bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification
Authors: Cao Shanni , He Chao , Zhao Xue , Yu Ranran , Li Yuqi , Fang Wen , Zhang Chen-Yu , Yan Wenhao , Chen Dijun 
Published: October 2022

AbstractPlant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors (TFs) in intricate regulatory networks at a cell-type specific manner. Here we presented a reference single-cell transcriptomic atlas ofArabidopsisseedlings by integration of 40 published scRNA-seq datasets from representative tissues as well as the entire under- and above-ground parts. We identified 34 distinct cell types or states, largely expanding our current view of plant cell compositions. We then mapped the developmental trajectory of root-shoot lineage separation and identified differential gene expression programs that may regulate the cell fate determination of under- and above-ground organs. Lastly, we systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordination manner to control cell-type specific gene expression. Taken together, our study not only offers a valuable resource plant cell atlas exploration but also provides molecular insights into gene-regulatory programs that determines organ specify, particularly the differentiation between root and shoot.
Transcriptome analyses using regulon, functional category, and operon information with GINtool
Authors: Wang Biwen , van der Kloet Frans , Kes Mariah B.M.J. , Luirink Joen , Hamoen Leendert W. 
Published: October 2022

ABSTRACTWhen analysing transcriptome data, threshold values are chosen to decide whether the regulation of a gene is relevant or not, however this may result in the loss of valuable information. To overcome this problem it can be useful to analyse regulons instead of individual genes, to harness the statistical power of combining genes. Another advantage of a regulon-based analysis is that it provides direct insights into the activity of regulatory pathways, which is the essence of transcriptome analyses. We have developed a software tool called GINtool that can use regulon information to analyse transcriptome data. GINtool includes the option to take the activity mode of a regulator in account, which is important when a regulator can function both as an activator and repressor. GINtool also contains two novel graphical representations that greatly facilitate the visual inspection of regulon-based transcriptome analyses. Additional features of GINtool includes the evaluation of transcriptome data using functional categories, and the analysis of gene expression differences within operons. To ease the analyses and downstream processing of figures, GINtool has been developed as an add-in for Excel.
Cytoplasmic mRNA levels are regulated by a combination of chromatin retention and RNA stability
Authors: Henfrey Callum , Murphy Shona , Tellier Michael 
Published: October 2022

ABSTRACTTranscription and co-transcriptional processes, including pre-mRNA splicing and mRNA cleavage and polyadenylation, regulate the production of mature mRNAs. The carboxyl terminal domain (CTD) of RNA polymerase (pol) II, which comprises 52 repeats of the Tyr1Ser2Pro3Thr4Ser5Pro6Ser7 peptide, is involved in the coordination of transcription with co-transcriptional processes. The pol II CTD is dynamically modified by protein phosphorylation, which regulates recruitment of transcription and co-transcriptional factors. We have investigated whether cytoplasmic levels of mature mRNA from intron-containing protein-coding genes are related to pol II CTD phosphorylation, RNA stability, and pre-mRNA splicing and mRNA cleavage and polyadenylation efficiency. We find that genes that produce a low level of mature mRNA are associated with relatively high phosphorylation of the pol II CTD Tyr1 and Thr4 residues, poor RNA processing, increased chromatin retention, and shorter RNA half-life. While these poorly-processed transcripts are degraded by the nuclear RNA exosome, our results indicate that in addition to RNA half-life, chromatin retention due to a low RNA processing efficiency also plays an important role in the regulation of cytoplasmic mRNA levels.
A Robust, Compact and Diverse Population Code for Competing Sounds in Auditory Cortex
Authors: Nocon Jian Carlo , Witter Jake , Houghton Conor , Gritton Howard , Han Xue , Sen Kamal 
Published: October 2022

AbstractCortical circuits encoding sensory information consist of populations of neurons, yet how information aggregates via pooling individual cells remains poorly understood. Such pooling may be particularly important in noisy settings where single neuron encoding is degraded. One example is the cocktail party problem, with competing sounds from multiple spatial locations. How populations of neurons in auditory cortex (ACx) code competing sounds have not been previously investigated. Here, we apply a novel information theoretic approach to estimate information in populations of neurons in ACx about competing sounds from multiple spatial locations, including both summed population (SP) and labeled line (LL) codes. We find that a small subset of neurons is sufficient to nearly maximize mutual information over different spatial configurations, with the LL code outperforming the SP code, and approaching information levels attained without noise. Moreover, with a LL code, units with diverse spatial responses, including both regular and narrow-spiking units, constitute the best pool. Finally, information in the population increases with spatial separation between target and masker, in correspondence with behavioral results on spatial release from masking in human and animals. Taken together, our results reveal that a compact and diverse population of neurons in ACx provide a robust code for competing sounds from different spatial locations.
Cell Painting transfer increases screening hit rate
Authors: Cohen Ethan , Corbe Maxime , Franco Cláudio A. , Vasconcelos Francisca F. , Perez Franck , Nery Elaine Del , Bollot Guillaume , Genovesio Auguste 
Published: October 2022

AbstractDrug discovery uses high throughput screening to identify compounds that interact with a molecular target or that alter a phenotype favorably. The cautious selection of molecules used for such a screening is instrumental, and is tightly related to the hit rate. In this work, we wondered if Cell Painting, a general purpose image-based assay, could be used as an efficient proxy for compound selection, thus increasing the success rate of a specific assay. To this end, we considered Cell Painting images with 30,000 molecules treatments, and selected compounds that produced a visual effect close to the positive control of an assay, by using the Frechet Inception Distance. We then compared the hit rates of such a preselection with what was actually obtained in real screening campaigns. As a result, Cell Painting would have permitted a significant increase in the success rate and, even for one of the assays, would have allowed to reach 80% of the hits with ten times fewer compounds to test. We conclude that images of a Cell Painting assay can be directly used for compound selection prior to screening, and we provide a simple quantitative approach in order to do so.
Spatially resolved human kidney multi-omics single cell atlas highlights the key role of the fibrotic microenvironment in kidney disease progression
Authors: Abedini Amin , Levinsohn Jonathan , Klötzer Konstantin A , Dumoulin Bernhard , Ma Ziyuan , Frederick Julia , Dhillon Poonam , Balzer Michael S , Shrestha Rojesh , Liu Hongbo , Vitale Steven , Devalaraja-Narashimha Kishor , Grandi Paola , Bhattacharyya Tanmoy , Hu Erding , Pullen Steven S. , Boustany-Kari Carine M , Guarnieri Paolo , Karihaloo Anil , Traum Daniel , Yan Hanying , Coleman Kyle , Palmer Matthew , Sarov-Blat Lea , Morton Lori , Hunter Christopher A. , Kaestner Klaus H , Li Mingyao , Susztak Katalin 
Published: October 2022

AbstractKidneys possess one of the most intricate three-dimensional cellular structures in the body, yet the spatial and molecular principles of kidney health and disease remain inadequately understood. Here, we have generated high-quality datasets for 81 samples, including single cell (sc), single nuclear (sn), spot level (Visium) and single cell resolution (CosMx) spatial (sp)-RNA expression, and sn open chromatin, capturing cells from healthy, diabetic, and hypertensive diseased human kidneys. By combining the snRNA, snATAC and scRNA sequencing we identify cell types and map these cell types to their locations within the tissue. Unbiased deconvolution of the spatial data identifies 4 distinct spatial microenvironments: glomerular, immune, tubule and fibrotic. We describe the complex, heterogenous cellular and spatial organization of human microenvironments in health and disease. Further, we find that the fibrotic microenvironment spatial gene signature is not only able to molecularly classify human kidneys, but it also offers an improved prognosis prediction compared to traditional histopathological analysis. We provide a comprehensive spatially resolved molecular roadmap of the human kidney and the fibrotic process, demonstrating the clinical utility of spatial transcriptomics.
LARP4 Is an RNA-Binding Protein That Binds Nuclear-Encoded Mitochondrial mRNAs To Promote Mitochondrial Function
Authors: Lewis Benjamin M , Cho Chae Yun , Her Hsuan-Lin , Hunter Tony , Yeo Gene W 
Published: October 2022

AbstractMitochondrial associated RNA-binding proteins (RBPs) have emerged as key contributors to mitochondrial biogenesis and homeostasis. With few examples described, we set out to identify RBPs that regulate nuclear-encoded mitochondrial mRNAs (NEMmRNAs). Our systematic analysis of RNA-targets of 150 RBPs identified RBPs with a preference for binding NEMmRNAs, including LARP4, a La RBP family member. We show that LARP4’s targets are particularly enriched in mRNAs that encode respiratory chain complex proteins (RCCPs) and mitochondrial ribosome proteins (MRPs) across multiple human cell lines. Quantitative proteomics of cells lacking LARP4 show that protein levels of RCCPs and MRPs are significantly reduced. Furthermore, we show that LARP4 depletion reduces mitochondrial function, and that this phenotype is rescued by LARP4 re-expression. Our findings shed light onto a novel function for LARP4 as an RBP that binds to NEMmRNAs to promote mitochondrial respiratory function.HighlightsAnalysis of CLIP data reveals RBPs with a preference for mitochondrial mRNA targetsLARP4’s RNA-target set is enriched for OXPHOS and mitochondrial ribosomal proteinsLoss of LARP4 reduces protein levels of these two groups of mitochondrial proteinsLARP4 is required for normal proliferation, translation, and OXPHOS function
Immunogenicity of the BA.5 Bivalent mRNA Vaccine Boosters
Authors: Collier Ai-ris Y. , Miller Jessica , Hachmann Nicole P. , McMahan Katherine , Liu Jinyan , Bondzie Esther Apraku , Gallup Lydia , Rowe Marjorie , Schonberg Eleanor , Thai Siline , Barrett Julia , Borducchi Erica N. , Bouffard Emily , Jacob-Dolan Catherine , Mazurek Camille R. , Mutoni Audrey , Powers Olivia , Sciacca Michaela , Surve Nehalee , VanWyk Haley , Wu Cindy , Barouch Dan H. 
Published: October 2022

ABSTRACTWaning immunity following mRNA vaccination and the emergence of SARS-CoV-2 variants has led to reduced mRNA vaccine efficacy against both symptomatic infection and severe disease. Bivalent mRNA boosters expressing the Omicron BA.5 and ancestral WA1/2020 Spike proteins have been developed and approved, because BA.5 is currently the dominant SARS-CoV-2 variant and substantially evades neutralizing antibodies (NAbs). Our data show that BA.5 NAb titers were comparable following monovalent and bivalent mRNA boosters.
Impact of postnatal depression on neonatal outcomes: an exploratory study in Kisumu County, western Kenya
Authors: Gribbin Catherine , Achieng Florence , K’Oloo Alloys , Barsosio Hellen C. , Kwobah Edith , Kariuki Simon , Nabwera Helen M 
Published: October 2022

AbstractBackgroundPrevious Kenyan studies suggest postnatal depression (PND) may negatively impact infant growth. However these studies are limited to Nairobi and no research has explored the effects of PND in the neonatal period.AimTo explore the impact of PND on neonatal feeding practices, weight gain, illness episodes and identify key maternal caregiving challenges.MethodsA mixed methods study of mothers and newborns <72 hours post-delivery from postnatal wards and clinics across 5 facilities in Kisumu County. At baseline, the Edinburgh Postnatal Depression Scale (EPDS) identified mothers with depressive features (EPDS ≥12) and infant feeding practices were assessed by questionnaire. 24 mothers were followed up 2 weeks later with a questionnaire and interview to further explore caregiving practices. Quantitative data was analysed using descriptive statistics. A thematic framework was used to identify and analyse emerging themes from the interviews.Results56 (37%) out of 150 mother-infant pairs screened at baseline had an EPDS score ≥12. These mothers practiced exclusive breastfeeding less frequently (76.9% vs 90.9% p = 0.6) and a smaller proportion of their infants gained weight at 2 weeks (23.1% vs 36.4% p = 0.75). Key stressors were financial insecurity and lack of social support. Mothers described the benefits of social support on their mood and caregiving abilities.ConclusionAdverse growth and feeding outcomes are already apparent in the first 2 weeks of life among infants of mothers with features of PND. Early screening and intervention through community support structures could mitigate against the impact of PND on maternal mood and caregiving ability.
Electrophysiological recording of human neuronal networks during suborbital spaceflight
Authors: Padilla Andie E. , Hovell Candice , Mares Jeremy , Reumers Veerle , Joddar Binata 
Published: October 2022

AbstractThe use of microfluidic tissue-on-a-chip devices in conjunction with electrophysiology (EPHYS) techniques has become prominent in recent years to study cell-cell interactions critical to the understanding of cellular function in extreme environments, including spaceflight and microgravity. Current techniques are confined to invasive whole-cell recording at intermittent time points during spaceflight, limiting data acquisition and overall reduced insight on cell behaviour. Currently, there exists no validated technology that offers continuous EPHYS recording and monitoring in physiological systems exposed to microgravity. In collaboration with imec and SpaceTango, we have developed an enclosed, automated research platform that enables continuous monitoring of electrically active human cell cultures during spaceflight. The Neuropixels probe system (imec) will be integrated for the first time within an engineered in-vitro neuronal tissue-on-a-chip model that facilitates the EPHYS recording of cells in response to extracellular electrical activity in the assembled neuronal tissue platform. Our goal is to study the EPHYS recordings and understand how exposure to microgravity affects cellular interaction within human tissue-on-a-chip systems in comparison to systems maintained under Earth’s gravity. Results may be useful for dissecting the complexity of signals obtained from other tissue systems, such as cardiac or gastrointestinal, when exposed to microgravity. This study will yield valuable knowledge regarding physiological changes in human tissue-on-a-chip models due to spaceflight, as well as validate the use of this type of platform for more advanced research critical in potential human endeavours to space.
Ultra-fast joint-genotyping with SparkGOR
Authors: Guðbjartsson Hákon , Þór Ísleifsson Hjalti , Ragnarsson Bergur , Guimaraes Raony , Wu Haiguo , Ólafsdóttir Hildur , Stefánsson Sigmar K. 
Published: October 2022

ABSTRACTMotivationOur aim was to simplify and speedup joint-genotyping, from sequence based variation data of individual samples, while maintaining as high sensitivity and specificity as possible.ResultsWe have leveraged versatile GOR data structures to store biallelic representations of variants and sequence read coverage in a very efficient way, allowing for very fast joint-genotyping that is an order of magnitude faster than any joint-genotyping method published to date. Furthermore, it can be easily extended and executed much faster in an incremental fashion. Concordance analysis based on the Genome In A Bottle (GIAB) samples shows favorable results when compared with the de-facto standard approach, using gVCF files and GATK joint-calling. Additionally, we have developed variant quality classification using XGBoost and variant training sets derived from the GIAB samples. The entire business logic is implemented efficiently and concisely in SparkGOR.AvailabilitySparkGOR is open-source and freely available athttps://github.com/gorpipe.Contacthakon@genuitysci.com
Fast and versatile sequence-independent protein docking for nanomaterials design using RPXDock
Authors: Sheffler William , Yang Erin C. , Dowling Quinton , Hsia Yang , Fries Chelsea N. , Stanislaw Jenna , Langowski Mark , Brandys Marisa , Khmelinskaia Alena , King Neil P. , Baker David 
Published: October 2022

AbstractComputationally designed multi-subunit assemblies have shown considerable promise for a variety of applications, including a new generation of potent vaccines. One of the major routes to such materials is rigid body sequence-independent docking of cyclic oligomers into architectures with point group or lattice symmetries. Current methods for docking and designing such assemblies are tailored to specific classes of symmetry and are difficult to modify for novel applications. Here we describe RPXDock, a fast, flexible, and modular software package for sequence-independent rigid-body protein docking across a wide range of symmetric architectures that is easily customizable for further development. RPXDock uses an efficient hierarchical search and a residue-pair transform (RPX) scoring method to rapidly search through multidimensional docking space. We describe the structure of the software, provide practical guidelines for its use, and describe the available functionalities including a variety of score functions and filtering tools that can be used to guide and refine docking results towards desired configurations.Author SummaryProtein design methodologies are now able to generate, through a stepwise approach, a wide variety of self-assembling protein structures that begin to rival the structural complexity of naturally occurring protein nanomachines. Efficient methods for docking oligomeric protein building blocks in user-defined target symmetries are central to these techniques. We developed RPXDock as a fast and versatile method to systematically dock pre-existing proteins together into a multitude of asymmetrical and symmetrical architectures. RPXdock is also readily extendable to future applications through the addition of new symmetries, score functions, and filtering criteria.
SurvivalML: an integrative platform for the discovery and exploration of prognostic models in multi-center cancer cohorts
Authors: Liu Zaoqu , Xu Hui , Liu Long , Weng Siyuan , Xing Zhe , Ren Yuqing , Ge Xiaoyong , Wang Libo , Guo Chunguang , Chen Shuang , Cheng Quan , Luo Peng , Zhang Jian , Han Xinwei 
Published: October 2022

AbstractAdvances in multi-omics and big-data technologies have led to numerous prognostic signatures aimed at improving current clinicopathological staging systems. Due to the lack of reproducibility and independent confirmation, few signatures have been translated into clinical routine. As high-quality datasets accumulate, identifying robust signatures across multiple independent cohorts becomes possible. Nonetheless, inaccurate data retrieval, different versions of genome annotations, disparate expression distributions, difficult data cleaning, inconsistent clinical information, algorithm selection, and parameter tuning have impeded model development and validation in multi-center datasets. Hence, for the first time, we introduced SurvivalML (https://rookieutopia.com/app_direct/SurvivalML/), a web application for helping develop and validate prognostic models across multi-center datasets. SurvivalML included 37,325 samples (253 eligible datasets) with both transcriptome data and survival information from 21 cancer types, which were renewedly and uniformly re-annotated, normalized, and cleaned. This application provided 10 survival machine-learning algorithms for flexibly training models via tuning essential parameters online and delivered four aspects for model evaluation, including Kaplan-Meier survival analysis, time-dependent ROC, calibration curve, and decision curve analysis. Overall, we believe that SurvivalML can serve as an attractive platform for model discovery from multi-center datasets.
MeCP2 represses the induction and maintenance of long-term synaptic plasticity
Authors: Liu Rong-Yu , Zhang Yili , Smolen Paul , Byrne John H. 
Published: October 2022

AbstractMechanisms of specific memory deficits associated with Rett syndrome are poorly understood, at least in part because mutations ofMECP2have confounding effects on nervous system development and basal synaptic transmission. To mitigate such empirical uncertainties, this study exploited technical advantages of theAplysiasensorimotor synapse to examine the potential role of MeCP2 in long-term synaptic plasticity. The results indicate MeCP2 may act as an inhibitory constraint on gene expression required for formation as well as maintenance of plasticity.