we presented an R package called powerEQTL with flexible functions to calculate power, minimal sample size, or detectable minor allele frequency in both bulk tissue and single-cell eQTL analysis. A user-friendly, program-free web application is also provided, allowing customers to calculate and visualize the parameters interactively. Availability and implementation The powerEQTL R package source code and online tutorial are freely available at CRAN: https://cran.r-project.org/web/packages/powerEQTL/. The R shiny application is publicly hosted at https://bwhbioinfo.shinyapps. io/powerEQTL/. Contact Xianjun Dong (xdong@rics.bwh.harvard.edu), Weiliang Qiu (weiliang.qiu@sanofi.com) Supplementary information Supplementary data are available at Bioinformatics online.
The p-coumaroyl arabinoxylan transferase HvAT10 underlies natural variation in whole-grain cell wall phenolic acids in cultivated barley

Phenolic acids in cereal grains have important health-promoting properties and influence digestibility for industrial or agricultural uses. Here we identify alleles of a single BAHD p-coumaroyl arabinoxylan transferase gene, HvAT10, as responsible for the natural variation in cell wall-esterified p-coumaric and ferulic acid in whole grain of a collection of cultivated two-row spring barley genotypes. We show that HvAT10 is rendered non-functional by a premature stop codon mutation in approximately half of the genotypes in our mapping panel. The causal mutation is virtually absent in wild and landrace germplasm suggesting an important function for grain arabinoxylan p-coumaroylation pre-domestication that is dispensable in modern agriculture. Intriguingly, we detected detrimental impacts of the mutated locus on barley grain quality traits. We propose that HvAT10 could be a focus for future grain quality improvement or for manipulating phenolic acid content of wholegrain food products.
Disentangling the aging network of a termite queen

Background Most insects are relatively short-lived, with a maximum lifespan of a few weeks, like the aging model organism, the fruit-fly Drosophila melanogaster. By contrast, the queens of social insects (termites, ants, some bees and wasps) can live for more than a decade. This makes social insects promising new models in aging research providing insights into how a long reproductive life can be achieved. Yet, aging studies on social insect reproductives are hampered by a lack of quantitative data on age-dependent survival and time series analyses that cover the whole lifespan of such long-lived individuals. We studied aging in queens of the drywood termite Cryptotermes secundus by determining survival probabilities over more than 15 years and performed transcriptome analyses for queens of known age that covered their whole lifespan. Results The maximum lifespan of C. secundus queens was 13 years with a median maximum longevity of 11.0 years. Time course and co-expression network analyses of gene expression patterns over time indicated a non-gradual aging pattern. It was characterized by networks of genes that became differentially expressed only late in life, namely after an age of 10 years, which associates well with the median maximum lifespan for queens. These old-age gene networks reflect processes of physiological upheaval. We detected strong signs of stress, decline, defence and repair at the transcriptional level of epigenetic control as well as at the post-transcriptional level with changes in transposable element activity and the proteostasis network. The latter depicts an upregulation of protein degradation, together with protein synthesis and protein folding, processes which are often down-regulated in old animals. The simultaneous upregulation of protein synthesis and autophagy is indicative for a stress-response mediated by the transcription factor cnc, a homolog of human nrf genes. Conclusion Our results show non-linear senescence with a rather sudden physiological upheaval at old-age. Most importantly, they point to a re-wiring in the proteostatis network as central for explaining the long life of social insect queens.
Adenovirus E1A Binding to DCAF10 Targets Degradation of AAA+ ATPases Required for Quaternary Assembly of Multiprotein Machines and Innate Immunity

Adenovirus E1A early proteins modify host cell physiology to optimize virus replication. The N-terminal half of small e1a interacts with RB-family proteins to de-repress dNTP and DNA synthesis, and with p300/CBP to inhibit host anti-viral innate immune responses. These e1a N-terminal interactions activate a strong, late host anti-viral response due to stabilization and activation of interferon response factor 3 (IRF3). However, the C-terminal half of e1a inhibits this through interactions with three host proteins with seemingly unrelated functions. Proteomic analysis showed that all three C-terminal interactions are required for e1a-association into an ∼1 MDa multi-protein complex with scaffold subunits of a CRL4 E3 ubiquitin ligase and DCAF10, a presumed specificity subunit. This e1a-DCAF10-CRL4 prevents IRF3 stabilization indirectly by directing degradation of the essential AAA+ ATPases RUVBL1/2, subunits of several HSP90 co-chaperones required for quaternary assembly of cellular protein machines required for anti-viral defenses and responses to genotoxic and metabolic stress.
rTPC and nls.multstart: a new pipeline to fit thermal performance curves in R

The quantification of thermal performance curves (TPCs) for biological rates has many applications to problems such as predicting species’ responses to climate change. There is currently no widely used open-source pipeline to fit mathematical TPC models to data, which limits the transparency and reproducibility of the curve fitting process underlying applications of TPCs. We present a new pipeline in R that currently allows for reproducible fitting of 24 different TPC models using non-linear least squares (NLLS) regression. The pipeline consists of two packages – rTPC and nls. multstart – that allow multiple start values for NLLS fitting and provides helper functions for setting start parameters. This pipeline overcomes previous problems that have made NLLS fitting and estimation of key parameters difficult or unreliable. We demonstrate how rTPC and nls.multstart can be combined with other packages in R to robustly and reproducibly fit multiple models to multiple TPC datasets at once. In addition, we show how model selection or averaging, weighted model fitting, and bootstrapping can easily be implemented within the pipeline. This new pipeline provides a flexible and reproducible approach that makes the challenging task of fitting multiple TPC models to data accessible to a wide range of users.
The role of ecosystem engineers in shaping the diversity and function of arid soil bacterial communities

Ecosystem engineers (EEs) are present in every environment and are known to strongly influence ecological processes and thus shape the distribution of species and resources. In this study, we assessed the direct and indirect effect of two EEs (perennial shrubs and ant nests), individually and combined, on the composition and function of arid soil bacterial communities. To that end, top soil samples were collected in the Negev Desert Highlands during the dry season from four patch types: (1) barren soil; (2) under shrubs; (3) near ant nests; or (4) near ant nests situated under shrubs. The bacterial composition was evaluated in the soil samples (fourteen replicates per patch type) using 16S rRNA gene amplicon sequencing, together with physico-chemical measures of the soil, and the potential functions of the community. We have found that the EEs differently affected the community composition. Indeed, barren patches supported a soil microbiome, dominated by Rubrobacter and Proteobacteria, while in EE patches the Deinococcus-Thermus phylum was dominating. The presence of the EEs similarly enhanced the abundance of phototrophic, nitrogen cycle and stress- related genes. In addition, only when both EEs were combined, were the soil characteristics altered. Our results imply that arid landscapes foster unique communities selected by each EE(s), solo or in combination, yet these communities have similar potential biological traits to persist under the harsh arid conditions. Environments with multiple EEs are complicated to study due to the possibility of non-additive effects of EEs and thus further research should be done. IMPORTANCE Ecosystem engineers are organisms that can create, modify, or maintain their habitat. They are present in various environments but are particularly conspicuous in desert ecosystems, where their presence is tightly linked to vital resources like water or nutrients. Despite their key role in structuring and controlling desert ecosystems, joint engineering, and their effect on soil function, are unknown. Our study explores the contributions of key ecosystem engineers to the diversity and function of their soil microbiome allowing better understanding of their role in shaping habitats and engineering their activity
Artificial light at night shifts the circadian system but still leads to physiological disruption in a wild bird

Globally increasing levels of artificial light at night (ALAN) have been associated with shifts in behavioral rhythms of many wild organisms. It is however unknown to what extent this change in behavior is due to shifts in the circadian clock, and, importantly, whether the physiological pathways orchestrated by the circadian clock are desynchronized by ALAN. Such circadian disruption could have severe consequences for wildlife health, as shown for humans. Here, we analyze the effects of experimental ALAN on rhythmic behavior, gene expression and metabolomic profiles in a wild songbird, the great tit (Parus major). We exposed 34 captive males to three ALAN intensities or to dark nights and recorded their activity rhythms. After three weeks, we collected mid-day and midnight samples of hypothalamus, hippocampus, liver, spleen and plasma. ALAN advanced wake-up time, and this shift was paralleled by an advance in hypothalamic expression of the clock gene BMAL1, which is key to integrating physiological pathways. BMAL1 advances were remarkably consistent across tissues, suggesting close links of brain and peripheral clock gene expression with activity rhythms. However, only a minority of other candidate genes (4 out of 12) paralleled the shifted BMAL1 expression. Moreover, metabolomic profiling showed that only 9.7% of the 755 analyzed metabolites followed the circadian shift. Thus, despite the shifted timing of key clock functions under ALAN, birds suffered internal desynchronization. We thus suggest circadian disruption to be a key link between ALAN and health impacts, in birds and humans alike. Significance Statement Shifts in daily activity are a common consequence of artificial light at night (ALAN). In humans, shifted activity cycles often become desynchronized from internal physiological rhythms, with serious health implications. To what extent a similar desynchronization occurs in wild animals experiencing ALAN is currently unknown. We exposed captive great tits to increasing levels of LAN, and found that activity patterns and a core clock gene, BMAL1, shifted in concert. However, only a minority of additional candidate genes and less than 10% of the metabolites followed this circadian shift, suggesting internal desynchronization of physiological rhythms. Our study emphasizes the massive potential for ALAN to impact the health of wild animals through circadian disruption.
Continental-scale genomic analysis suggests shared post-admixture adaptation in the Americas

American populations are one of the most interesting examples of recently admixed groups, where ancestral components from three major continental human groups (Africans, Eurasians and Native Americans) have admixed within the last 15 generations. Recently, several genetic surveys focusing on thousands of individuals shed light on the geography, chronology and relevance of these events. However, despite the fact that gene-flow could drive adaptive evolution, it is not clear whether and how natural selection acted on the resulting genetic variation in the Americas. In this study, we analysed the patterns of local ancestry of genomic fragments in genome-wide data for ∼6,000 admixed individuals from ten American countries. In doing so, we identified regions characterized by a Divergent Ancestry Profile (DAP), in which a significant over or under ancestral representation is evident. Our results highlighted a series of genomic regions with Divergent Ancestry Profiles (DAP) associated with immune system response and relevant medical traits, with the longest DAP region encompassing the Human Leukocyte Antigen locus. Furthermore, we found that DAP regions are enriched in genes linked to cancer-related traits and autoimmune diseases. Then, analyzing the biological impact of these regions, we showed that natural selection could have acted preferentially towards variants located in coding and non-coding transcripts, and characterized by a high deleteriousness score. Taken together, our analyses suggest that shared patterns of post admixture adaptation occurred at continental scale in the Americas, affecting more often functional and impactful genomic variants.
Using physiological signals to predict temporal defense responses: a multi-modality analysis

Defense responses are a highly conserved behavioral response set across species. Defense responses motivate organisms to detect and react to threats and potential danger as a precursor to anxiety. Accurate measurement of temporal defense responses is important for understanding clinical anxiety and mood disorders, such as post-traumatic stress disorder, obsessive compulsive disorder, and generalized anxiety disorder. Within these conditions, anxiety is defined as a state of prolonged defense response elicitation to a threat that is ambiguous or unspecific. In this study, we aimed to develop a data-driven approach to capture temporal defense response elicitation through a multi-modality data analysis of physiological signals, including electroencephalogram (EEG), electrocardiogram (ECG), and eye-tracking information. A fear conditioning paradigm was adopted to develop a defense response classification model. From a classification model based on 42 feature sets, a higher order crossing feature set-based model was chosen for further analysis with cross-validation loss of 0.0462 (SEM: 0.0077). To validate our model, we compared predicted defense response occurrence ratios from a comprehensive situation that generates defense responses by watching movie clips with fear awareness and threat existence predictability, which have been reported to correlate with defense response elicitation in previous studies. We observed that defense response occurrence ratios are correlated with threat existence predictability, but not with fear awareness. These results are similar to those of previous studies using comprehensive situations. Our study provides insight into measurement of temporal defense responses via a novel approach, which can improve understanding of anxiety and related clinical disorders for neurobiological and clinical researchers.
Institutionalizing an Evidence-Based Practice in a Selected Government Agency in Nigeria

The need to tackle the discrepancy between research outputs and the execution of the findings into real practice is a crucial factor in establishing evidence-based practice in a selected government agency. There is a need to increase the number of experts in our education sector who can synthesise, translate, and package the evidence for ready use by decision-makers and to foster entrepreneurship in Africa. To achieve this, the activities of a 28-man Evidence Leaders in Africa (ELA) team were recruited to drive the project through capacity building training and workshop sessions. Thereafter, a non-random purposive sampling technique targeted at policy makers at various government and non-governmental organizations was adopted as the study design. In all, purposive administration of 424 copies of questionnaire to individuals in different governmental and non-governmental organizations was done by the recruited personnel. The retrieved data from the questionnaire were analyzed using standard statistical method. Socio-demographic characteristics of respondents reveal 34% representation of (31-40 years) age bracket, with (57%) of them working in the University spanning over 2 to 5years (47%) work experience. Approximately 64% of the respondents are not aware of EIDM while 71% had no understanding of EIDM. As regards knowledge of EIDM, 36% had no knowledge of EIDM, 29% had moderate knowledge, 34% were beginners while approximately 1% had advanced knowledge of EIDM. Also, approximately 99% of the respondents have neither been trained nor involved in training others in EIDM. It was also observed that 8.5% of the respondents were policy-makers in the organization, yet 90.7% of the respondents agree that EIDM is useful in policy-making while 81.3% of the respondents engage their colleagues in EIDM. From this study, it is safe to infer that institutionalizing EIDM in NNMDA has numerous benefits as shown by the findings of this study. This will only be possible when all parties involved in producing and using research evidence are well informed and knowledgeable in EIDM.
Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics

Neuronal firing and neuron-to-neuron synaptic wiring are currently widely described as orchestrated by astrocytes — elaborately ramified glial cells tiling the cortical and hippocampal space into non-overlapping domains, each covering hundreds of individual dendrites and hundreds thousands synapses. A key component to astrocytic signaling is the dynamics of cytosolic Ca2+ which displays multiscale spatiotemporal patterns from short confined elemental Ca2+ events (puffs) to Ca2+ waves expanding through many cells. Here we synthesize the current understanding of astrocyte morphology, coupling local synaptic activity to astrocytic Ca2+ in perisynaptic astrocytic processes and morphology-defined mechanisms of Ca2+ regulation in a distributed model. To this end, we build simplified realistic data-driven spatial network templates and compile model equations as defined by local cell morphology. The input to the model is spatially uncorrelated stochastic synaptic activity. The proposed modeling approach is validated by statistics of simulated Ca2+ transients at a single cell level. In multicellular templates we observe regular sequences of cell entrainment in Ca2+ waves, as a result of interplay between stochastic input and morphology variability between individual astrocytes. Our approach adds spatial dimension to the existing astrocyte models by employment of realistic morphology while retaining enough flexibility and scalability to be embedded in multiscale heterocellular models of neural tissue. We conclude that the proposed approach provides a useful description of neuron-driven Ca2+-activity in the astrocyte syncytium.
Zfp36l1 and Zfp36l2 balances proliferation and differentiation in the developing retina

Both transcriptional and post-transcriptional regulation of gene expression play significant roles in diverse biological processes, but little is known about how post-transcriptional regulation impacts retinal development. Here we report our study of the function of two members of the TTP (tristetraprolin) mRNA binding protein family, Zfp36l1 and Zfp36l2, in the developing retina. TTP proteins are highly conserved CCCH zinc finger proteins, which carry out their functions by promoting target mRNA decay and modulating translation. We found that Zfp36l1 and Zfp36l2 were expressed in retinal progenitor cells (RPCs) during development and Müller glial cells and photoreceptors in the mature retina. Our analysis of the mutant retinas showed that, whereas the single knockout retinas were largely normal, the double knockout (DKO) retina showed decreased RPC proliferation and increased differentiation of multiple retinal cell types. RNA-seq analysis confirmed the imbalance of proliferation and differentiation in the DKO retina. Gene ontology and in silico target gene analysis indicates that Zfp36l1 and Zfp36l2 exert their function by directly regulating multiple classes of proteins, including components of multiple signaling pathways such as the sonic hedgehog pathway and the Notch pathway, cell cycle regulators, and most interestingly transcription factors directly involved in retinal differentiation. These results reveal a new tier of gene regulation controlling retinal development.
TranSuite: a software suite for accurate translation and characterization of transcripts

Protein translation programs often select the longest open reading frame (ORF) in a transcript leading to numerous inaccurate and mis-annotated ORFs in databases. Unproductive transcript isoforms containing premature termination codons (PTCs) are potential substrates for nonsense-mediated decay (NMD). These transcripts often contain truncated ORFs but are incorrectly annotated due to selection of a long ORF beginning at an AUG downstream of the PTC despite the transcript containing the authentic translation start AUG. In gene expression and alternative splicing analyses, it is important to identify transcript isoforms which code for different protein variants and to distinguish these from potential NMD substrates. Here, we present TranSuite, a pipeline of bioinformatics tools that address these challenges by performing accurate translations, characterizing alternative ORFs and identifying NMD and other features of transcripts in newly assembled and existing transcriptomes. Directly comparing ORFs defined by TranSuite and TransDecoder for the Arabidopsis transcriptome AtRTD2 identified ORF mis-calling in over 16k (27%) of transcripts by TransDecoder.