bluuebunny/crossref_metadata_2025_split huggingface dataset:
A map of direct TF-DNA interactions in the human genome
Authors: Gheorghe Marius , Sandve Geir Kjetil , Khan Aziz , Chèneby Jeanne , Ballester Benoit , Mathelier Anthony 
Published: August 2018

ABSTRACTChromatin immunoprecipitation followed by sequencing (ChIP-seq) is the most popular assay to identify genomic regions, called ChIP-seq peaks, that are bound in vivo by transcription factors (TFs). These regions are derived from direct TF-DNA interactions, indirect binding of the TF to the DNA (through a co-binding partner), nonspecific binding to the DNA, and noise/bias/artifacts. Delineating the bona fide direct TF-DNA interactions within the ChIP-seq peaks remains challenging. We developed a dedicated software, ChIP-eat, that combines computational TF binding models and ChIP-seq peaks to automatically predict direct TF-DNA interactions. Our work culminated with predicted interactions covering >4% of the human genome, obtained by uniformly processing 1,983 ChIP-seq peak data sets from the ReMap database for 232 unique TFs. The predictions were a posteriori assessed using protein binding microarray and ChIP-exo data, and were predominantly found in high quality ChIP-seq peaks. The set of predicted direct TF-DNA interactions suggested that high-occupancy target regions are likely not derived from direct binding of the TFs to the DNA. Our predictions derived co-binding TFs supported by protein-protein interaction data and defined cis-regulatory modules enriched for disease- and trait-associated SNPs. Finally, we provide this collection of direct TF-DNA interactions and cis-regulatory modules in the human genome through the UniBind web-interface (http://unibind.uio.no).
Evolutionary history of Alzheimer Disease causing protein family Presenilins with pathological implications
Authors: Khan Ammad Aslam , Mirza Bushra , Raja Hashim Ali 
Published: August 2018

AbstractPresenilin proteins are type II transmembrane proteins. They make the catalytic component of Gamma secretase, a multiportion transmembrane protease. Amyloid protein, Notch and beta catenin are among more than 90 substrates of Presenilins. Mutations in Presenilins lead to defects in proteolytic cleavage of its substrate resulting in some of the most devastating pathological conditions including Alzheimer disease (AD), developmental disorders and cancer. In addition to catalytic roles, Presenilin protein is also shown to be involved in many non-catalytic roles i.e. calcium homeostasis, regulation of autophagy and protein trafficking etc. These proteolytic proteins are highly conserved, present in almost all the major eukaryotic groups. Studies on wide variety of organisms ranging from human to unicellular dictyostelium have shown the important catalytic and non-catalytic roles of Presenilins. In the current research project, we aimed to elucidate the phylogenetic history of Presenilins. We showed that Presenilins are the most ancient of the Gamma secretase proteins and might have their origin in last common eukaryotic ancestor (LCEA). We also demonstrated that these proteins have been evolving under strong purifying selection. Through evolutionary trace analysis, we showed that Presenilin protein sites which undergoes mutations in Familial Alzheimer Disease are highly conserved in metazoans. Finally, we discussed the evolutionary, physiological and pathological implication of our findings and proposed that evolutionary profile of Presenilins supports the loss of function hypothesis of AD pathogenesis.
RT States: systematic annotation of the human genome using cell type-specific replication timing programs
Authors: Poulet Axel , Li Ben , Dubos Tristan , Rivera-Mulia Juan Carlos , Gilbert David M. , Qin Zhaohui S 
Published: August 2018

ABSTRACTThe replication timing (RT) program has been linked to many key biological processes including cell fate commitment, 3D chromatin organization and transcription regulation. Significant technology progress now allows to characterize the RT program in the entire human genome in a high-throughput and high-resolution fashion. These experiments suggest that RT changes dynamically during development in coordination with gene activity. Since RT is such a fundamental biological process, we believe that an effective quantitative profile of the local RT program from a diverse set of cell types in various developmental stages and lineages can provide crucial biological insights for a genomic locus. In the present study, we explored recurrent and spatially coherent combinatorial profiles from 42 RT programs collected from multiple lineages at diverse differentiation states. We found that a Hidden Markov Model with 15 hidden states provide a good model to describe these genome-wide RT profiling data. Each of the hidden state represents a unique combination of RT profiles across different cell types which we refer to as “RT states”. To understand the biological properties of these RT states, we inspected their relationship with chromatin states, gene expression, functional annotation and 3D chromosomal organization. We found that the newly defined RT states possess interesting genome-wide functional properties that add complementary information to the existing annotation of the human genome.AUTHOR SUMMARYThe replication timing (RT) program is an important cellular mechanism and has been linked to many key biological processes including cell fate commitment, 3D chromatin organization and transcription regulation. Significant technology progress now allows us to characterize the RT program in the entire human genome. Results from these experiments suggest that RT changes dynamically across different developmental stages. Since RT is such a fundamental biological process, we believe that the local RT program from a diverse set of cell types in various developmental stages can provide crucial biological insights for a genomic locus. In the present study, we explored combinatorial profiles from 42 RT programs collected from multiple lineages at diverse differentiation states. We developed a statistical model consist of 15 “RT states” to describe these genome-wide RT profiling data. To understand the biological properties of these RT states, we inspected the relationship between RT states and other types of functional annotations of the genome. We found that the newly defined RT states possess interesting genome-wide functional properties that add complementary information to the existing annotation of the human genome.
Interrogating Mutant Allele Expression via Customized Reference Genomes to Define Influential Cancer Mutations
Authors: Grant Adam , Vail Paris , Padi Megha , Witkiewicz Agnieszka K. , Knudsen Erik S. 
Published: August 2018

AbstractGenetic alterations are essential for cancer initiation and progression. However, differentiating mutations that drive the tumor phenotype from mutations that do not affect tumor fitness remains a fundamental challenge in cancer biology. To better understand the impact of a given mutation within cancer, RNA-sequencing data was used to categorize mutations based on their allelic expression. For this purpose, we developed the MAXX (Mutation Allelic Expression Extractor) software, which is highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions. Results from MAXX demonstrated that mutations can be separated into three groups based on their expression of the mutant allele, lack of expression from both alleles, or expression of only the wild-type allele. By taking into consideration the allelic expression patterns of genes that are mutated in PDAC, it was possible to increase the sensitivity of widely used driver mutation detection methods, as well as identify subtypes that have prognostic significance and are associated with sensitivity to select classes of therapeutic agents in cell culture. Thus, differentiating mutations based on their mutant allele expression via MAXX represents a means to parse somatic variants in tumor genomes, helping to elucidate of a gene’s respective role in cancer.
Decomposing cell identity for transfer learning across cellular measurements, platforms, tissues, and species
Authors: Stein-O’Brien Genevieve L. , Clark Brian S. , Sherman Thomas , Zibetti Cristina , Hu Qiwen , Sealfon Rachel , Liu Sheng , Qian Jiang , Colantuoni Carlo , Blackshaw Seth , Goff Loyal A. , Fertig Elana J. 
Published: August 2018

ABSTRACTNew approaches are urgently needed to glean biological insights from the vast amounts of single cell RNA sequencing (scRNA-Seq) data now being generated. To this end, we propose that cell identity should map to a reduced set of factors which will describe both exclusive and shared biology of individual cells, and that the dimensions which contain these factors reflect biologically meaningful relationships across different platforms, tissues and species. To find a robust set of dependent factors in large-scale scRNA- Seq data, we developed a Bayesian non-negative matrix factorization (NMF) algorithm, scCoGAPS. Application of scCoGAPS to scRNA-Seq data obtained over the course of mouse retinal development identified gene expression signatures for factors associated with specific cell types and continuous biological processes. To test whether these signatures are shared across diverse cellular contexts, we developed projectR to map biologically disparate datasets into the factors learned by scCoGAPS. Because projecting these dimensions preserve relative distances between samples, biologically meaningful relationships/factors will stratify new data consistent with their underlying processes, allowing labels or information from one dataset to be used for annotation of the other—a machine learning concept called transfer learning. Using projectR, data from multiple datasets was used to annotate latent spaces and reveal novel parallels between developmental programs in other tissues, species and cellular assays. Using this approach we are able to transfer cell type and state designations across datasets to rapidly annotate cellular features in a new dataset without a priori knowledge of their type, identify a species-specific signature of microglial cells, and identify a previously undescribed subpopulation of neurosecretory cells within the lung. Together, these algorithms define biologically meaningful dimensions of cellular identity, state, and trajectories that persist across technologies, molecular features, and species.GRAPHICAL ABSTRACT
Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies
Authors: Chen Han , Huffman Jennifer E. , Brody Jennifer A. , Wang Chaolong , Lee Seunggeun , Li Zilin , Gogarten Stephanie M. , Sofer Tamar , Bielak Lawrence F. , Bis Joshua C. , Blangero John , Bowler Russell P. , Cade Brian E. , Cho Michael H. , Correa Adolfo , Curran Joanne E. , Vries Paul S. de , Glahn David C. , Guo Xiuqing , Johnson Andrew D. , Kardia Sharon , Kooperberg Charles , Lewis Joshua P. , Liu Xiaoming , Mathias Rasika A. , Mitchell Braxton D. , O’Connell Jeffrey R. , Peyser Patricia A. , Post Wendy S. , Reiner Alex P. , Rich Stephen S. , Rotter Jerome I. , Silverman Edwin K. , Smith Jennifer A. , Vasan Ramachandran S. , Wilson James G. , Yanek Lisa R. ,   NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, Redline Susan , Smith Nicholas L. , Boerwinkle Eric , Borecki Ingrid B. , Cupples L. Adrienne , Laurie Cathy C. , Morrison Alanna C. , Rice Kenneth M. , Lin Xihong 
Published: August 2018

ABSTRACTWith advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.
Butyrivibrio hungateiMB2003 competes effectively for soluble sugars released byButyrivibrio proteoclasticusB316Tfrom growth on xylan or pectin
Authors: Palevich Nikola , Kelly William J. , Ganesh Siva , Rakonjac Jasna , Attwood Graeme T. 
Published: August 2018

ABSTRACTRumen bacterial species belonging to the generaButyrivibrioare important degraders of plant polysaccharides, particularly hemicelluloses (arabinoxylans) and pectin. Currently, four distinct species are recognized which have very similar substrate utilization profiles, but little is known about how these microorganisms are able to co-exist in the rumen. To investigate this question,Butyrivibrio hungatei(MB2003) andButyrivibrio proteoclasticus(B316T) were grown alone or in co-culture on the insoluble substrates, xylan or pectin, and their growth, release of sugars, fermentation end products and transcriptomes were examined. In single cultures, B316Twas able to degrade and grow well on xylan and pectin, whileB. hungateiMB2003 was unable to utilize either of these insoluble substrates to support significant growth. Co-cultures of B316Tgrown with MB2003 revealed that MB2003 showed almost equivalent growth to B316Twhen either xylan or pectin were supplied as substrates. The effect of co-culture on the transcriptomes of B316Tand MB2003 was very marked; B316Ttranscription was largely unaffected by the presence MB2003, but MB2003 expressed a wide range of genes encoding carbohydrate degradation/metabolism and oligosaccharide transport/assimilation in order to compete with B316Tfor the released sugars. These results suggest that B316Thas a role as an initiator of the primary solubilization of xylan and pectin, while MB2003 competes effectively as a scavenger for the released soluble sugars to enable its growth and maintenance in the rumen.IMPORTANCEFeeding a global population of nine billion people and climate change are the primary challenges facing agriculture today. Determining the roles of rumen microbes involved in plant polysaccharide breakdown is fundamental to understanding digestion and maximizing productivity of ruminant livestock.Butyrivibrioare abundant rumen bacteria and are a substantial source of polysaccharide-degrading enzymes with biotechnological applications for the depolymerization of lignocellulosic material. Our findings suggest that closely related species ofButyrivibriohave developed unique strategies for the degradation of plant fibre and the subsequent assimilation of carbohydrates in order to coexist in the competitive rumen environment. The identification of genes related to their enzymatic machinery by which these bacteria work in concert to degrade these different forms of polysaccharides contributes to our understanding of carbon flow in the rumen.
MaizeYABBY drooping leafgenes regulate floret development and floral meristem determinacy
Authors: Strable Josh , Vollbrecht Erik 
Published: August 2018

AbstractFloret units in cereals produce grain, directly impacting yield. Here we report mutations in the maizeCRABS CLAW(CRC) co-orthologsdrooping leaf1(drl1) anddrl2alter the development of ear and tassel florets. Pistillate florets ofdrl1ears appear sterile and display ectopic unfused carpels that fail to enclose an expanded nucellus. Staminate florets ofdrl1tassels have extra stamens and retain fertile anthers. Natural variation and transposon alleles ofdrl2enhancedrl1floret phenotypes by reducing floral meristem (FM) determinacy. Thedrlparalogs are co-expressed in lateral floral organ primordia, but not within the FM. Together, the expression patterns and indeterminate mutant FMs suggest that thedrlgenes regulate FM activity and impose meristem determinacy by a non-cell autonomous signal. Genetic interaction analyses ofdrlmutants with maize floral mutants indicate that thedrlgenes are required throughout floret development, illustrating their importance for proper floret patterning in maize.
Fast Estimation of Recombination Rates Using Topological Data Analysis
Authors: Humphreys Devon P. , McGuirl Melissa R. , Miyagi Michael , Blumberg Andrew J. 
Published: August 2018

AbstractAccurate estimation of recombination rates is critical for studying the origins and maintenance of genetic diversity. Because the inference of recombination rates under a full evolutionary model is computationally expensive, an alternative approach using topological data analysis (TDA) has been proposed. Previous TDA methods used information contained solely in the first Betti number (β1)of the cloud of genomes, which relates to the number of loops that can be detected within a genealogy. While these methods are considerably less computationally intensive than current biological model-based methods, these explorations have proven difficult to connect to the theory of the underlying biological process of recombination, and consequently have unpredictable behavior under different perturbations of the data. We introduce a new topological feature with a natural connection to coalescent models, which we callψ. We show thatψandβ1are differentially affected by changes to the structure of the data and use them in conjunction to provide a robust, efficient, and accurate estimator of recombination rates, TREE. Compared to previous TDA methods, TREE more closely approximates of the results of commonly used model-based methods. These characteristics make TREE well suited as a first-pass estimator of recombination rate heterogeneity or hotspots throughout the genome. In addition, we present novel arguments relatingβ1to population genetic models; our work justifies the use of topological statistics as summaries of distributions of genome sequences and describes a new, unintuitive relationship between topological summaries of distance and the footprint of recombination on genome sequences.
The comparative biogeography of Philippine geckos challenges predictions from a paradigm of climate-driven vicariant diversification across an island archipelago
Authors: Oaks Jamie R. , Siler Cameron D. , Brown Rafe M. 
Published: August 2018

AbstractA primary goal of biogeography is to understand how large-scale environmental processes, like climate change, affect diversification One often-invoked but seldom tested process is the “species-pump” model, in which repeated bouts of co-speciation are driven by oscillating climate-induced habitat connectivity cycles. For example, over the past three million years, the landscape of the Philippine Islands has repeatedly coalesced and fragmented due to sea-level changes associated with glacial cycles. This repeated climate-driven vicariance has been proposed as a model of speciation across evolutionary lineages codistributed throughout the islands. This model predicts speciation times that are temporally clustered around the times when interglacial rises in sea level fragmented the islands. To test this prediction, we collected comparative genomic data from 16 pairs of insular gecko populations. We analyze these data in a full-likelihood, Bayesian model-choice framework to test for shared divergence times among the pairs. Our results provide support against the species-pump model prediction in favor of an alternative interpretation, namely that each pair of gecko populations diverged independently. These results suggest the repeated bouts of climate-driven landscape fragmentation has not been an important mechanism of speciation for gekkonid lizards on the Philippine Islands.
Life-history traits inform on population trends when assessing the conservation status of a declining tiger shark population
Authors: Brown Christopher J. , Roff George 
Published: August 2018

AbstractThe assessment of the conservation status of wide ranging species depends on estimates of the magnitude of their population trends. The accuracy of trend estimates will depend on where and how many locations within a species’ range are sampled. We ask how the spatial extent of sampling interacts with non-linear patterns in long-term trends to affect estimates of decline in standardised catch of tiger sharks (Galeocerdo cuvier) on the east coast of Australia. We apply a Bayesian trend model that uses prior information on life-history traits to estimate trends where we use data from all regions versus spatial subsets of the data. As more regions were included in the model the trend estimates converged towards an overall decline of 71% over three generations. Trends estimated from data only from northern regions or southern regions underestimated and overestimated the regional decline, respectively. When a subset of regions was modelled, rather than the full data-set, the prior informed by life-history traits performed well, as did a weakly informed prior that allowed for high variation. The rate of decline in tiger sharks is consistent with a listing East Coast Australia tiger sharks as endangered under local legislation. Monitoring programs that aim to estimate population trends should attempt to cover the extremes and mid-points of a population’s range. Life-history information can be used to inform priors for population variation and may give more accurate estimates of trends that can be justified in debates about the status of threatened species, particularly when sampling is limited.