bluuebunny/crossref_metadata_2025_split huggingface dataset:
Applications of community detection algorithms to large biological datasets
Authors: Kanter Itamar , Yaari Gur , Kalisky Tomer 
Published: February 2019

ABSTRACTRecent advances in data acquiring technologies in biology have led to major challenges in mining relevant information from large datasets. For example, single-cell RNA sequencing technologies are producing expression and sequence information from tens of thousands of cells in every single experiment. A common task in analyzing biological data is to cluster samples or features (e.g. genes) into groups sharing common characteristics. This is an NP-hard problem for which numerous heuristic algorithms have been developed. However, in many cases, the clusters created by these algorithms do not reflect biological reality. To overcome this, a Networks Based Clustering (NBC) approach was recently proposed, by which the samples or genes in the dataset are first mapped to a network and then community detection (CD) algorithms are used to identify clusters of nodes.Here, we created an open and flexible python-based toolkit for NBC that enables easy and accessible network construction and community detection. We then tested the applicability of NBC for identifying clusters of cells or genes from previously published large-scale single-cell and bulk RNA-seq datasets.We show that NBC can be used to accurately and efficiently analyze large-scale datasets of RNA sequencing experiments.
MEXCOWalk: Mutual Exclusion and Coverage Based Random Walk to Identify Cancer Modules
Authors: Ahmed Rafsan , Baali Ilyes , Erten Cesim , Hoxha Evis , Kazan Hilal 
Published: February 2019

AbstractMotivationGenomic analyses from large cancer cohorts have revealed the mutational heterogeneity problem which hinders the identification of driver genes based only on mutation profiles. One way to tackle this problem is to incorporate the fact that genes act together in functional modules. The connectivity knowledge present in existing protein-protein interaction networks together with mutation frequencies of genes and the mutual exclusivity of cancer mutations can be utilized to increase the accuracy of identifying cancer driver modules.ResultsWe present a novel edge-weighted random walk-based approach that incorporates connectivity information in the form of protein-protein interactions, mutual exclusion, and coverage to identify cancer driver modules. MEXCOWalk outperforms several state-of-the-art computational methods on TCGA pan-cancer data in terms of recovering known cancer genes, providing modules that are capable of classifying normal and tumor samples, and that are enriched for mutations in specific cancer types. Furthermore, the risk scores determined with output modules can stratify patients into low-risk and high-risk groups in multiple cancer types. MEXCOwalk identifies modules containing both well-known cancer genes and putative cancer genes that are rarely mutated in the pan-cancer data. The data, the source code, and useful scripts are available at:https://github.com/abu-compbio/MEXCOwalk.Contacthilal.kazan@antalya.edu.tr
MuStARD: Deep Learning for intra- and inter-species scanning of functional genomic patterns
Authors: Georgakilas Georgios K , Grioni Andrea , Liakos Konstantinos G , Malanikova Eliska , Plessas Fotis C , Alexiou Panagiotis 
Published: February 2019

AbstractRegions of the genome that produce different classes of functional elements also exhibit different patterns in their sequence, secondary structure, and evolutionary conservation. Deep Learning is a family of Machine Learning algorithms recently applied to a variety of pattern recognition problems. Here we present MuStARD (gitlab.com/RBP_Bioinformatics/mustard) a Deep Learning framework that can learn and combine sequence, structure, and conservation patterns in sets of functional regions, and accurately identify additional members of the given set over wide genomic areas. MuStARD is designed with general use in mind, and has sophisticated iterative fully-automated background selection capability. We demonstrate that MuStARD can be trained without changes on different classes of human small RNA loci (pre-microRNAs and snoRNAs) and accurately build prediction models for both, outperforming state of the art methods specifically designed for each specific class. Furthermore, we demonstrate the ability of MuStARD for inter-species identification of functional elements by predicting mouse small RNAs using human trained models. MuStARD is easy to deploy and extend to a variety of genomic classification questions.
Stratifying depression by neuroticism: revisiting a diagnostic tradition using GWAS data
Authors: Adams Mark J. , Howard David M. , Luciano Michelle , Clarke Toni-Kim , Davies Gail , Hill W. David ,   23andMe Research Team,   Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Smith Daniel , Deary Ian J. , Porteous David J. , McIntosh Andrew M. 
Published: February 2019

AbstractMajor depressive disorder and neuroticism share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression. We analysed two sets of summary statistics from genome-wide association studies of depression (from the Psychiatric Genomics Consortium and 23andMe) and compared them to GWAS of neuroticism (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only neuroticism, or with both. Second, we estimated partial genetic correlations to test whether the depression’s genetic link with other phenotypes was explained by shared overlap with neuroticism. We found evidence that most genetic variants associated with depression are likely to be shared with neuroticism. The overlapping common genetic variance of depression and neuroticism was negatively genetically correlated with cognitive function and positively genetically correlated with several psychiatric disorders. We found that the genetic contributions unique to depression, and not shared with neuroticism, were correlated with inflammation, cardiovascular disease, and sleep patterns. Our findings demonstrate that, while genetic risk factors for depression are largely shared with neuroticism, there are also non-neuroticism related features of depression that may be useful for further patient or phenotypic stratification.
ZEB1 insufficiency causes corneal endothelial cell state transition and altered cellular processing
Authors: Frausto Ricardo F. , Chung Doug D. , Boere Payton M. , Swamy Vinay S. , Duong Huong N.V. , Kao Liyo , Azimov Rustam , Zhang Wenlin , Carrigan Liam , Wong Davey , Morselli Marco , Zakharevich Marina , Hanser E. Maryam , Kassels Austin C. , Kurtz Ira , Pellegrini Matteo , Aldave Anthony J. 
Published: February 2019

ABSTRACTThe zinc finger e-box binding homeobox 1 (ZEB1) transcription factor is a master regulator of the epithelial to mesenchymal transition (EMT), and of the reverse mesenchymal to epithelial transition (MET) processes. ZEB1 plays an integral role in mediating cell state transitions during cell lineage specification, wound healing and disease. EMT/MET are characterized by distinct changes in molecular and cellular phenotype that are generally context-independent. Posterior polymorphous corneal dystrophy (PPCD), associated with ZEB1 insufficiency, provides a new biological context in which to understand and evaluate the classic EMT/MET paradigm. PPCD is characterized by a cadherin-switch and transition to an epithelial-like transcriptomic and cellular phenotype, which we study in a cell-based model of PPCD generated using CRISPR-Cas9-mediated ZEB1 knockout in corneal endothelial cells (CEnCs). Transcriptomic and functional studies support the hypothesis that CEnC undergo a MET-like transition in PPCD, termed endothelial to epithelial transition (EnET), and lead to the conclusion that EnET may be considered a corollary to the classic EMT/MET paradigm.
Loss of Shh signaling in the neocortex reveals heterogeneous cell recovery responses from distinct oligodendrocyte populations
Authors: Winkler Caitlin C , Franco Santos J 
Published: February 2019

AbstractThe majority of oligodendrocytes in the neocortex originate from neural progenitors that reside in the dorsal forebrain. We recently showed that Sonic Hedgehog (Shh) signaling in these dorsal progenitors is required to produce normal numbers of neocortical oligodendrocytes during embryonic development. Conditional deletion of the Shh signaling effector,Smo, in dorsal progenitors caused a dramatic reduction in oligodendrocyte numbers in the embryonic neocortex. In the current study, we show that the depleted oligodendrocyte lineage inSmoconditional mutants is able to recover to control numbers over time. This eventual recovery is achieved in part by expansion of the ventrally-derived wild-type lineage that normally makes up a minority of the total oligodendrocyte population. However, we find that the remaining dorsally-derived mutant cells also increase in numbers over time to contribute equally to the recovery of the total population. Additionally, we found that the ways in which the dorsal and ventral sources cooperate to achieve recovery is different for distinct subclasses of oligodendrocyte-lineage cells. Oligodendrocyte precursor cells (OPCs) in the neocortical white matter recover completely by expansion of the remaining dorsally-derivedSmomutant cells. On the other hand, mature oligodendrocytes in the white and gray matter recover through an equal contribution from dorsal mutant and ventral wild-type lineages. Interestingly, the only population that did not make a full recovery was OPCs in the gray matter. We find that gray matter OPCs are less proliferative inSmocKO mutants compared to controls, which may explain their inability to fully recover. These studies shed light on the nature of competition and cooperation between dorsal and ventral sources of oligodendrocytes in the developing neocortex. Furthermore, our data point towards differential use of Shh signaling in the development of distinct subclasses of the oligodendrocyte lineage.
Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues
Authors: Glaser Adam K. , Reder Nicholas P. , Chen Ye , Yin Chengbo , Wei Linpeng , Kang Soyoung , Barner Lindsey A. , Xie Weisi , McCarty Erin F. , Mao Chenyi , Halpern Aaron R. , Stoltzfus Caleb R. , Daniels Jonathan S. , Gerner Michael Y. , Nicovich Philip R. , Vaughan Joshua C. , True Lawrence D. , Liu Jonathan T.C. 
Published: February 2019

AbstractRecent advances in optical clearing and light-sheet microscopy have provided unprecedented access to structural and molecular information from intact tissues. However, current light-sheet microscopes have imposed constraints on the size, shape, number of specimens, and compatibility with various clearing protocols. Here we present a multi-immersion open-top light-sheet microscope that enables simple mounting of multiple specimens processed with a variety of protocols, which will facilitate wider adoption by preclinical researchers and clinical laboratories.One Sentence SummaryGlaseret al.describe a multi-immersion open-top light-sheet microscope that enables simple and high-throughput imaging of large numbers of preclinical and clinical specimens prepared with a variety of clearing protocols.
Adaptive efficient coding of correlated acoustic properties
Authors: Lu Kai , Liu Wanyi , Dutta Kelsey , Fritz Jonathan B. , Shamma Shihab A. 
Published: February 2019

AbstractNatural sounds such as vocalizations often have co-varying acoustic attributes where one acoustic feature can be predicted from another, resulting in redundancy in neural coding. It has been proposed that sensory systems are able to detect such covariation and adapt to reduce redundancy, leading to more efficient neural coding. Results of recent psychoacoustic studies suggest that, following passive exposure to sounds in which temporal and spectral attributes covaried in a correlated fashion, the auditory system adapts to efficiently encode the two co-varying dimensions as a single dimension, at the cost of lost sensitivity to the orthogonal dimension. Here we explore the neural basis of this psychophysical phenomenon by recording single-unit responses from primary auditory cortex (A1) in awake ferrets exposed passively to stimuli with two correlated attributes in the temporal and spectral domain similar to that utilized in the psychoacoustic experiments. We found that: (1) the signal-to-noise (SNR) ratio of spike rate coding of cortical responses driven by sounds with correlated attributes was reduced along the orthogonal dimension; while the SNR ratio remained intact along the exposure dimension; (2) Mutual information of spike temporal coding increased only along the exposure dimension; (3) correlation between neurons tuned to the two covarying attributes decreased after exposure; (4) these exposure effects still occurred if sounds were correlated along two acoustic dimensions, but varied randomly along a third dimension. These neurophysiological results are consistent with the Efficient Learning Hypothesis and may deepen our understanding of how the auditory system represents acoustic regularities and covariance.SignificanceIn the Efficient Coding (EC) hypothesis, proposed by Barlow in 1961, the neural code in sensory systems efficiently encodes natural stimuli by minimizing the number of spikes to transmit a sensory signal. Results of recent psychoacoustic studies are consistent with the EC hypothesis, showing that following passive exposure to stimuli with correlated attributes, the auditory system adapts so as to more efficiently encode the two co-varying dimensions as a single dimension. In the current neurophysiological experiments, using a similar stimulus design and experimental paradigm to the psychoacoustic studies of Stilp and colleagues (2010, 2011, 2012, 2016), we recorded responses from single neurons in the auditory cortex of the awake ferret, showing adaptive efficient neural coding of correlated acoustic properties.
Drug resistance evolution in HIV in the late 1990s: hard sweeps, soft sweeps, clonal interference and the accumulation of drug resistance mutations
Authors: Williams Kadie-Ann , Pennings Pleuni 
Published: February 2019

1AbstractThe goal of this paper is to provide examples of evolutionary dynamics of HIV within patients who are treated with antiretrovirals. We hope that the figures in this paper will be used in evolution and population genetics classes. We show a wide variety of patterns, specifically: soft sweeps, hard sweeps, softening sweeps and hardening sweeps, simultaneous sweeps, accumulation of mutations and clonal interference.
Decoding and recoding phase behavior of TDP43 reveals that phase separation is not required for splicing function
Authors: Schmidt Hermann Broder , Barreau Ariana , Rohatgi Rajat 
Published: February 2019

AbstractIntrinsically disordered regions (IDRs) often are fast evolving protein domains of low sequence complexity that can drive phase transitions and are commonly found in many proteins associated with neurodegenerative diseases, including the RNA processing factor TDP43. Yet, how phase separation contributes to the physiological functions of TDP43 in cells remains enigmatic. We combined systematic mutagenesis guided by evolutionary sequence analysis with a live-cell reporter assay of TDP43 phase dynamics to identify regularly-spaced hydrophobic motifs separated by flexible, hydrophilic segments in the IDR as a key determinant of TDP43 phase properties. This heuristic framework allowed us to customize the material properties of TDP43 condensates to determine effects on splicing function. Remarkably, mutants with increased or decreased phase dynamics, and even mutants that failed to phase separate, could mediate the splicing of a quantitative, single-cell splicing reporter and endogenous targets. We conclude that phase separation is not required for the function of TDP43 in splicing.
Multivariate climate change, the climate niche, and the Holocene history of eastern hemlock (Tsuga canadensis)
Authors: Shuman Bryan , Oswald W. Wyatt , Foster David R. 
Published: February 2019

AbstractForests in the eastern North America have changed progressively over the 11,700 years of the Holocene Epoch. To understand the dynamics involved, we focus on eastern hemlock (Tsuga canadensis), which shifted its distribution through time and, notably, exhibited a rapid range-wide decline at 5280±180 YBP. We consider how climate could have shaped this history by comparing fossil pollen records from eight New England sites with quantitative temperature and effective precipitation reconstructions and evaluating the realization of Tsuga’s climate niche through time. The comparisons indicate that multivariate climate change significantly influenced Tsuga abundance, including its abrupt decline and recovery. The comparisons show that the realized climate niche of Tsuga expressed today includes two important features that persisted through time. First, Tsuga pollen percentages reach their maxima (>30%) where July temperatures equal 18-20°C, but do so at two modes where annual precipitation equals either ∼1100 or ∼775 mm. The bimodality reflects Tsuga’s two geographic modes in the Great Lakes and Appalachian regions today, and explains past dynamics, such as short-lived peaks in Tsuga abundance associated with effective precipitation of ∼775 mm at ca. 10,000 years before CE 1950 (YBP). Second, the two peaks in Tsuga abundance follow negative correlations between temperature and precipitation such that the two modes shift toward high precipitation if temperatures are low (e.g., ∼1400 and ∼1000 mm at <18°C). Consequently, rapid cooling at 5200±100 YBP facilitated widespread Tsuga declines because cooling did not coincide with increased precipitation. Abundance declined as local climates departed from optimal temperature and precipitation combinations. Recovery only followed as effective precipitation increased by >150 mm over the past 4000 years. A regionally calibrated model of the relationship of Tsuga pollen percentages to temperature and precipitation explains 70-75% of the variance in the percentages at eight study sites. Iteratively excluding each site from the model shows that accurately representing the major features of the climate niche enables the model to predict the mid-Holocene decline and other past changes at the excluded site (site-level RMSE = 2.1-5.6%). Similar multivariate climate dynamics closely modulated the species’ abundance throughout the Holocene with no evidence of additional large-scale disturbances.
Extracellular Caspase-1 regulates hair follicle stem cell migration during wound-healing
Authors: Ghosh Subhasri , Hegde Akshay , Ananthan Akhil SHP , Kataria Sunny , Pincha Neha , Dutta Anupam , Dutta Abhik , Athreya Srilekha , Khedkar Sneha , Dey Rakesh , Bhosale Aishwarya , Jamora Colin 
Published: February 2019

ABSTRACTThe wound-healing process is a paradigm of the directed migration of various pools of stem cells from their niche to the site of injury where they replenish damaged cells. Two decades have elapsed since the observation that wounding activates multipotent hair follicle stem cells to infiltrate the epidermis, but the cues that coax these cells out of their niche remains unknown. Using an excisional wound and genetic mouse models of wound healing, we discovered that Caspase-1, a protein classically known as an integral component of the cytosolic inflammasome, is secreted and has a non-canonical role in the extracellular milieu. Through its Caspase Activation Recruitment Domain (CARD), Caspase-1 is sufficient to initiate chemotaxis of hair follicle stem cells into the epidermis. Uncovering this novel function of Caspase-1 also facilitates a deeper understanding of the mechanistic basis of the epithelial hyperplasia found to accompany numerous inflammatory skin diseases.
Reassessment of the basis of cell size control based on analysis of cell-to-cell variability
Authors: Facchetti Giuseppe , Knapp Benjamin , Chang Fred , Howard Martin 
Published: February 2019

ABSTRACTFundamental mechanisms governing cell size control and homeostasis are still poorly understood. The relationship between sizes at division and birth in single cells is used as a metric to categorize the basis of size homeostasis [1–3]. Cells dividing at a fixed size regardless of birth size (sizer) are expected to show a division-birth slope of 0, whereas cells dividing after growing for a fixed size increment (adder) have an expected slope of +1 [4]. These two theoretical values are, however, rarely experimentally observed. Here we investigate possible reasons for this discrepancy. Rod-shaped fission yeastSchizosaccharomyces pombecells divide at a fixed surface area [5, 6], and exhibit a division-birth slope of 0.23±0.04, significantly different from the sizer value of zero. To understand whether fission yeast uses a mix of sizer and adder control, or whether size sensing is simply imprecise, we developed a mathematical model of sizer control, including the relevant sources of variation. Our results supportpuresizer control and show that deviation from zero slope is exaggerated by measurement of an inappropriate geometrical quantity (e.g., length instead of area), combined with cell-to-cell radius variability. The model predicts that mutants with greater errors in size sensing or septum positioning paradoxically appear to behave as better sizers. Furthermore, accounting for cell width variability, we show that pure sizer control can in some circumstances reproduce the apparent adder behaviour observed inE. coli. These findings demonstrate that refined analysis of geometric variation can lead to new insights into cell size control.
The asymmetric chemical structures of two mating pheromones reflect their differential roles in conjugation of Schizosaccharomyces pombe
Authors: Seike Taisuke , Maekawa Hiromi , Nakamura Taro , Shimoda Chikashi 
Published: February 2019

AbstractIn the fission yeast Schizosaccharomyces pombe, the mating reaction is controlled by two mating pheromones, M-factor and P-factor, secreted by M- and P-type cells, respectively. M-factor is a C-terminally farnesylated lipid peptide, whereas P-factor is a simple peptide. To examine whether this chemical asymmetry in the two pheromones is essential for conjugation, we constructed a mating system in which either pheromone can stimulate both M- and P-cells, and examined whether the resulting autocrine strains can mate. Autocrine M-cells responding to M-factor successfully mated with P-factor-less P-cells, indicating that P-factor is not essential for conjugation; by contrast, autocrine P-cells responding to P-factor were unable to mate with M-factor-less M-cells. The sterility of the autocrine P-cells was completely recovered by expressing the M-factor receptor. These observations indicate that the different chemical characteristics of the two types of pheromone, a lipid and a simple peptide, are not essential; however, a lipid peptide is absolutely required for successful mating. Our findings allow us to propose a model of the differential roles of M-factor and P-factor in conjugation of S. pombe.Summary statementLipid pheromone peptides secreted locally from one cell may be concentrated at the fusion site with an opposite mating-type cell, which then polarizes to enable successful conjugation in S. pombe.