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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 57,915 bioRxiv papers from 266,490 authors.

Most downloaded bioRxiv papers, since beginning of last month

56,515 results found. For more information, click each entry to expand.

181: Comparative transcriptomic and epigenomic analysis identifies key regulators of injury response and neurogenic competence in retinal glia
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Posted to bioRxiv 30 Jul 2019

Comparative transcriptomic and epigenomic analysis identifies key regulators of injury response and neurogenic competence in retinal glia
629 downloads neuroscience

Thanh Hoang, Jie Wang, Patrick Boyd, Fang Wang, Clayton Santiago, Lizhi Jiang, Manuela Lahne, Levi Todd, Christian Saez, Sooyeon Yoo, Casey Keuthan, Isabella Palazzo, Nathalie Squires, Warren Campbell, Meng Jia, Fatemeh Rajaii, Trisha Parayil, Guohua Wang, John Ash, Andrew Fischer, David Hyde, Jiang Qian, Seth Blackshaw

Injury induces retinal Muller glia of cold-blooded, but not mammalian, vertebrates to generate neurons. To identify gene regulatory networks that control neurogenic competence in retinal glia, we comprehensively profiled injury-dependent changes in gene expression and chromatin conformation in Muller glia from zebrafish, chick and mice using bulk RNA and ATAC-Seq, as well as single-cell RNA-Seq. Integration of these data, together with functional analysis of candidate genes, identified evolutionarily conserved and species-specific gene networks controlling glial quiescence, gliosis, and neurogenic competence. In zebrafish and chick, transition from quiescence to gliosis is a critical stage in acquisition of neurogenic competence, while in mice a dedicated network suppresses this transition and rapidly restores quiescence. Selective disruption of NFI family transcription factors in mice, which maintain and restore quiescence, confers injury-dependent proliferative and neurogenic competence on Muller glia. These findings may help guide the design of cell-based therapies aimed at restoring retinal neurons lost in disease.

182: Hair-bearing human skin generated entirely from pluripotent stem cells
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Posted to bioRxiv 08 Jul 2019

Hair-bearing human skin generated entirely from pluripotent stem cells
628 downloads developmental biology

Jiyoon Lee, Cyrus Rabbani, Hongyu Gao, Matthew Steinhart, Benjamin W Woodruff, Zachary Pflum, Alexander Kim, Stefan Heller, Yunlong Liu, Taha Z Shipchandler, Karl R Koehler

The skin is important for regulating bodily fluid retention and temperature, guarding against external stresses, and mediating touch and pain sensation. The skin is also susceptible to damage from burns, diseases, or genetic defects, which affect nearly one billion people worldwide. For the advancement of skin regenerative therapies, it remains challenging to construct new skin with hair follicles and nerves in tissue cultures and in bioengineered skin grafts. Here, we report an organoid culture system that generates complex skin from human pluripotent stem cells. We use step-wise modulation of the TGF and FGF signalling pathways to co-induce cranial epithelial cells and neural crest cells within a spherical cell aggregate. During 4-5 months incubation, we observe the emergence of a cyst-like skin organoid composed of stratified epidermis, fat-rich dermis, and pigmented hair follicles equipped with sebaceous glands. A network of sensory neurons and Schwann cells form nerve-like bundles that target Merkel cells in organoid hair follicles, mimicking human touch circuitry. Single-cell RNA sequencing and direct comparison to foetal specimens suggest that skin organoids are equivalent to human facial skin in the second-trimester of development. Moreover, we show that skin organoids produce planar hair-bearing skin when grafted on nude mice. Together, our results demonstrate the self-assembly of nearly complete skin tissue in vitro that can be used to reconstitute skin in vivo. We anticipate that our skin organoid model will be foundational to future studies of human skin development, disease modelling, or reconstructive surgery.

183: A unified role for membrane-cortex detachment during cell protrusion initiation
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Posted to bioRxiv 08 Jul 2019

A unified role for membrane-cortex detachment during cell protrusion initiation
628 downloads cell biology

Erik S Welf, Christopher E Miles, Jaewon Huh, Meghan K Driscoll, Tadamoto Isogai, Jungsik Noh, Andrew D Weems, Joseph Chi, Theresa Pohlkamp, Kevin Dean, Reto Fiolka, Alex Mogilner, Gaudenz Danuser

Cell morphogenesis employs a diversity of membrane protrusions. They are discriminated by differences in force generation. Actin polymerization is the best studied mechanism of force generation, but growing interest in how variable molecular conditions and microenvironments alter morphogenesis has revealed other mechanisms, including intracellular pressure. Here, we show that local depletion of membrane cortex links is an essential step in the initiation of both pressure-based and actin-based protrusions. This observation challenges the quarter-century old Brownian ratchet model of actin-driven membrane protrusion, which requires an optimal balance of actin filament growth and membrane tethering. An updated model confirms membrane-filament detachment is necessary to activate the ratchet mechanism. These findings unify the regulation of different protrusion types, explaining how cells generate robust yet flexible strategies of morphogenesis.

184: A robust benchmark for germline structural variant detection
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Posted to bioRxiv 09 Jun 2019

A robust benchmark for germline structural variant detection
621 downloads genomics

Justin M Zook, Nancy F Hansen, Nathan D Olson, Lesley M Chapman, James C. Mullikin, Chunlin Xiao, Stephen Sherry, Sergey Koren, Adam M Phillippy, Paul C. Boutros, Sayed Mohammad E. Sahraeian, Vincent Huang, Alexandre Rouette, Noah Alexander, Christopher C Mason, Iman C Hajirasouliha, Camir C Ricketts, Joyce Lee, Rick Tearle, Ian T. Fiddes, Alvaro Martinez Barrio, Jeremiah Wala, Andrew Carroll, Noushin Ghaffari, Oscar L. Rodriguez, Ali Bashir, Shaun D Jackman, John J Farrell, Aaron M Wenger, Can Alkan, Arda Soylev, Michael C. Schatz, Shilpa Garg, George Church, Tobias Marschall, Ken Chen, Xian Fan, Adam C English, Jeffrey Dunn Rosenfeld, Weichen Zhou, Ryan E. Mills, Jay M. Sage, Jennifer R. Davis, Michael D. Kaiser, John S. Oliver, Anthony P Catalano, Noah Spies, Mark J.P. Chaisson, Fritz J. Sedlazeck, Marc Salit, Genome in a Bottle Consortium

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls ≥50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

185: Prefrontal somatostatin interneurons encode fear memory
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Posted to bioRxiv 09 Jul 2019

Prefrontal somatostatin interneurons encode fear memory
621 downloads neuroscience

Roger L Clem, Kirstie A Cummings

Theories stipulate that memories are encoded within networks of cortical projection neurons (PNs). Conversely, GABAergic interneurons (INs) are thought to function primarily to inhibit PNs and thereby impose network gain control, an important but purely modulatory role. However, we found that associative fear learning potentiates synaptic transmission and cue-specific activity of medial prefrontal cortex (mPFC) somatostatin interneurons (SST-INs), and that activation of these cells controls both memory encoding and expression. Furthermore, the synaptic organization of SST- and parvalbumin (PV)-INs provides a potential circuit basis for SST-IN-evoked disinhibition of mPFC output neurons and recruitment of remote brain regions associated with defensive behavior. These data suggest that rather than constrain mnemonic processing, potentiation of SST-IN activity represents an important causal mechanism for conditioned fear.

186: Human condensin I and II drive extensive ATP-dependent compaction of nucleosome-bound DNA
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Posted to bioRxiv 27 Jun 2019

Human condensin I and II drive extensive ATP-dependent compaction of nucleosome-bound DNA
619 downloads biochemistry

Muwen Kong, Erin Cutts, Dongqing Pan, Fabienne Beuron, Thangavelu Kaliyappan, Chaoyou Xue, Ed Morris, Andrea Musacchio, Alessandro Vannini, Eric Greene

Structural maintenance of chromosomes (SMC) complexes are essential for genome organization from bacteria to humans, but their mechanisms of action remain poorly understood. Here, we characterize human SMC complexes condensin I and II and unveil the architecture of the human condensin II complex, revealing two putative DNA-binding sites. Using single-molecule imaging, we demonstrate that both condensin I and II exhibit ATP-dependent motor activity and promote extensive and reversible compaction of double-stranded DNA. Nucleosomes are incorporated into DNA loops during compaction without being displaced from the DNA, indicating that condensin complexes can readily act upon nucleosome fibers. These observations shed light on critical processes involved in genome organization in human cells.

187: The Reproducibility Of Research And The Misinterpretation Of P Values
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Posted to bioRxiv 31 May 2017

The Reproducibility Of Research And The Misinterpretation Of P Values
618 downloads scientific communication and education

David Colquhoun

We wish to answer this question If you observe a “significant” P value after doing a single unbiased experiment, what is the probability that your result is a false positive? The weak evidence provided by P values between 0.01 and 0.05 is explored by exact calculations of false positive risks. When you observe P = 0.05, the odds in favour of there being a real effect (given by the likelihood ratio) are about 3:1. This is far weaker evidence than the odds of 19 to 1 that might, wrongly, be inferred from the P value. And if you want to limit the false positive risk to 5%, you would have to assume that you were 87% sure that there was a real effect before the experiment was done. If you observe P = 0.001 in a well-powered experiment, it gives a likelihood ratio of almost 100:1 odds on there being a real effect. That would usually be regarded as conclusive, But the false positive risk would still be 8% if the prior probability of a real effect was only 0.1. And, in this case, if you wanted to achieve a false positive risk of 5% you would need to observe P = 0.00045. It is recommended that the terms “significant” and “non-significant” should never be used. Rather, P values should be supplemented by specifying the prior probability that would be needed to produce a specified (e.g. 5%) false positive risk. It may also be helpful to specify the minimum false positive risk associated with the observed P value. Despite decades of warnings, many areas of science still insist on labelling a result of P < 0.05 as “statistically significant”. This practice must account for a substantial part of the lack of reproducibility in some areas of science. And this is before you get to the many other well-known problems, like multiple comparisons, lack of randomisation and P-hacking. Science is endangered by statistical misunderstanding, and by university presidents and research funders who impose perverse incentives on scientists.

188: Choice-selective sequences in cortical inputs to the NAc provide a potential substrate for credit assignment
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Posted to bioRxiv 06 Aug 2019

Choice-selective sequences in cortical inputs to the NAc provide a potential substrate for credit assignment
616 downloads neuroscience

Nathan F. Parker, Avinash Baidya, Malavika Murugan, Ben Engelhard, Anna Zhukovskaya, Mark S Goldman, Ilana B. Witten

How are actions linked with subsequent outcomes to guide choices? The nucleus accumbens (NAc), which is implicated in this process, receives glutamatergic inputs from the prelimbic cortex (PL) and midline regions of the thalamus (mTH). However, little is known about what is represented in PL or mTH neurons that project to NAc (PL-NAc and mTH-NAc). By comparing these inputs during a reinforcement learning task in mice, we discovered that i) PL-NAc preferentially represents actions and choices, ii) mTH-NAc preferentially represents cues, iii) choice-selective activity in PL-NAc is organized in sequences that persist beyond the outcome. Through computational modeling, we demonstrate that these sequences can support the neural implementation of temporal difference learning, a powerful algorithm to connect actions and outcomes across time. Finally, we test and confirm predictions of our circuit model by direct manipulation of PL-NAc neurons. Thus, we integrate experiment and modeling to suggest a neural solution for credit assignment.

189: Protocol: Genome-scale CRISPR-Cas9 Knockout and Transcriptional Activation Screening
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Posted to bioRxiv 18 Jun 2016

Protocol: Genome-scale CRISPR-Cas9 Knockout and Transcriptional Activation Screening
615 downloads molecular biology

Julia Joung, Silvana Konermann, Jonathan S Gootenberg, Omar O Abudayyeh, Randall J Platt, Mark D Brigham, Neville E Sanjana, Feng Zhang

Forward genetic screens are powerful tools for the unbiased discovery and functional characterization of specific genetic elements associated with a phenotype of interest. Recently, the RNA-guided endonuclease Cas9 from the microbial immune system CRISPR (clustered regularly interspaced short palindromic repeats) has been adapted for genome-scale screening by combining Cas9 with guide RNA libraries. Here we describe a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system. Custom- or ready-made guide RNA libraries are constructed and packaged into lentivirus for delivery into cells for screening. As each screen is unique, we provide guidelines for determining screening parameters and maintaining sufficient coverage. To validate candidate genes identified from the screen, we further describe strategies for confirming the screening phenotype as well as genetic perturbation through analysis of indel rate and transcriptional activation. Beginning with library design, a genome-scale screen can be completed in 6-10 weeks followed by 3-4 weeks of validation.

190: The successor representation in human reinforcement learning
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Posted to bioRxiv 27 Oct 2016

The successor representation in human reinforcement learning
615 downloads neuroscience

Ida Momennejad, Evan M. Russek, Jin H. Cheong, Matthew M. Botvinick, Nathaniel D. Daw, Samuel Gershman

Theories of reward learning in neuroscience have focused on two families of algorithms, thought to capture deliberative vs. habitual choice. Model-based algorithms compute the value of candidate actions from scratch, whereas model-free algorithms make choice more efficient but less flexible by storing pre-computed action values. We examine an intermediate algorithmic family, the successor representation (SR), which balances flexibility and efficiency by storing partially computed action values: predictions about future events. These pre-computation strategies differ in how they update their choices following changes in a task. SR's reliance on stored predictions about future states predicts a unique signature of insensitivity to changes in the task's sequence of events, but flexible adjustment following changes to rewards. We provide evidence for such differential sensitivity in two behavioral studies with humans. These results suggest that the SR is a computational substrate for semi-flexible choice in humans, introducing a subtler, more cognitive notion of habit.

191: Minor allele frequency thresholds strongly affect population structure inference with genomic datasets
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Posted to bioRxiv 14 Sep 2017

Minor allele frequency thresholds strongly affect population structure inference with genomic datasets
613 downloads genomics

Ethan B. Linck, C. J. Battey

Across the genome, the effects of different evolutionary processes and historical events can result in different classes of genetic variants (or alleles) characterized by their relative frequency in a given population. As a result, population genetic inference can be strongly affected by biases in laboratory and bioinformatics treatments that affect the site frequency spectrum, or SFS. Yet despite the widespread use of reduced-representation genomic datasets with nonmodel organisms, the potential consequences of these biases for downstream analyses remain poorly examined. Here, we assess the influence of minor allele frequency (MAF) thresholds implemented during variant detection on inference of population structure. We use simulated and empirical datasets to evaluate the effect of MAF thresholds on the ability to discriminate among populations and quantify admixture with both model-based and non-model-based clustering methods. We find model-based inference of population structure is highly sensitive to choice of MAF, and may be confounded by either including singletons or excluding all rare alleles. In contrast, non-model-based clustering is largely robust to MAF choice. Our results suggest that model-based inference of population structure can fail due to either natural demographic processes or assembly artifacts, with broad consequences for phylogeographic and population genetic studies using NGS data. We propose a simple hypothesis to explain this behavior and recommend a set of best practices for researchers seeking to describe population structure using reduced-representation libraries.

192: Creating a universal SNP and small indel variant caller with deep neural networks
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Posted to bioRxiv 14 Dec 2016

Creating a universal SNP and small indel variant caller with deep neural networks
610 downloads genomics

Ryan Poplin, Pi-Chuan Chang, David Alexander, Scott Schwartz, Thomas Colthurst, Alexander Ku, Dan Newburger, Jojo Dijamco, Nam Nguyen, Pegah T. Afshar, Sam S. Gross, Lizzie Dorfman, Cory Y. McLean, Mark A. DePristo

Next-generation sequencing (NGS) is a rapidly evolving set of technologies that can be used to determine the sequence of an individual's genome by calling genetic variants present in an individual using billions of short, errorful sequence reads. Despite more than a decade of effort and thousands of dedicated researchers, the hand-crafted and parameterized statistical models used for variant calling still produce thousands of errors and missed variants in each genome. Here we show that a deep convolutional neural network can call genetic variation in aligned next-generation sequencing read data by learning statistical relationships (likelihoods) between images of read pileups around putative variant sites and ground-truth genotype calls. This approach, called DeepVariant, outperforms existing tools, even winning the "highest performance" award for SNPs in a FDA-administered variant calling challenge. The learned model generalizes across genome builds and even to other species, allowing non-human sequencing projects to benefit from the wealth of human ground truth data. We further show that, unlike existing tools which perform well on only a specific technology, DeepVariant can learn to call variants in a variety of sequencing technologies and experimental designs, from deep whole genomes from 10X Genomics to Ion Ampliseq exomes. DeepVariant represents a significant step from expert-driven statistical modeling towards more automatic deep learning approaches for developing software to interpret biological instrumentation data.

193: A transparent model for learning in volatile environments
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Posted to bioRxiv 16 Jul 2019

A transparent model for learning in volatile environments
610 downloads neuroscience

Payam Piray, Nathaniel D. Daw

Sound principles of statistical inference dictate that uncertainty shapes learning. In this work, we revisit the question of learning in volatile environments, in which both the first and second-order statistics of environments dynamically evolve over time. We propose a new model, the volatile Kalman filter (VKF), which is based on a tractable state-space model of uncertainty and extends the Kalman filter algorithm to volatile environments. Algorithmically, the proposed model is simpler and more transparent than existing models, and encompasses the Kalman filter as a special case. Specifically, in addition to the error-correcting rule of Kalman filter for learning observations, the VKF learns volatility according to a second error-correcting rule. These dual updates echo and contextualize classical psychological models of learning, in particular hybrid accounts of Pearce-Hall and Rescorla-Wagner. At the computational level, compared with existing models, the VKF is more accurate, particularly in estimating volatility, as it is based on more faithful approximations to the exact inference. Accordingly, when fit to empirical data, the VKF is better behaved than alternatives and better captures human choice data in a probabilistic learning task. The proposed model provides a transparent and coherent account of learning in stable or volatile environments and has implications for decision neuroscience research.

194: A novel metric reveals previously unrecognized distortion in dimensionality reduction of scRNA-Seq data
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Posted to bioRxiv 02 Jul 2019

A novel metric reveals previously unrecognized distortion in dimensionality reduction of scRNA-Seq data
610 downloads bioinformatics

Shamus M. Cooley, Timothy Hamilton, Eric J. Deeds, J. Christian J. Ray

High-dimensional data are becoming increasingly common in nearly all areas of science. Developing approaches to analyze these data and understand their meaning is a pressing issue. This is particularly true for the rapidly growing field of single-cell RNA-Seq (scRNA-Seq), a technique that simultaneously measures the expression of tens of thousands of genes in thousands to millions of single cells. The emerging consensus for analysis workflows reduces the dimensionality of the dataset before performing downstream analysis, such as assignment of cell types. One problem with this approach is that dimensionality reduction can introduce substantial distortion into the data; consider the familiar example of trying to represent the three-dimensional earth as a two-dimensional map. It is currently unclear if such distortion affects analysis of scRNA-Seq data sets. Here, we introduce a straightforward approach to quantifying this distortion by comparing the local neighborhoods of points before and after dimensionality reduction. We found that popular techniques like t-SNE and UMAP introduce significant distortion even for relatively simple geometries such as simulated hyperspheres. For scRNA-Seq data, we found the distortion in local neighborhoods was greater than 95% in the 2- and 3-dimensional space typically used for downstream analysis. This high level of distortion can readily introduce important errors into cell type identification, pseudotime ordering, and other analyses that rely on local relationships. We found that principal component analysis can generate accurate embeddings of the data, but only when using dimensionalities that are much higher than typically used in scRNA-Seq analysis. We suggest approaches to take these findings into account and call for a new generation of dimensional reduction algorithms that can accurately embed high dimensional data in its true latent dimension.

195: A context-free grammar for Caenorhabditis elegans behavior
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Posted to bioRxiv 19 Jul 2019

A context-free grammar for Caenorhabditis elegans behavior
609 downloads animal behavior and cognition

Saurabh Gupta, Alex Gomez-Marin

Hierarchy is a candidate organizing principle of ethology, where actions grouped into higher order chunks combine in specific ways to generate adaptive behavior. However, demonstrations of hierarchical organization in behavior have been scarce. Moreover, it remains unclear how such underlying organization allows for behavioral flexibility. Here we uncover the hierarchical and flexible nature of Caenorhabditis elegans behavior. By describing worm locomotion as a sequence of discrete postural templates, we identified chunks containing mutually substitutable postures along the dynamics. We then elucidated the rules governing their interactions. We found that stereotypical roaming can be described by a specific sequence of postural chunks, which exhibit flexibility at the lowest postural level. The same chunks get combined differently to produce dwelling, capturing non-stereotypical actions across timescales. We show that worm foraging is organized hierarchically (a feature not explainable via Markovian dynamics), and derive a context-free grammar governing its behavior (which is different than a regular grammar, or a hidden Markov chain). In sum, in making the analogy with human language concrete (but not literal) our work demonstrates, in line with the foundational insights of classical ethologists, that spontaneous behavior is orderly flexible. Once more, investigating the humble nematode suggests that everything human has its roots in lower animal behavior.

196: Vaccine-induced ICOS+CD38+ cTfh are sensitive biosensors of age-related changes in inflammatory pathways
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Posted to bioRxiv 24 Jul 2019

Vaccine-induced ICOS+CD38+ cTfh are sensitive biosensors of age-related changes in inflammatory pathways
602 downloads immunology

Ramin S Herati, Luisa V. Silva, Laura A. Vella, Alexander Muselman, Cécile Alanio, Bertram Bengsch, Raj Kurupati, Senthil Kannan, Sasikanth Manne, Andrew Kossenkov, David Canaday, Susan Doyle, Hildegund Ertl, Kenneth Schmader, E. John Wherry

Humoral immune responses are dysregulated with aging but details remain incompletely understood. In particular, little is known about the effects of aging on T follicular helper (Tfh) CD4 cells, the subset that provides critical help to B cells for effective humoral immunity. We previously demonstrated that influenza vaccination increases a circulating Tfh (cTfh) subset that expresses ICOS and CD38, contains influenza-specific memory cells, and is correlated with antibody responses. To directly study the effects of aging on the cTfh response, we performed transcriptional profiling and cellular analysis before and after influenza vaccination in young and elderly adults. Several key differences in cTfh responses were revealed in the elderly. First, whole blood transcriptional profiling defined cross-validated genesets of youth versus aging and these genesets were, compared to other T cells, preferentially enriched in ICOS+CD38+ cTfh from young and elderly subjects, respectively, following vaccination. Second, vaccine-induced ICOS+CD38+ cTfh from the elderly were enriched for transcriptional signatures of inflammation including TNF-NFkB pathway activation. Indeed, we reveal a paradoxical positive effect of TNF signaling on Tfh providing help to B cells linked to survival circuits that may explain detrimental effects of TNF blockade on vaccine responses. Finally, vaccine-induced ICOS+CD38+ cTfh displayed strong enrichment for signatures of underlying age-associated biological changes. Thus, these data reveal key biological changes in cTfh during aging and also demonstrate the sensitivity of vaccine-induced cTfh to underlying changes in host physiology. This latter observation suggests that vaccine-induced cTfh could function as sensitive biosensors of underlying inflammatory and/or overall immune health.

197: Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure
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Posted to bioRxiv 10 Jul 2019

Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure
598 downloads genetics

Sonia Shah, Albert Henry, Carolina Roselli, Honghuang Lin, Garðar Sveinbjörnsson, Ghazaleh Fatemifar, Åsa K. Hedman, Jemma B Wilk, Michael P. Morley, Mark D. Chaffin, Anna Helgadottir, Niek Verweij, Abbas Dehghan, Peter Almgren, Charlotte Anderson, Krishna G. Aragam, Johan Ärnlöv, Joshua D Backman, Mary L Biggs, Heather L Bloom, Jeffrey Brandimarto, Broad AF Investigators, Michael R Brown, Leonard Buckbinder, David J Carey, Regeneron Genetics Center, Daniel I Chasman, Xing Chen, Xu Chen, Jonathan Chung, William Chutkow, James P Cook, Graciela E Delgado, Spiros Denaxas, Alexander S Doney, Marcus Dörr, Samuel C Dudley, Michael E Dunn, EchoGen Consortium, Gunnar Engström, Tõnu Esko, Stephan B. Felix, Chris Finan, Ian Ford, Mohsen Ghanbari, Sahar Ghasemi, Vilmantas Giedraitis, Franco Giulianini, John S Gottdiener, Stefan Gross, Daníel F Guðbjartsson, Rebecca Gutmann, Christopher M Haggerty, Pim van der Harst, Harry Hemingway, Craig L Hyde, Erik Ingelsson, J Wouter Jukema, Maryam Kavousi, Kay-Tee Khaw, Marcus E Kleber, Lars Køber, Andrea Koekemoer, Claudia Langenberg, Lars Lind, Cecilia M Lindgren, Barry London, Luca A Lotta, Ruth C. Lovering, Jian'an Luan, Patrik Magnusson, Anubha Mahajan, Kenneth B Margulies, Winfried März, Olle Melander, Ify R Mordi, Thomas Morgan, Andrew D Morris, Andrew P Morris, Alanna C. Morrison, Michael W Nagle, Christopher P Nelson, Alexander Niessner, Teemu Niiranen, Michelle L O'Donoghue, Anjali T Owens, Colin N A Palmer, Helen M Parry, Markus Perola, Eliana Portilla-Fernandez, Bruce M Psaty, Kenneth M Rice, Paul M Ridker, Simon P R Romaine, Jerome I Rotter, Perttu Salo, Veikko Salomaa, Jessica van Setten, Alaa A Shalaby, Diane T. Smelser, Nicholas L Smith, Steen Stender, David J. Stott, Per Svensson, Mari-Liis Tammesoo, Kent D Taylor, Maris Teder-Laving, Alexander Teumer, Guðmundur Thorgeirsson, Unnur Thorsteinsdottir, Christian Torp-Pedersen, Stella Trompet, Benoit Tyl, Andre G Uitterlinden, Abirami Veluchamy, Uwe Völker, Adriaan A Voors, Xiaosong Wang, Nicholas J Wareham, Dawn M Waterworth, Peter E. Weeke, Raul Weiss, Kerri L. Wiggins, Heming Xing, Laura M Yerges-Armstrong, Bing Yu, Faiez Zannad, Jing Hua Zhao, Nilesh J Samani, John J V McMurray, Jian Yang, Peter M. Visscher, Christopher Newton-Cheh, Anders Malarstig, Hilma Holm, Steven A. Lubitz, Naveed Sattar, Michael V Holmes, Thomas P. Cappola, F W Asselbergs, Aroon Dinesh Hingorani, Karoline Kuchenbaecker, Patrick T Ellinor, Chim C Lang, Kari Stefansson, J. Gustav Smith, Ramachandran S Vasan, Daniel I Swerdlow, R Thomas Lumbers

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.

198: Dynamic 3D chromosomal landscapes in acute leukemia
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Posted to bioRxiv 04 Aug 2019

Dynamic 3D chromosomal landscapes in acute leukemia
597 downloads cancer biology

Andreas Kloetgen, Palaniraja Thandapani, Panagiotis Ntziachristos, Yohana Ghebrechristos, Sofia Nomikou, Charalampos Lazaris, Xufeng Chen, Hai Hu, Sofia Bakogianni, Jingjing Wang, Yi Fu, Francesco Boccalatte, Hua Zhong, Elisabeth Paietta, Thomas Trimarchi, Yixing Zhu, Pieter van Vlierberghe, Giorgio G Inghirami, Timothee Lionnet, Iannis Aifantis, Aristotelis Tsirigos

Three-dimensional (3D) chromatin architectural changes can alter the integrity of topologically associated domains (TADs) and rewire specific enhancer-promoter interactions impacting gene expression. Recently, such alterations have been implicated in human disease, highlighting the need for a deeper understanding of their role. Here, we investigate the reorganization of chromatin architecture in T cell acute lymphoblastic leukemia (T-ALL) using primary human leukemia specimens and its dynamic responses to pharmacological agents. Systematic integration of matched in situ Hi-C, RNA-Seq and CTCF ChIP-Seq datasets revealed widespread changes in intra-TAD chromatin interactions and TAD boundary insulation in T-ALL. Our studies identify and focus on a TAD "fusion" event being associated with loss of CTCF-mediated insulation, enabling direct interactions between the MYC promoter and a distal super-enhancer. Moreover, our data show that small molecule inhibitors targeting either oncogenic signal transduction or epigenetic regulation reduce specific 3D interactions associated with transformation. Overall, our study highlights the impact, complexity and dynamic nature of 3D chromatin architecture in human acute leukemia.

199: Cholesterol and matrisome pathways dysregulated in human APOE ε4 glia
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Posted to bioRxiv 25 Jul 2019

Cholesterol and matrisome pathways dysregulated in human APOE ε4 glia
595 downloads neuroscience

Julia TCW, Shuang A Liang, Lu Qian, Nina H. Pipalia, Michael J Chao, Yang Shi, Sarah E Bertelsen, Manav Kapoor, Edoardo Marcora, Elizabeth Sikora, David M Holtzman, Frederick R. Maxfield, Bin Zhang, Minghui Wang, Wayne W. Poon, Alison A. Goate

Apolipoprotein E ( APOE ) ε4 is the strongest genetic risk factor for Alzheimer's disease (AD). Although its association with AD is well-established, the impact of APOE ε4 on human brain cell function remains unclear. Here we investigated the effects of APOE ε4 on several brain cell types derived from human induced pluripotent stem cells and human APOE targeted replacement mice. Gene set enrichment and pathway analyses of whole transcriptome profiles showed that APOE ε4 is associated with dysregulation of cholesterol homeostasis in human but not mouse astrocytes and microglia. Elevated matrisome signaling associated with chemotaxis, glial activation and lipid biosynthesis in APOE ε4 mixed neuron/astrocyte cultures parallels altered pathways uncovered in cell-type deconvoluted transcriptomic data from APOE ε4 glia and AD post-mortem brains. Experimental validation of the transcriptomic findings showed that isogenic APOE ε4 is associated with increased lysosomal cholesterol levels and decreased cholesterol efflux, demonstrating decoupled lipid metabolism. APOE ε4 glia also secrete higher levels of proinflammatory chemokines, cytokines and growth factors, indicative of glial activation. Thus, APOE ε4 induces human glia-specific dysregulation that may initiate AD risk.

200: Psychoactive plant- and mushroom-associated alkaloids from two behavior modifying cicada pathogens
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Posted to bioRxiv 24 Jul 2018

Psychoactive plant- and mushroom-associated alkaloids from two behavior modifying cicada pathogens
595 downloads ecology

Greg Boyce, Emile Gluck-Thaler, Jason C. Slot, Jason E Stajich, William J. Davis, Tim Y. James, John R. Cooley, Daniel G. Panaccione, Jorgen Eilenberg, Henrik H. De Fine Licht, Angie M. Macias, Matthew C. Berger, Kristen L. Wickert, Cameron M. Stauder, Ellie J. Spahr, Matthew D. Maust, Amy M. Metheny, Chris Simon, Gene Kritsky, Kathie T. Hodge, Richard A. Humber, Terry Gullion, Dylan P. G. Short, Teiya Kijimoto, Dan Mozgai, Nidia Arguedas, Matt T. Kasson

Entomopathogenic fungi routinely kill their hosts before releasing infectious spores, but select species keep insects alive while sporulating, which enhances dispersal. Transcriptomics and metabolomics studies of entomopathogens with post-mortem dissemination from their parasitized hosts have unraveled infection processes and host responses, yet mechanisms underlying active spore transmission by Entomophthoralean fungi in living insects remain elusive. Here we report the discovery, through metabolomics, of the plant-associated amphetamine, cathinone, in four Massospora cicadina-infected periodical cicada populations, and the mushroom-associated tryptamine, psilocybin, in annual cicadas infected with Massospora platypediae or Massospora levispora, which appear to represent a single fungal species. The absence of some fungal enzymes necessary for cathinone and psilocybin biosynthesis along with the inability to detect intermediate metabolites or gene orthologs are consistent with possibly novel biosynthesis pathways in Massospora. The neurogenic activities of these compounds suggest the extended phenotype of Massospora that modifies cicada behavior to maximize dissemination is chemically-induced.

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