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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 57,294 bioRxiv papers from 263,837 authors.

Most downloaded bioRxiv papers, since beginning of last month

55,837 results found. For more information, click each entry to expand.

381: The murine transcriptome reveals global aging nodes with organ-specific phase and amplitude
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Posted to bioRxiv 07 Jun 2019

The murine transcriptome reveals global aging nodes with organ-specific phase and amplitude
364 downloads genomics

Nicholas Schaum, Benoit Lehallier, Oliver Hahn, Shayan Hosseinzadeh, Song E Lee, Rene Sit, Davis P Lee, Patricia Morán Losada, Macy E Zardeneta, Róbert Pálovics, Tobias Fehlmann, James Webber, Aaron McGeever, Hui Zhang, Daniela Berdnik, Weilun Tan, Alexander Zee, Michelle Tan, The Tabula Muris Consortium, Angela Pisco, Jim Karkanias, Norma F. Neff, Andreas Keller, Spyros Darmanis, Stephen R. Quake, Tony Wyss-Coray

Aging is the single greatest cause of disease and death worldwide, and so understanding the associated processes could vastly improve quality of life. While the field has identified major categories of aging damage such as altered intercellular communication, loss of proteostasis, and eroded mitochondrial function, these deleterious processes interact with extraordinary complexity within and between organs. Yet, a comprehensive analysis of aging dynamics organism-wide is lacking. Here we performed RNA-sequencing of 17 organs and plasma proteomics at 10 ages across the mouse lifespan. We uncover previously unknown linear and non-linear expression shifts during aging, which cluster in strikingly consistent trajectory groups with coherent biological functions, including extracellular matrix regulation, unfolded protein binding, mitochondrial function, and inflammatory and immune response. Remarkably, these gene sets are expressed similarly across tissues, differing merely in age of onset and amplitude. Especially pronounced is widespread immune cell activation, detectable first in white adipose depots in middle age. Single-cell RNA-sequencing confirms the accumulation of adipose T and B cells, including immunoglobulin J-expressing plasma cells, which also accrue concurrently across diverse organs. Finally, we show how expression shifts in distinct tissues are highly correlated with corresponding protein levels in plasma, thus potentially contributing to aging of the systemic circulation. Together, these data demonstrate a similar yet asynchronous inter- and intra-organ progression of aging, thereby providing a foundation to track systemic sources of declining health at old age.

382: Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores
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Posted to bioRxiv 31 Jul 2019

Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores
362 downloads genomics

Julian R Homburger, Cynthia L. Neben, Gilad Mishne, Alicia Y. Zhou, Sekar Kathiresan, Amit V Khera

Background: The inherited susceptibility of common, complex diseases may be caused by rare, 'monogenic' pathogenic variants or by the cumulative effect of numerous common, 'polygenic' variants. As such, comprehensive genome interpretation could involve two distinct genetic testing technologies -- high coverage next generation sequencing for known genes to detect pathogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). Here we assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs. Methods: First, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for three common diseases -- coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF) -- calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in 11,502 European individuals seeking genetic testing. Results: We found imputation accuracy r2 values of greater than 0.90 for all ten samples -- including those of African and Ashkenazi Jewish ancestry -- with lcWGS data at 0.5X. GPSs calculated using both lcWGS and genotyping array followed by imputation in 184 individuals were highly correlated for each of the three common diseases (r2 = 0.93 - 0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse ancestral backgrounds, including South Asian, East Asian, and Hispanic individuals, we found similar results with respect to imputation accuracy and GPS correlations. Finally, we calculated GPSs for CAD, BC, and AF using lcWGS in 11,502 European individuals, confirming odds ratios per standard deviation increment in GPSs ranging 1.28 to 1.59, consistent with previous studies. Conclusions: Here we show that lcWGS is an alternative approach to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.

383: 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
362 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.

384: Mathematical modeling with single-cell sequencing data
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Posted to bioRxiv 22 Jul 2019

Mathematical modeling with single-cell sequencing data
361 downloads cell biology

Heyrim Cho, Russell C. Rockne

Single-cell sequencing technologies have revolutionized molecular and cellular biology and stimulated the development of computational tools to analyze the data generated from these technology platforms. However, despite the recent explosion of computational analysis tools, relatively few mathematical models have been developed to utilize these data. Here we compare and contrast two approaches for building mathematical models of cell state-transitions with single-cell RNA-sequencing data with hematopoeisis as a model system; by solving partial differential equations on a graph representing discrete cell state relationships, and by solving the equations on a continuous cell state-space. We demonstrate how to calibrate model parameters from single or multiple time-point single-cell sequencing data, and examine the effects of data processing algorithms on the model calibration and predictions. As an application of our approach, we demonstrate how the calibrated models may be used to mathematically perturb normal hematopoeisis to simulate, predict, and study the emergence of novel cell types during the pathogenesis of acute myeloid leukemia. The mathematical modeling framework we present is general and can be applied to study cell state-transitions in any single-cell genome sequencing dataset.

385: Ultrafast immunostaining of organ-scale tissues for scalable proteomic phenotyping
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Posted to bioRxiv 05 Jun 2019

Ultrafast immunostaining of organ-scale tissues for scalable proteomic phenotyping
361 downloads bioengineering

Dae Hee Yun, Young-Gyun Park, Jae Hun Cho, Lee Kamentsky, Nicholas B Evans, Alexandre Albanese, Katherine Xie, Justin Swaney, Chang Ho Sohn, Yuxuan Tian, Qiangge Zhang, Gabi Drummond, Webster Guan, Nicholas DiNapoli, Heejin Choi, Hae-Yoon Jung, Luzdary Ruelas, Guoping Feng, Kwanghun Chung

Studying the function and dysfunction of complex biological systems necessitates comprehensive understanding of individual cells. Advancements in three-dimensional (3D) tissue processing and imaging modalities have enabled rapid visualization and phenotyping of cells in their spatial context. However, system-wide interrogation of individual cells within large intact tissue remains challenging, low throughput, and error-prone owing to the lack of robust labeling technologies. Here we introduce a rapid, versatile, and scalable method, eFLASH, that enables complete and uniform labeling of organ-scale tissue within one day. eFLASH dynamically modulates chemical transport and reaction kinetics to establish system-wide uniform labeling conditions throughout the day-long labeling period. This unique approach enables the same protocol to be compatible with a wide range of tissue types and probes, enabling combinatorial molecular phenotyping across different organs and species. We applied eFLASH to generate quantitative maps of various cell types in mouse brains. We also demonstrated multidimensional cell profiling in a marmoset brain block. We envision that eFLASH will spur holistic phenotyping of emerging animal models and disease models to help assess their functions and dysfunctions.

386: Widespread associations between grey matter structure and the human phenome
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Posted to bioRxiv 09 Jul 2019

Widespread associations between grey matter structure and the human phenome
360 downloads neuroscience

Baptiste Couvy-Duchesne, Lachlan T. Strike, Futao Zhang, Yan Holtz, Zhili Zheng, Kathryn E. Kemper, Loic Yengo, Olivier Colliot, Margaret J Wright, Naomi R. Wray, Jian Yang, Peter M. Visscher

The recent availability of large-scale neuroimaging cohorts (here the UK Biobank [UKB] and the Human Connectome Project [HCP]) facilitates deeper characterisation of the relationship between phenotypic and brain architecture variation in humans. We tested the association between 654,386 vertex-wise measures of cortical and subcortical morphology (from T1w and T2w MRI images) and behavioural, cognitive, psychiatric and lifestyle data. We found a significant association of grey-matter structure with 58 out of 167 UKB phenotypes spanning substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains (UKB discovery sample: N=9,888). Twenty-three of the 58 associations replicated (UKB replication sample: N=4,561; HCP, N=1,110). In addition, differences in body size (height, weight, BMI, waist and hip circumference, body fat percentage) could account for a substantial proportion of the association, providing possible insight into previous MRI case-control studies for psychiatric disorders where case status is associated with body mass index. Using the same linear mixed model, we showed that most of the associated characteristics (e.g. age, sex, body size, diabetes, being a twin, maternal smoking, body size) could be significantly predicted using all the brain measurements in out-of-sample prediction. Finally, we demonstrated other applications of our approach including a Region Of Interest (ROI) analysis that retain the vertex-wise complexity and ranking of the information contained across MRI processing options.

387: Photoswitchable microtubule inhibitors enabling robust, GFP-orthogonal optical control over the tubulin cytoskeleton
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Posted to bioRxiv 28 Jul 2019

Photoswitchable microtubule inhibitors enabling robust, GFP-orthogonal optical control over the tubulin cytoskeleton
360 downloads cell biology

Li Gao, Yvonne Kraus, Maximilian Wranik, Tobias Weinert, Stefanie D. Pritzl, Joyce C.M. Meiring, Rebekkah Bingham, Natacha Olieric, Anna Akhmanova, Theobald Lohmüller, Michel O. Steinmetz, Oliver Thorn-Seshold

Here we present GFP-orthogonal optically controlled reagents for reliable and repetitive in cellulo modulation of microtubule dynamics and its dependent processes. Optically controlled reagents ('photopharmaceuticals') have developed into powerful tools for high-spatiotemporal-precision control of endogenous biology, with numerous applications in neuroscience, embryology, and cytoskeleton research. However, the restricted chemical domain of photopharmaceutical scaffolds has constrained their properties and range of applications. Styrylbenzothiazoles are an as-yet unexplored scaffold for photopharmaceuticals, which we now rationally design to feature potent photocontrol, switching microtubule cytoskeleton function off and on according to illumination conditions. We show more broadly that this scaffold is exceptionally chemically and biochemically robust as well as substituent-tolerant, and offers particular advantages for intracellular biology through a range of desirable photopharmaceutical and drug-like properties not accessible to the current classes of photoswitches. We expect that these reagents will find powerful applications enabling robust, high precision, optically controlled cell biological experimentation in cytoskeleton research and beyond.

388: Slide-seq: A Scalable Technology for Measuring Genome-Wide Expression at High Spatial Resolution
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Posted to bioRxiv 28 Feb 2019

Slide-seq: A Scalable Technology for Measuring Genome-Wide Expression at High Spatial Resolution
359 downloads genomics

Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, Carly A Martin, Evan Murray, Charles R Vanderburg, Joshua Welch, Linlin M Chen, Fei Chen, Evan Z Macosko

The spatial organization of cells in tissue has a profound influence on their function, yet a high-throughput, genome-wide readout of gene expression with cellular resolution is lacking. Here, we introduce Slide-seq, a highly scalable method that enables facile generation of large volumes of unbiased spatial transcriptomes with 10 micron spatial resolution, comparable to the size of individual cells. In Slide-seq, RNA is transferred from freshly frozen tissue sections onto a surface covered in DNA-barcoded beads with known positions, allowing the spatial locations of the RNA to be inferred by sequencing. To demonstrate Slide-seq's utility, we localized cell types identified by large-scale scRNA-seq datasets within the cerebellum and hippocampus. We next systematically characterized spatial gene expression patterns in the Purkinje layer of mouse cerebellum, identifying new axes of variation across Purkinje cell compartments. Finally, we used Slide-seq to define the temporal evolution of cell-type-specific responses in a mouse model of traumatic brain injury. Slide-seq will accelerate biological discovery by enabling routine, high-resolution spatial mapping of gene expression.

389: Fast, sensitive, and accurate integration of single cell data with Harmony
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Posted to bioRxiv 04 Nov 2018

Fast, sensitive, and accurate integration of single cell data with Harmony
358 downloads bioinformatics

Ilya Korsunsky, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-Ru Loh, Soumya Raychaudhuri

The rapidly emerging diversity of single cell RNAseq datasets allows us to characterize the transcriptional behavior of cell types across a wide variety of biological and clinical conditions. With this comprehensive breadth comes a major analytical challenge. The same cell type across tissues, from different donors, or in different disease states, may appear to express different genes. A joint analysis of multiple datasets requires the integration of cells across diverse conditions. This is particularly challenging when datasets are assayed with different technologies in which real biological differences are interspersed with technical differences. We present Harmony, an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Unlike available single-cell integration methods, Harmony can simultaneously account for multiple experimental and biological factors. We develop objective metrics to evaluate the quality of data integration. In four separate analyses, we demonstrate the superior performance of Harmony to four single-cell-specific integration algorithms. Moreover, we show that Harmony requires dramatically fewer computational resources. It is the only available algorithm that makes the integration of ~1 million cells feasible on a personal computer. We demonstrate that Harmony identifies both broad populations and fine-grained subpopulations of PBMCs from datasets with large experimental differences. In a meta-analysis of 14,746 cells from 5 studies of human pancreatic islet cells, Harmony accounts for variation among technologies and donors to successfully align several rare subpopulations. In the resulting integrated embedding, we identify a previously unidentified population of potentially dysfunctional alpha islet cells, enriched for genes active in the Endoplasmic Reticulum (ER) stress response. The abundance of these alpha cells correlates across donors with the proportion of dysfunctional beta cells also enriched in ER stress response genes. Harmony is a fast and flexible general purpose integration algorithm that enables the identification of shared fine-grained subpopulations across a variety of experimental and biological conditions.

390: Suite2p: beyond 10,000 neurons with standard two-photon microscopy
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Posted to bioRxiv 30 Jun 2016

Suite2p: beyond 10,000 neurons with standard two-photon microscopy
358 downloads neuroscience

Marius Pachitariu, Carsen Stringer, Mario Dipoppa, Sylvia Schröder, L. Federico Rossi, Henry Dalgleish, Matteo Carandini, Kenneth D. Harris

Two-photon microscopy of calcium-dependent sensors has enabled unprecedented recordings from vast populations of neurons. While the sensors and microscopes have matured over several generations of development, computational methods to process the resulting movies remain inefficient and can give results that are hard to interpret. Here we introduce Suite2p: a fast, accurate and complete pipeline that registers raw movies, detects active cells, extracts their calcium traces and infers their spike times. Suite2p runs on standard workstations, operates faster than real time, and recovers ~2 times more cells than the previous state-of-the-art method. Its low computational load allows routine detection of ~10,000 cells simultaneously with standard two-photon resonant-scanning microscopes. Recordings at this scale promise to reveal the fine structure of activity in large populations of neurons or large populations of subcellular structures such as synaptic boutons.

391: Prospective, brain-wide labeling of neuronal subclasses with enhancer-driven AAVs
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Posted to bioRxiv 20 Jan 2019

Prospective, brain-wide labeling of neuronal subclasses with enhancer-driven AAVs
358 downloads neuroscience

Lucas Graybuck, Adriana Sedeño-Cortés, Thuc Nghi Nguyen, Miranda Walker, Eric Szelenyi, Garreck Lenz, La'Akea Sieverts, Tae Kyung Kim, Emma Garren, Brian Kalmbach, Shenqin Yao, Marty Mortrud, John Mich, Jeff Goldy, Kimberly A Smith, Nick Dee, Zizhen Yao, Ali Cetin, Boaz P Levi, Ed Lein, Jonathan Ting, Hongkui Zeng, Tanya Daigle, Bosiljka Tasic

Labeling and perturbation of specific cell types in multicellular systems has transformed our ability to understand them. The rapid pace of cell type identification by new single-cell analysis methods has not been met with efficient access to these newly discovered types. To enable access to specific neural populations in the mouse cortex, we have collected single cell chromatin accessibility data from select cell types. We clustered the single cell data and mapped them to single cell transcriptomics to identify highly specific enhancers for cell subclasses. These enhancers, when cloned into AAVs and delivered to the brain by retro orbital injections, transgene expression in specific cell subclasses throughout the mouse brain. This approach will enable functional investigation of cell types in the mouse cortex and beyond.

392: State-specific gating of salient cues by midbrain dopaminergic input to basal amygdala
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Posted to bioRxiv 02 Jul 2019

State-specific gating of salient cues by midbrain dopaminergic input to basal amygdala
357 downloads neuroscience

Andrew Lutas, Hakan Kucukdereli, Osama Alturkistani, Crista Carty, Arthur U. Sugden, Kayla Fernando, Veronica Diaz, Vanessa Flores-Maldonado, Mark L. Andermann

Basal amygdala (BA) neurons guide associative learning via acquisition of responses to stimuli that predict salient appetitive or aversive outcomes. We examined the learning- and state-dependent dynamics of BA neurons and ventral tegmental area dopamine axons that innervate BA (VTADA→BA) using two-photon imaging and photometry in behaving mice. BA neurons did not respond to arbitrary visual stimuli, but acquired responses to stimuli that predicted either rewards or punishments. Most VTADA→BA axons were activated by both rewards and punishments, and acquired responses to cues predicting these outcomes during learning. Responses to cues predicting food rewards in VTADA→BA axons and BA neurons in hungry mice were strongly attenuated following satiation, while responses to cues predicting unavoidable punishments persisted or increased. Therefore, VTADA→BA axons may provide a reinforcement signal of motivational salience that invigorates adaptive behaviors by promoting learned responses to appetitive or aversive cues in distinct, intermingled sets of BA excitatory neurons.

393: Directed evolution of TurboID for efficient proximity labeling in living cells and organisms
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Posted to bioRxiv 02 Oct 2017

Directed evolution of TurboID for efficient proximity labeling in living cells and organisms
357 downloads bioengineering

Tess C Branon, Justin A Bosch, Ariana D Sanchez, Namrata D Udeshi, Tanya Svinkina, Steven A. Carr, Jessica L Feldman, Norbert Perrimon, Alice Y. Ting

Protein interaction networks and protein compartmentation underlie every signaling process and regulatory mechanism in cells. Recently, proximity labeling (PL) has emerged as a new approach to study the spatial and interaction characteristics of proteins in living cells. However, the two enzymes commonly used for PL come with tradeoffs: BioID is slow, requiring tagging times of 18-24 hours, while APEX peroxidase uses substrates that have limited cell permeability and high toxicity. To address these problems, we used yeast display-based directed evolution to engineer two mutants of biotin ligase, TurboID and miniTurbo, with much greater catalytic efficiency than BioID, and the ability to carry out PL in cells in much shorter time windows (as little as 10 minutes) with non-toxic and easily deliverable biotin. In addition to shortening PL time by 100-fold and increasing PL yield in cell culture, TurboID enabled biotin-based PL in new settings, including yeast, Drosophila, and C. elegans.

394: Assembly methods for nanopore-based metagenomic sequencing: a comparative study
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Posted to bioRxiv 01 Aug 2019

Assembly methods for nanopore-based metagenomic sequencing: a comparative study
357 downloads bioinformatics

Adriel Latorre-Perez, Pascual Villalba-Bermell, Javier Pascual, Manuel Porcar, Cristina Vilanova

Background: Metagenomic sequencing has lead to the recovery of previously unexplored microbial genomes. In this sense, short-reads sequencing platforms often result in highly fragmented metagenomes, thus complicating downstream analyses. Third generation sequencing technologies, such as MinION, could lead to more contiguous assemblies due to their ability to generate long reads. Nevertheless, there is a lack of studies evaluating the suitability of the available assembly tools for this new type of data. Findings: We benchmarked the ability of different short-reads and long-reads tools to assembly two different commercially available mock communities, and observed remarkable differences in the resulting assemblies depending on the software of choice. Short-reads metagenomic assemblers proved unsuitable for MinION data. Among the long-reads assemblers tested, Flye and Canu were the only ones performing well in all the datasets. These tools were able to retrieve complete individual genomes directly from the metagenome, and assembled a bacterial genome in only two contigs in the best scenario. Despite the intrinsic high error of long-reads technologies, Canu and Flye lead to high accurate assemblies (~99.4-99.8 % of accuracy). However, errors still had an impact on the prediction of biosynthetic gene clusters. Conclusions: MinION metagenomic sequencing data proved sufficient for assembling low-complex microbial communities, leading to the recovery of highly complete and contiguous individual genomes. This work is the first systematic evaluation of the performance of different assembly tools on MinION data, and may help other researchers willing to use this technology to choose the most appropriate software depending on their goals. Future work is still needed in order to assess the performance of Oxford Nanopore MinION data on more complex microbiomes.

395: Variable prediction accuracy of polygenic scores within an ancestry group
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Posted to bioRxiv 07 May 2019

Variable prediction accuracy of polygenic scores within an ancestry group
357 downloads genetics

Hakhamanesh Mostafavi, Arbel Harpak, Dalton Conley, Jonathan K Pritchard, Molly Przeworski

Fields as diverse as human genetics and sociology are increasingly using polygenic scores based on genome-wide association studies (GWAS) for phenotypic prediction. However, recent work has shown that polygenic scores have limited portability across groups of different genetic ancestries, restricting the contexts in which they can be used reliably and potentially creating serious inequities in future clinical applications. Using the UK Biobank data, we demonstrate that even within a single ancestry group, the prediction accuracy of polygenic scores depends on characteristics such as the age or sex composition of the individuals in which the GWAS and the prediction were conducted, and on the GWAS study design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.

396: Insights into protein structural, physicochemical, and functional consequences of missense variants in 1,330 disease-associated human genes
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Posted to bioRxiv 04 Jul 2019

Insights into protein structural, physicochemical, and functional consequences of missense variants in 1,330 disease-associated human genes
356 downloads genetics

Sumaiya Iqbal, Jakob B Jespersen, Eduardo Perez-Palma, Patrick May, David Hoksza, Henrike O. Heyne, Shehab S Ahmed, Zaara T Rifat, M. Sohel Rahman, Kasper Lage, Aarno Palotie, Jeffrey Cottrell, Florence F Wagner, Mark J. Daly, Arthur J Campbell, Dennis Lal

Inference of the structural and functional consequences of amino acid-altering missense variants is challenging and not yet scalable. Clinical and research applications of the colossal number of identified missense variants is thus limited. Here we describe the aggregation and analysis of large-scale genomic variation and structural biology data for 1,330 disease-associated genes. Comparing the burden of 40 structural, physicochemical, and functional protein features of altered amino acids with 3-dimensional coordinates, we found 18 and 14 features that are associated with pathogenic and population missense variants, respectively. Separate analyses of variants from 24 protein functional classes revealed novel function-dependent vulnerable features. We then devised a quantitative spectrum, identifying variants with higher pathogenic variant-associated features. Finally, we developed a web resource (MISCAST; http://miscast.broadinstitute.org/) for interactive analysis of variants on linear and tertiary protein structures. The biological impact of missense variants available through the webtool will assist researchers in hypothesizing variant pathogenicity and disease trajectories.

397: Defining the emergence of myeloid-derived suppressor cells in breast cancer using single-cell transcriptomics
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Posted to bioRxiv 15 Jul 2019

Defining the emergence of myeloid-derived suppressor cells in breast cancer using single-cell transcriptomics
356 downloads cancer biology

Hamad Alshetaiwi, Nicholas Pervolarakis, Laura Lynn McIntyre, Dennis Ma, Quy Nguyen, Jan Akara Rath, Kevin Nee, Grace Hernandez, Katrina Evans, Leona Torosian, Anushka Silva, Craig Walsh, Kai Kessenbrock

Myeloid-derived suppressor cells (MDSCs) are innate immune cells that acquire the capacity to suppress adaptive immune responses during cancer. It remains elusive how MDSCs differ from their normal myeloid counterparts, which limits our ability to specifically detect and therapeutically target MDSCs during cancer. Here, we used single-cell RNAseq to compare MDSC-containing splenic myeloid cells from breast tumor-bearing mice to wildtype controls. Our computational analysis of 14,646 single-cell transcriptomes reveals that MDSCs emerge through a previously unrealized aberrant neutrophil maturation trajectory in the spleen giving rise to a unique chemokine-responsive, immunosuppressive cell state that strongly differs from normal myeloid cells. We establish the first MDSC-specific gene signature and identify novel surface markers for improved detection and enrichment of MDSCs in murine and human samples. Our study provides the first single-cell transcriptional map defining the development of MDSCs, which will ultimately enable us to specifically target these cells in cancer patients.

398: A better way to define and describe Morlet wavelets for time-frequency analysis
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Posted to bioRxiv 21 Aug 2018

A better way to define and describe Morlet wavelets for time-frequency analysis
355 downloads neuroscience

Michael X Cohen

Morlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal precision and frequency precision. It is typically defined as the "number of cycles," but this parameter is opaque, and often leads to uncertainty and suboptimal analysis choices, as well as being difficult to interpret and evaluate. The purpose of this paper is to present alternative formulations of Morlet wavelets in time and in frequency that allow parameterizing the wavelets directly in terms of the desired temporal and spectral smoothing (as full-width at half-maximum). This formulation provides clarity on an important data analysis parameter, and should facilitate proper analyses, reporting, and interpretation of results. MATLAB code is provided.

399: A lineage-resolved molecular atlas of C. elegans embryogenesis at single cell resolution
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Posted to bioRxiv 01 Mar 2019

A lineage-resolved molecular atlas of C. elegans embryogenesis at single cell resolution
355 downloads genomics

Jonathan S Packer, Qin Zhu, Chau Huynh, Priya Sivaramakrishnan, Elicia Preston, Hannah Dueck, Derek Stefanik, Kai Tan, Cole Trapnell, Junhyong Kim, Robert H. Waterston, John I. Murray

C. elegans is an animal with few cells, but a striking diversity of cell types. Here, we characterize the molecular basis for their specification by profiling the transcriptomes of 84,625 single embryonic cells. We identify 284 terminal and pre-terminal cell types, mapping most single cell transcriptomes to their exact position in the invariant C. elegans lineage. We use these annotations to perform the first quantitative analysis of the relationship between lineage and the transcriptome for a whole organism. We find that a strong lineage-transcriptome correlation in the early embryo breaks down in the final two cell divisions as cells adopt their terminal fates and that most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state. Users can explore our data with a graphical application VisCello.

400: Monosomes actively translate synaptic mRNAs in neuronal processes
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Posted to bioRxiv 29 Jun 2019

Monosomes actively translate synaptic mRNAs in neuronal processes
354 downloads neuroscience

Anne Biever, Caspar Glock, Georgi Tushev, Elena Ciirdaeva, Julian D. Langer, Erin M. Schuman

In order to deal with their huge volume and complex morphology, neurons localize mRNAs and ribosomes near synapses to produce proteins locally. A relative paucity of polyribosomes (considered the active sites of translation) detected in electron micrographs of neuronal processes (axons and dendrites), however, has suggested a rather limited capacity for local protein synthesis. Polysome profiling together with ribosome footprinting of microdissected synaptic regions revealed that a surprisingly high number of dendritic and/or axonal transcripts were predominantly associated with monosomes (single ribosomes). Contrary to prevailing views, the neuronal monosomes were in the process of active protein synthesis (e.g. they exhibited elongation). Most mRNAs showed a similar translational status in both compartments, but some transcripts exhibited differential ribosome occupancy in the somata and neuropil. Strikingly, monosome-preferred transcripts often encoded high-abundance synaptic proteins. This work suggests a significant contribution of monosome translation to the maintenance of the local neuronal proteome. This mode of translation can presumably solve some of restricted space issues (given the large size of polysomes) and also increase the diversity of proteins made from a limited number of ribosomes available in dendrites and axons.

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