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Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,616 bioRxiv papers from 308,268 authors.

Most tweeted bioRxiv papers, last 24 hours

398 results found. For more information, click each entry to expand.

341: BiofilmQ, a software tool for quantitative image analysis of microbial biofilm communities
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Posted to bioRxiv 15 Aug 2019

BiofilmQ, a software tool for quantitative image analysis of microbial biofilm communities
1 tweet microbiology

Raimo Hartmann, Hannah Jeckel, Eric Jelli, Praveen K Singh, Sanika Vaidya, Miriam Bayer, Lucia Vidakovic, Francisco Díaz-Pascual, Jiunn C.N. Fong, Anna Dragoš, Olga Besharova, Carey D. Nadell, Victor Sourjik, Ákos T. Kovács, Fitnat H. Yildiz, Knut Drescher

Biofilms are now considered to be the most abundant form of microbial life on Earth, playing critical roles in biogeochemical cycles, agriculture, and health care. Phenotypic and genotypic variations in biofilms generally occur in three-dimensional space and time, and biofilms are therefore often investigated using microscopy. However, the quantitative analysis of microscopy images presents a key obstacle in phenotyping biofilm communities and single-cell heterogeneity inside biofilms. Here, we present BiofilmQ, a comprehensive image cytometry software tool for the automated high-throughput quantification and visualization of 3D and 2D community properties in space and time. Using BiofilmQ does not require prior knowledge of programming or image processing and provides a user-friendly graphical user interface, resulting in editable publication-quality figures. BiofilmQ is designed for handling fluorescence images of any spatially structured microbial community and growth geometry, including microscopic, mesoscopic, macroscopic colonies and aggregates, as well as bacterial biofilms in the context of eukaryotic hosts.

342: Station and train surface microbiomes of Mexico City's metro (subway/underground)
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Posted to bioRxiv 14 Aug 2019

Station and train surface microbiomes of Mexico City's metro (subway/underground)
1 tweet microbiology

Apolinar Misael Hernández, Daniela Vargas-Robles, Luis D. Alcaraz, Mariana Peimbert

The metro is one of the more representative urban systems of Mexico City, and it transports approximately 4.5 million commuters every day. Large crowds promote the constant exchange of human and environmental microbes. In this study, we determined the bacterial diversity profile of the Mexico City subway by massive sequencing of the 16S rRNA gene. We identified a total of 50,197 operative taxonomic units (OTUs) and 1058 genera. The metro microbiome was dominated by the phylum Actinobacteria and by the genera Propionibacterium (15%) (P. acnes 13%), Corynebacterium (13%), Streptococcus (9%), and Staphylococcus (5%) (S. epidermidis; 4%), reflecting the microbe composition of normal human skin. The metro microbial sources were skin, dust, saliva, and vaginal, with no fecal contribution detected. A total of 420 bacterial genera were universal to the twelve metro lines tested, and they contributed to 99.10% of the abundance. The large OTUs number are probably reflecting the vast human influx, while selection from hosts and environments are constraining the genera diversity, shown by the OTUs to genus ratio. Finally, this study shows that the microbial composition of the Mexico City subway comes from a mixture of environmental and human sources and that commuters are exposed to normal human microbiota.

343: Analysis of functional connectivity and oscillatory power using DICS: from raw MEG data to group-level statistics in Python
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Posted to bioRxiv 16 Jan 2018

Analysis of functional connectivity and oscillatory power using DICS: from raw MEG data to group-level statistics in Python
1 tweet neuroscience

Marijn van Vliet, Mia Liljeström, Susanna Aro, Riitta Salmelin, Jan Kujala

Communication between brain regions is thought to be facilitated by the synchronization of oscillatory activity. Hence, large-scale functional networks within the brain may be estimated by measuring synchronicity between regions. Neurophysiological recordings, such as magnetoencephalography (MEG) and electroencephalography (EEG), provide a direct measure of oscillatory neural activity with millisecond temporal resolution. In this paper, we describe a full data analysis pipeline for functional connectivity analysis based on dynamic imaging of coherent sources (DICS) of MEG data. DICS is a beamforming technique in the frequency-domain that enables the study of the cortical sources of oscillatory activity and synchronization between brain regions. All the analysis steps, starting from the raw MEG data up to publication-ready group-level statistics and visualization, are discussed in depth, including methodological considerations, rules of thumb and tradeoffs. We start by computing cross-spectral density (CSD) matrices using a wavelet approach in several frequency bands (alpha, theta, beta, gamma). We then provide a way to create comparable source spaces across subjects and discuss the cortical mapping of spectral power. For connectivity analysis, we present a canonical computation of coherence that facilitates a stable estimation of all-to-all connectivity. Finally, we use group-level statistics to limit the network to cortical regions for which significant differences between experimental conditions are detected and produce vertex- and parcel-level visualizations of the different brain networks. Code examples using the MNE-Python package are provided at each step, guiding the reader through a complete analysis of the freely available openfMRI ds000117 "familiar vs. unfamiliar vs. scrambled faces" dataset. The goal is to educate both novice and experienced data analysts with the "tricks of the trade" necessary to successfully perform this type of analysis on their own data.

344: Bagging Improves Reproducibility of Functional Parcellation of the Human Brain
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Posted to bioRxiv 11 Jun 2018

Bagging Improves Reproducibility of Functional Parcellation of the Human Brain
1 tweet neuroscience

Aki Nikolaidis, Anibal Solon Heinsfeld, Ting Xu, Pierre Bellec, Joshua Vogelstein, Michael Milham

Increasing the reproducibility of neuroimaging measurement addresses a central impediment to the advancement of human neuroscience and its clinical applications. Recent efforts demonstrating variance in functional brain organization within and between individuals shows a need for improving reproducibility of functional parcellations without long scan times. We apply bootstrap aggregation, or bagging, to the problem of improving reproducibility in functional parcellation. We use two large datasets to demonstrate that compared to a standard clustering framework, bagging improves the reproducibility and test-retest reliability of both cortical and subcortical functional parcellations across a range of sites, scanners, samples, scan lengths, clustering algorithms, and clustering parameters (e.g., number of clusters, spatial constraints). With as little as six minutes of scan time, bagging creates more reproducible parcellations than standard approaches with twice as much data. This suggests that regardless of the specific parcellation strategy employed, bagging may be a key method for improving functional parcellation and bringing functional neuroimaging-based measurement closer to clinical impact.

345: Six-state amino acid recoding is not an effective strategy to offset the effects of compositional heterogeneity and saturation in phylogenetic analyses
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Posted to bioRxiv 08 Aug 2019

Six-state amino acid recoding is not an effective strategy to offset the effects of compositional heterogeneity and saturation in phylogenetic analyses
1 tweet evolutionary biology

Alexandra M. Hernandez, Joseph F Ryan

Six-state amino acid recoding strategies are commonly applied to combat the effects of compositional heterogeneity and substitution saturation in phylogenetic analyses. While these methods have been endorsed from a theoretical perspective, their performance has never been extensively tested. Here, we test the effectiveness of 6-state recoding approaches by comparing the performance of analyses on recoded and non-recoded datasets that have been simulated under gradients of compositional heterogeneity or saturation. In all of our simulation analyses, non-recoding approaches greatly outperformed 6-state recoding approaches. Our results suggest that 6-state recoding strategies are not effective in the face of high saturation. Further, while recoding strategies do buffer the effects of compositional heterogeneity, the loss of information that accompanies 6-state recoding outweighs its benefits, even in the most compositionally heterogeneous datasets. In addition, we evaluate recoding schemes with 9, 12, 15, and 18 states and show that these all outperform 6-state recoding. Our results have important implications for the more than 70 published papers that have incorporated 6-state recoding, many of which have significant bearing on relationships across the tree of life.

346: Metabolic and Epigenomic Regulation of Th17/Treg Balance by the Polyamine Pathway
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Posted to bioRxiv 23 Jan 2020

Metabolic and Epigenomic Regulation of Th17/Treg Balance by the Polyamine Pathway
1 tweet immunology

Chao Wang, Allon Wagner, Johannes Fessler, Julian Avila-Pacheco, Jim Karminski, Pratiksha Thakore, Sarah Zaghouani, Kerry Pierce, Lloyd Bod, Alexandra Schnell, David DeTomaso, Noga Ron-Harel, Marcia Haigis, Daniel Puleston, Erika Pearce, Manoocher Soleimani, Ray Sobel, Clary Clish, Aviv Regev, Nir Yosef, Vijay Kuchroo

Cellular metabolism can orchestrate immune cell function. We previously demonstrated that lipid biosynthesis represents one such gatekeeper to Th17 cell functional state. Utilizing Compass, a transcriptome-based algorithm for prediction of metabolic flux, we constructed a comprehensive metabolic circuitry for Th17 cell function and identified the polyamine pathway as a candidate metabolic node, the flux of which regulates the inflammatory function of T cells. Testing this prediction, we found that expression and activities of enzymes of the polyamine pathway were enhanced in pathogenic Th17 cells and suppressed in regulatory T cells. Perturbation of the polyamine pathway in Th17 cells suppressed canonical Th17 cell cytokines and promoted the expression of Foxp3, accompanied by dramatic shift in transcriptome and epigenome, transitioning Th17 cells into a Treg-like state. Genetic and chemical perturbation of the polyamine pathway resulted in attenuation of tissue inflammation in an autoimmune disease model of central nervous system, with changes in T cell effector phenotype.

347: Linguistic input drives brain network configuration during language comprehension.
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Posted to bioRxiv 23 Jan 2020

Linguistic input drives brain network configuration during language comprehension.
1 tweet neuroscience

Ileana Quinones, Nicola Molinaro, Cesar Caballero Gaudes, Simona Mancini, Juan Andres Hernandez-Cabrera, Horacio Barber, Manuel Carreiras

Assessing the synchrony and interplay between distributed neural regions is critical to understanding how language is processed. Here, we investigated possible neuro-functional links between form and meaning during sentence comprehension combining a classical whole-brain approach to characterize patterns of brain activation resulting from our experimental manipulation with a novel multivariate network-based approach where the combination of graph-theory measures allow us to unravel the architectonic configuration of the language system. Capitalizing on the Spanish gender agreement system, we experimentally manipulated formal and conceptual factors: whether the noun-adjective grammatical gender relationship was congruent or not and whether the noun gender type was conceptual or strictly formal. Left inferior and middle frontal gyri, as well as left MTG/STG emerged as critical areas for the computation of grammatical relations. However, critically, we demonstrate how the interface between formal and conceptual features depends on the synergic articulation of brain areas divided in three subnetworks and extends beyond this classical left-lateralized perisylvian language circuit. Critically, we isolated a subregion of the left angular gyrus showing a significant interaction between gender congruency and gender type. The functional interplay between the angular gyrus and left perisylvian language-specific circuit was identified as crucial for constructing coherent and meaningful messages. Importantly, using graph theory we show the functional malleability of this complex system, so that the role each node play within the network changes depending on the available linguistic cues.

348: A time resolved interaction analysis of Bem1 reconstructs the flow of Cdc42 during polar growth
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Posted to bioRxiv 02 Aug 2019

A time resolved interaction analysis of Bem1 reconstructs the flow of Cdc42 during polar growth
1 tweet cell biology

Sören Grinhagens, Alexander Dünkler, Yehui Wu, Lucia Rieger, Philipp Brenner, Thomas Gronemeyer, Nils Johnsson

Cdc42 organizes cellular polarity and directs the formation of cellular structures in many organisms. By locating Cdc24, the source of active Cdc42, to the growing edge of the yeast cell, the scaffold protein Bem1 is instrumental in shaping the cellular gradient of Cdc42. This gradient instructs bud formation, bud growth, or cytokinesis through the actions of a diverse set of effector proteins. To address how Bem1 participates in this transformation we systematically mapped its protein interactions in time and space. SPLIFF analysis defined a unique ensemble of Bem1 interaction-states for each cell cycle stage. The characterization of mutants of Bem1 that interact with a discrete subset of the interaction partners allowed to assign specific functions to different interaction states and identified the determinants for their cellular distributions. The analysis characterizes Bem1 as a cell cycle specific shuttle that distributes active Cdc42 from its source to its effectors and helps to convert the PAKs Cla4 and Ste20 into their active conformation.

349: Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology
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Posted to bioRxiv 02 Jul 2019

Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology
1 tweet immunology

Travis K Hughes, Marc H Wadsworth, Todd M Gierahn, Tran Do, David Weiss, Priscilla R. Andrade, Feiyang Ma, Bruno J. de Andrade Silva, Shuai Shao, Lam C Tsoi, Jose Ordovas-Montanes, Johann E Gudjonsson, Robert L Modlin, J Christopher Love, Alex K. Shalek

The development of high-throughput single-cell RNA-sequencing (scRNA-Seq) methodologies has empowered the characterization of complex biological samples by dramatically increasing the number of constituent cells that can be examined concurrently. Nevertheless, these approaches typically recover substantially less information per-cell as compared to lower-throughput microtiter plate-based strategies. To uncover critical phenotypic differences among cells and effectively link scRNA-Seq observations to legacy datasets, reliable detection of phenotype-defining transcripts – such as transcription factors, affinity receptors, and signaling molecules – by these methods is essential. Here, we describe a substantially improved massively-parallel scRNA-Seq protocol we term Seq-Well S^3 (“Second-Strand Synthesis”) that increases the efficiency of transcript capture and gene detection by up to 10- and 5-fold, respectively, relative to previous iterations, surpassing best-in-class commercial analogs. We first characterized the performance of Seq-Well S^3 in cell lines and PBMCs, and then examined five different inflammatory skin diseases, illustrative of distinct types of inflammation, to explore the breadth of potential immune and parenchymal cell states. Our work presents an essential methodological advance as well as a valuable resource for studying the cellular and molecular features that inform human skin inflammation.

350: Movement patterns of free-roaming dogs on heterogeneous urban landscapes: implications for rabies control
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Posted to bioRxiv 27 Jun 2019

Movement patterns of free-roaming dogs on heterogeneous urban landscapes: implications for rabies control
1 tweet ecology

Brinkley Raynor, Micaela De la Puente-León, Andrew Johnson, Elvis Díaz-Espinoza, Michael Z Levy, Sergio E. Recuenco, Ricardo Castillo-Neyra

In 2015, a case of canine rabies in Arequipa, Peru indicated the re-emergence of rabies virus in the city. Despite mass dog vaccination campaigns across the city and reactive ring vaccination and other control activities around positive cases (e.g. elimination of unowned dogs), the outbreak has spread. Here we explore how the urban landscape of Arequipa affects the movement patterns of free-roaming dogs, the main reservoirs of the rabies virus in the area. We tracked 23 free-roaming dogs using Global Positioning System (GPS) collars. We analyzed the spatio-temporal GPS data using the time- local convex hull method. Dog movement patterns varied across local environments. We found that water channels, an urban feature of Arequipa that are dry most of the year, promote movement. Dogs that used the water channels move further, faster and more directionally than dogs that do not. Our findings suggest that water channels can be used by dogs as ‘highways’ to transverse the city and have the potential to spread disease far beyond the radius of control practices. Control efforts should focus on a robust vaccination campaign attuned to the geography of the city, and not limited to small-scale rings surrounding cases.

351: PIWI proteins as prognostic markers in cancer: a systematic review and meta-analysis
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Posted to bioRxiv 14 Jun 2019

PIWI proteins as prognostic markers in cancer: a systematic review and meta-analysis
1 tweet epidemiology

Alexios-Fotios A. Mentis, Efthimios Dardiotis, Athanassios G. Papavassiliou

Background: PIWI proteins, which interact with piRNAs, are implicated in stem cell and germ cell regulation, but have been detected in various cancers, as well. Objectives: In this systematic review, we explored, for the first time in the literature (to our knowledge), the association between prognosis in patients with cancer and intratumoral expression of PIWI proteins. Data sources: PubMed, Embase and Web of Knowledge databases were searched for the relevant cohort studies. Study eligibility criteria: Prospective or retrospective cohort studies investigating the association of intratumoral mRNA or protein expression of different types of PIWI proteins with survival, metastasis or recurrence of various types of cancers in the systematic review. Exclusion of cross-sectional studies, of studies on the prognostic value of genetic polymorphism of PIWI genes, of studies re-analyzed previously published databases, and of conference abstracts and non-English articles. Participants: Twenty-six studies with 4,299 participants were included in the systematic review. Interventions: Pooled Hazard Ratios (HRs) and their 95% Confidence Intervals (CIs) were calculated for different PIWI proteins separately, by pooling of log of the calculated HRs using the random-effects model. Study appraisal and synthesis methods: Data extraction was performed using a pre-designed form and quality of the studies was assessed using REMARK criteria. Heterogeneity assessed using the I2 index and the Cochran Q test. Publication bias assessed using funnel plots and Egger's regression. Results: The pooled HR of mortality in high compared to low expression of HIWI, HILI and PIWIL4 was 1.87 (CI95%: 1.31-2.66, p < 0.05), 1.09 (CI95%: 0.58-2.07, p = 0.79) and 0.44 (CI95%: 0.25-0.76, p < 0.05), respectively. The pooled HR of recurrence in in high compared to low expression of HIWI and HILI was 1.72 (CI95%: 1.20-2.49, p < 0.05) and 1.98 (CI95%: 0.65-5.98, p = 0.23), respectively. Limitations: Exclusion of studies not in English; Discrepancy between mRNA and protein levels, and the respective analytical methods; Only one cancer site -PIWI protein pair investigated in three or more studies. Conclusions and Implications of Key Findings: The prognosis of cancer patients is worse with higher HIWI and lower PIWIL4 expression, although the results are highly variable for different cancers. The expression of these proteins can be used for personalized prognostication and treatment of individual patients.

352: Fluorescence Labeling of Circulating Tumor Cells with Folate Receptor Targeted Molecular Probes for Diffuse In Vivo Flow Cytometry
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Posted to bioRxiv 23 Jan 2020

Fluorescence Labeling of Circulating Tumor Cells with Folate Receptor Targeted Molecular Probes for Diffuse In Vivo Flow Cytometry
1 tweet bioengineering

Roshani A Patil, Madduri Srinivasarao, Mansoor Amiji, Philip S. Low, Mark Niedre

Purpose: We recently developed a new instrument called diffuse in vivo flow cytometry (DiFC) for enumeration of rare fluorescently-labeled circulating tumor cells (CTCs) in small animals without drawing blood samples. Until now, we have used cell lines that express fluorescent proteins, or were pre-labeled with a fluorescent dye ex-vivo. In this work, we investigated the use of two folate receptor (FR)-targeted fluorescence molecular probes for in vivo labeling of FR+ CTCs for DiFC. Methods: We used EC-17 and Cy5-PEG-FR fluorescent probes. We studied the affinity of these probes for L1210A and KB cancer cells, both of which over-express FR. We tested the labeling specificity in cells in culture in vitro, in whole blood, and in mice in vivo. We also studied detectability of labeled cells with DiFC. Results: Both EC-17 and Cy5-PEG-FR probes had high affinity for FR+ CTCs in cell culture in vitro. However, only EC-17 had sufficient specificity for CTCs in whole blood. EC-17 labeled CTCs were also readily detectable in circulation in mice with DiFC. Conclusions: This work demonstrates the feasibility of labeling CTCs for DiFC with a cell surface receptor targeted probe, greatly expanding the utility of the method for pre-clinical animal models. Because DiFC uses diffuse light, this method could be also used to enumerate CTCs in larger animal models and potentially in humans.

353: A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports.
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Posted to bioRxiv 14 Jun 2019

A new tool CovReport generates easy-to-understand sequencing coverage summary for diagnostic reports.
1 tweet bioinformatics

Mark Gorokhov, Mathieu Cerino, Marc Bartoli, Martin Krahn, Svetlana Gorokhova

In order to properly interpret the results of a diagnostic gene panel sequencing test, gene coverage needs to be taken into consideration. If coverage is too low, an additional re-sequencing test is needed to make sure that a pathogenic variant is not missed. To facilitate the interpretation of coverage data, we designed CovReport, a novel easy-to-use visualization tool. CovReport generates a concise coverage summary that allows one-glance assessment of the sequencing test performance. Both gene-level and exon-level coverage can be immediately appreciated and taken into consideration for further medical decisions. CovReport does not require complex installation and can thus be easily implemented in any diagnostic laboratory setting. A user-friendly interface generates a graphic summary of coverage that can be directly included in the diagnostic report. In addition to a stand-alone version, we also provide a command line version of CovReport that can be integrated into any bioinformatics pipeline. This flexible tool is now part of routine sequencing analysis at the Department of Medical Genetics at La Timone Hospital (Marseille, France). Availability and implementation: CovReport is available at http://jdotsoft.com/CovReport.php. It is implemented in Java and supported on Windows, Mac OS X and Linux.

354: Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population
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Posted to bioRxiv 13 Jun 2019

Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population
1 tweet neuroscience

M Montagnese, F Knolle, J. Haarsma, J.D. Griffin, A Richards, P Vertes, B Kiddle, P.C. Fletcher, PB Jones, MJ Owen, P Fonagy, ET Bullmore, R Dolan, NSPN Consortium, M Moutoussis, I Goodyer, G.K Murray

Background Schizophrenia is a complex disorder in which the causal relations between risk genes and observed clinical symptoms are not well understood and the explanatory gap is too wide to be clarified without considering an intermediary level. Thus, we aimed to test the hypothesis of a pathway from molecular polygenic influence to clinical presentation occurring via deficits in reinforcement learning. Methods We administered a reinforcement learning task (Go/NoGo) that measures reinforcement learning and the effect of Pavlovian bias on decision making. We modelled the behavioural data with a hierarchical Bayesian approach (hBayesDM) to decompose task performance into its underlying learning mechanisms. Study 1 included controls ( n = 29, F|M=0.81), At Risk Mental State for psychosis (ARMS, n = 23, F|M=0.35) and FEP (First-episode psychosis, n = 26, F|M=0.18). Study 2 included healthy adolescents ( n = 735, F|M= 1.06), 390 of whom had their polygenic risk scores for schizophrenia (PRSs) calculated. Results Patients with FEP showed significant impairments in overriding Pavlovian conflict, a lower learning rate and a lower sensitivity to both reward and punishment. Less widespread deficits were observed in ARMS. PRSs did not significantly predict performance on the task in the general population, which only partially correlated with measures of psychopathology. Conclusions Reinforcement learning deficits are observed in first episode psychosis and, to some extent, in those at clinical risk for psychosis, and were not predicted by molecular genetic risk for schizophrenia in healthy individuals. The study does not support the role of reinforcement learning as an intermediate phenotype in psychosis.

355: Systematic detection of divergent brain protein-coding genes in human evolution and their roles in cognition
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Posted to bioRxiv 03 Jun 2019

Systematic detection of divergent brain protein-coding genes in human evolution and their roles in cognition
1 tweet genetics

G. Dumas, Simon Malesys, Thomas Bourgeron

The human brain differs from that of other primates, but the genetic basis of these differences remains unclear. We investigated the evolutionary pressures acting on almost all human protein-coding genes (N=17,808) on the basis of their divergence from those of early hominins, such as Neanderthals, and non-human primates. We confirm that genes encoding brain-related proteins are among the most strongly conserved protein-coding genes in the human genome. Combining our evolutionary pressure metrics for the protein-coding genome with recent datasets, we found that this conservation applied to genes functionally associated with the synapse and expressed in brain structures such as the prefrontal cortex and the cerebellum. Conversely, several of the protein-coding genes in that diverge most in humans relative to other primates are associated with brain-associated diseases, such as micro/macrocephaly, dyslexia, and autism. We also showed that cerebellum granule neurons express a set of divergent protein-coding genes that may have contributed to the emergence of fine motor skills and social cognition in humans. This resource is available from http://neanderthal.pasteur.fr and can be used to estimate evolutionary constraints acting on a set of genes and to explore their relative contributions to human traits.

356: How biological attention mechanisms improve task performance in a large-scale visual system model
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Posted to bioRxiv 13 Dec 2017

How biological attention mechanisms improve task performance in a large-scale visual system model
1 tweet neuroscience

Grace W. Lindsay, Kenneth D. Miller

How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.

357: Tagsteady: a metabarcoding library preparation protocol to avoid false assignment of sequences to samples
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Posted to bioRxiv 23 Jan 2020

Tagsteady: a metabarcoding library preparation protocol to avoid false assignment of sequences to samples
1 tweet molecular biology

Christian Caroe, Kristine Bohmann

Metabarcoding of environmental DNA (eDNA) and DNA extracted from bulk specimen samples is a powerful tool in studies of biodiversity, diet and ecological interactions as its inherent labelling of amplicons allows sequencing of taxonomically informative genetic markers from many samples in parallel. However, the occurrence of so-called ′tag-jumps′ can cause incorrect assignment of sequences to samples and artificially inflate diversity. Two steps during library preparation of pools of 5′ nucleotide-tagged amplicons have been suggested to cause tag-jumps; i) T4 DNA polymerase blunt-ending in the end-repair step and ii) post-ligation PCR amplification of amplicon libraries. The discovery of tag-jumps has led to recommendations to only carry out metabarcoding PCR amplifications with primers carrying twin-tags to ensure that tag-jumps cannot result in false assignments of sequences to samples. As this increases both cost and workload, a metabarcoding library preparation protocol which circumvents the two steps that causes tag-jumps is needed. Here, we demonstrate Tagsteady, a metabarcoding Illumina library preparation protocol for pools of nucleotide-tagged amplicons that enables efficient and cost-effective generation of metabarcoding data with virtually no tag-jumps. We use pools of twin-tagged amplicons to investigate the effect of T4 DNA polymerase blunt-ending and post-ligation PCR on the occurrence of tag-jumps. We demonstrate that both blunt-ending and post-ligation PCR, alone or together, can result in detrimental amounts of tag-jumps (here, up to ca. 49% of total sequences), while leaving both steps out (the Tagsteady protocol) results in amounts of sequences carrying new combinations of used tags (tag-jumps) comparable to background contamination.

358: High-throughput screens of PAM-flexible Cas9 variants for gene knock-out and transcriptional modulation
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Posted to bioRxiv 23 Jan 2020

High-throughput screens of PAM-flexible Cas9 variants for gene knock-out and transcriptional modulation
1 tweet bioengineering

Mateusz Legut, Zharko Daniloski, Xinhe Xue, Dayna McKenzie, Xinyi Guo, Hans-Hermann Wessels, Neville E Sanjana

A key limitation of the commonly-used CRISPR enzyme S. pyogenes Cas9 is the strict requirement of an NGG protospacer-adjacent motif (PAM) at the target site, which reduces the number of accessible genomic loci. This constraint can be limiting for genome editing applications that require precise Cas9 positioning. Recently, two Cas9 variants with a relaxed PAM requirement (NG) have been developed (xCas9 and Cas9-NG) but their activity has been measured at only a small number of endogenous sites. Here we devised a high-throughput Cas9 pooled competition screen to compare the performance of both PAM-flexible Cas9 variants and wild-type Cas9 at thousands of genomic loci and across 3 modalities (gene knock-out, transcriptional activation and suppression). We show that PAM flexibility comes at a substantial cost of decreased DNA targeting and cutting. Of the PAM-flexible variants, we found that Cas9-NG outperforms xCas9 regardless of genome engineering modality or PAM. Finally, we combined xCas9 mutations with those of Cas9-NG, creating a stronger transcriptional modulator than existing PAM-flexible Cas9 variants.

359: The Impact of Pathway Database Choice on Statistical Enrichment Analysis and Predictive Modeling
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Posted to bioRxiv 31 May 2019

The Impact of Pathway Database Choice on Statistical Enrichment Analysis and Predictive Modeling
1 tweet bioinformatics

Sarah Mubeen, Charles Tapley Hoyt, Andre Gemünd, Martin Hofmann-Apitius, Holger Fröhlich, Daniel Domingo-Fernández

Background: Pathway-centric approaches are widely used to interpret and contextualize -omics data. However, databases contain different representations of the same biological pathway, which may lead to different results of statistical enrichment analysis and predictive models in the context of precision medicine. Results: We have performed an in-depth benchmarking of the impact of pathway database choice on statistical enrichment analysis and predictive modeling. We analyzed five cancer datasets using three major pathway databases and developed an approach to merge several databases into a single integrative database: MPath. Our results show that equivalent pathways from different databases yield disparate results in statistical enrichment analysis. Moreover, we observed a significant dataset-dependent impact on performance of machine learning models on different prediction tasks. Further, MPath significantly improved prediction performance and reduced the variance of prediction performances in some cases. At the same time, MPath yielded more consistent and biologically plausible results in the statistical enrichment analyses. Finally, we implemented a software package designed to make our comparative analysis with these and additional databases fully reproducible and to facilitate the update of our integrative pathway resource in the future. Conclusion: This benchmarking study demonstrates that pathway database choice can influence the results of statistical enrichment analysis and prediction modeling. Therefore, we recommend the use of multiple pathway databases or the use of integrative databases.

360: Single-cell transcriptional diversity is a hallmark of developmental potential
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Posted to bioRxiv 30 May 2019

Single-cell transcriptional diversity is a hallmark of developmental potential
1 tweet genomics

Gunsagar S. Gulati, Shaheen S. Sikandar, Daniel J Wesche, Anoop Manjunath, Anjan Bharadwaj, Mark J Berger, Francisco Ilagan, Angera H Kuo, Robert W Hsieh, Shang Cai, Maider Zabala, Ferenc A Scheeren, Neethan A. Lobo, Dalong Qian, Feiqiao Brian Yu, Frederick M Dirbas, Michael F Clarke, Aaron M. Newman

Single-cell RNA-sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation without prior knowledge has remained challenging. Here we describe a simple yet robust determinant of developmental potential—the number of detectably expressed genes per cell—and leverage this measure of transcriptional diversity to develop a new framework for predicting ordered differentiation states from scRNA-seq data. When evaluated on ~150,000 single-cell transcriptomes spanning 53 lineages and five species, our approach, called CytoTRACE, outperformed previous methods and ~19,000 molecular signatures for resolving experimentally-confirmed developmental trajectories. In addition, it enabled unbiased identification of tissue-resident stem cells, including cells with long-term regenerative potential. When used to analyze human breast tumors, we discovered candidate genes associated with less-differentiated luminal progenitor cells and validated GULP1 as a novel gene involved in tumorigenesis. Our study establishes a key RNA-based correlate of developmental potential and provides a new platform for robust delineation of cellular hierarchies (https://cytotrace.stanford.edu).

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