bluuebunny/crossref_metadata_2025_split huggingface dataset:
Soil microbial responses to forest floor litter manipulation and nitrogen addition in a mixed-wood forest of northern China
Authors: Sun Xiao-Lu , Zhao Jing , You Ye-Ming , Jianxin Sun Osbert 
Published: January 2016

AbstractChanges in litterfall dynamics and soil properties due to anthropogenic or natural perturbations have important implications to soil carbon (C) and nutrient cycling via microbial pathway. Here we determine soil microbial responses to contrasting types of litter inputs (leaf vs. fine woody litter) and nitrogen (N) deposition by conducting a multi-year litter manipulation and N addition experiment in a mixed-wood forest. We found significantly higher soil organic C, total N, microbial biomass C (MBC) and N (MBN), microbial activity (MR) and activities of four soil extracellular enzymes, including β-glucosidase (BG), N-acetyl-β-glucosaminidase (NAG), phenol oxidase (PO) and peroxidase (PER), as well as greater total bacteria biomass and relative abundance of gram-negative bacteria (G-) community, in top soils of plots with presence of leaf litter than of those without litter or with presence of only fine woody litter. No apparent additive or interactive effects of N addition were observed in this study. The occurrence of more labile leaf litter stimulated G-, which may facilitate microbial community growth and soil C stabilization as inferred by findings in literature. A continued treatment with contrasting types of litter inputs is likely to result in divergence in soil microbial community structure and function.
Evaluation of the External RNA Controls Consortium (ERCC) reference material using a modified Latin square design
Authors: Pine PS , Munro SA , Parsons JR , McDaniel J , Bergstrom Lucas A , Lozach J , Myers TG , Su Q , Jacobs-Helber SM , Salit M 
Published: January 2016

AbstractBACKGROUNDHighly multiplexed assays for quantitation of RNA transcripts are being used in many areas of biology and medicine. Using data generated by these transcriptomic assays requires measurement assurance with appropriate controls. Methods to prototype and evaluate multiple RNA controls were developed as part of the External RNA Controls Consortium (ERCC) assessment process. These approaches included a modified Latin square design to provide a broad dynamic range of relative abundance with known differences between four complex pools of ERCC RNA transcripts spiked into a human liver total RNA background.RESULTSERCC pools were analyzed on four different microarray platforms: Agilent 1- and 2-color, Illumina bead, and NIAID lab-made spotted microarrays; and two different second-generation sequencing platforms: the Life Technologies 5500xl and the Illumina HiSeq 2500. Individual ERCCs were assessed for reproducible performance in signal response to concentration among the platforms. Most demonstrated linear behavior if they were not located near one of the extremes of the dynamic range. Performance issues with any individual ERCC transcript could be attributed to detection limitations, platform-specific target probe issues, or potential mixing errors. Collectively, these pools of spike-in RNA controls were evaluated for suitability as surrogates for endogenous transcripts to interrogate the performance of the RNA measurement process of each platform. The controls were useful for establishing the dynamic range of the assay, as well as delineating the useable region of that range where differential expression measurements, expressed as ratios, would be expected to be accurate.CONCLUSIONSThe modified Latin square design presented here uses a composite testing scheme for the evaluation of multiple performance characteristics: linear performance of individual controls, signal response within dynamic range pools of controls, and ratio detection between pairs of dynamic range pools. This compact design provides an economical sample format for the evaluation of multiple external RNA controls within a single experiment per platform. These results indicate that well-designed pools of RNA controls, spiked-into samples, provide measurement assurance for endogenous gene expression experiments.
Systematic identification of cooperation between DNA binding proteins in 3D space
Authors: Zhang Kai , Li Nan , Wang Wei 
Published: January 2016

AbstractCooperation between DNA-binding proteins (DBPs) such as transcription factors and chromatin remodeling enzymes plays a pivotal role in regulating gene expression and other biological processes. Such cooperation is often via interaction between DBPs that bind to loci located distal in the linear genome but close in the 3D space, referred as trans-cooperation. Due to the lack of 3D chromosomal structure, identification of DBP cooperation has been limited to those binding to neighbor regions in the linear genome, referred as cis-cooperation. Here we present the first study that integrates protein ChIP-seq and Hi-C data to systematically identify both cis- and trans-cooperation between DBPs. We developed a new network model that allows identification of cooperation between multiple DBPs and reveals cell type specific or independent regulations. Particularly interesting, we have retrieved many known and previously unknown trans-cooperation between DBPs in the chromosomal loops that may be a key factor for influencing 3D chromosomal structure. The software is available athttp://wanglab.ucsd.edu/star/DBPnet/index.html.
A Probabilistic, Distributed, Recursive Mechanism for Decision-making in the Brain
Authors: Caballero Javier A. , Humphries Mark D. , Gurney Kevin N. 
Published: January 2016

AbstractDecision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics.Author SummaryDecision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinson’s and Huntington’s diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decisionmaking has, hitherto, remained elusive. Here we show the essential composition of the brain’s decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys’ choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decisionmaking in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.
High-quality thermodynamic data on the stability changes of proteins upon single-site mutations
Authors: Pucci Fabrizio , Bourgeas Raphaël , Rooman Marianne 
Published: January 2016

AbstractWe have set up and manually curated a dataset containing experimental information on the impact of amino acid substitutions in a protein on its thermal stability. It consists of a repository of experimentally measured melting temperatures (Tm) and their changes upon point mutations (ΔTm) for proteins having a well-resolved X-ray structure. This high-quality dataset is designed for being used for the training or benchmarking of in silico thermal stability prediction methods. It also reports other experimentally measured thermodynamic quantities when available,i.e. the folding enthalpy (ΔH) and heat capacity (ΔCP) of the wild type proteins and their changes upon mutations (ΔΔHand ΔΔCP), as well as the change in folding free energy (ΔΔG) at a reference temperature. These data are analyzed in view of improving our insights into the correlation between thermal and thermodynamic stabilities, the asymmetry between the number of stabilizing and destabilizing mutations, and the difference in stabilization potential of thermostable versus mesostable proteins.
Statistical evidence for common ancestry: New tests of universal ancestry
Authors: Larget Bret , Ané Cécile , Bontrager Martin , Hunter Steve , Stenz Noah , Baum David A. 
Published: January 2016

AbstractWhile there is no doubt among evolutionary biologists that all living species, or merely all living species within a particular group (e.g., animals), share descent from a common ancestor, formal statistical methods for evaluating common ancestry from aligned DNA sequence data have received criticism. One primary criticism is that prior methods take sequence similarity as evidence for common ancestry while ignoring other potential biological causes of similarity, such as functional constraints. We present a new statistical framework to test separate ancestry versus common ancestry that avoids this pitfall. We illustrate the efficacy of our approach using a recently published large molecular alignment to examine common ancestry of all primates (including humans).We find overwhelming evidence against separate ancestry and in favor of common ancestry for orders and families of primates. We also find overwhelming evidence that humans share a common ancestor with other primate species.The novel statistical methods presented here provide formal means to test separate ancestry versus common ancestry from aligned DNA sequence data while accounting for functional constraints that limit nucleotide base usage on a site-by-site basis.
ARGON: Fast, Whole-Genome Simulation of the Discrete Time Wright-Fisher Process
Authors: Palamara Pier Francesco 
Published: January 2016

AbstractMotivationSimulation under the coalescent model is ubiquitous in the analysis of genetic data. The rapid growth of real data sets from multiple human populations led to increasing interest in simulating very large sample sizes at whole-chromosome scales. When the sample size is large, the coalescent model becomes an increasingly inaccurate approximation of the discrete time Wright-Fisher model (DTWF). Analytical and computational treatment of the DTWF, however, is generally harder.ResultsWe present a simulator (ARGON) for the DTWF process that scales up to hundreds of thousands of samples and whole-chromosome lengths, with a time/memory performance comparable or superior to currently available methods for coalescent simulation. The simulator supports arbitrary demographic history, migration, Newick tree output, variable mutation/recombination rates and gene conversion, and efficiently outputs pairwise identical-bydescent (IBD) sharing data.AvailabilityARGON (version 0.1) is written in Java, open source, and freely available athttps://github.com/pierpal/ARGON.Contactppalama@hsph.harvard.eduSupplementary informationSupplementary data are available online.
The Computational Nature of Memory Modification
Authors: Gershman Samuel J. , Monfils Marie-H , Norman Kenneth A. , Niv Yael 
Published: January 2016

AbstractRetrieving a memory can modify its influence on subsequent behavior. Whether this phenomenon arises from modification of the contents of the memory trace or its accessibility is a matter of considerable debate. We develop a computational theory that incorporates both mechanisms. Modification of the contents of the memory trace occurs through classical associative learning, but which memory trace is accessed (and thus made eligible for modification) depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature, including dependence on the strength and age of memories, the interval between memory retrieval and extinction, and prediction errors following retrieval.
A performance-optimized model of neural responses across the ventral visual stream
Authors: Seibert Darren , Yamins Daniel , Ardila Diego , Hong Ha , DiCarlo James J. , Gardner Justin L. 
Published: January 2016

AbstractHuman visual object recognition is subserved by a multitude of cortical areas. To make sense of this system, one line of research focused on response properties of primary visual cortex neurons and developed theoretical models of a set of canonical computations such as convolution, thresholding, exponentiating and normalization that could be hierarchically repeated to give rise to more complex representations. Another line or research focused on response properties of high-level visual cortex and linked these to semantic categories useful for object recognition. Here, we hypothesized that the panoply of visual representations in the human ventral stream may be understood as emergent properties of a system constrained both by simple canonical computations and by top-level, object recognition functionality in a single unified framework (Yamins et al., 2014; Khaligh-Razavi and Kriegeskorte, 2014; Güçlü and van Gerven, 2015). We built a deep convolutional neural network model optimized for object recognition and compared representations at various model levels using representational similarity analysis to human functional imaging responses elicited from viewing hundreds of image stimuli. Neural network layers developed representations that corresponded in a hierarchical consistent fashion to visual areas from V1 to LOC. This correspondence increased with optimization of the model’s recognition performance. These findings support a unified view of the ventral stream in which representations from the earliest to the latest stages can be understood as being built from basic computations inspired by modeling of early visual cortex shaped by optimization for high-level object-based performance constraints.Significance StatementPrior work has taken two complimentary approaches to understanding the cortical processes underlying our ability to visually recognize objects. One approach identified canonical computations from primary visual cortex that could be hierarchically repeated and give rise to complex representations. Another approach linked later visual area responses to semantic categories useful for object recognition. Here we combined both approaches by optimizing a deep convolution neural network based on canonical computations to preform object recognition. We found that this network developed hierarchically similar response properties to those of visual areas we measured using functional imaging. Thus, we show that object-based performance optimization results in predictive models that not only share similarity with late visual areas, but also intermediate and early visual areas.
Neo-sex chromosomes in the Monarch butterfly,Danaus plexippus
Authors: Mongue Andrew J. , Nguyen Petr , Volenikova Anna , Walters James R. 
Published: January 2016

AbstractWe report the discovery of a neo-sex chromosome in Monarch butterfly,Danaus plexippus, and several of its close relatives. Z-linked scaffolds in theD. plexippusgenome assembly were identified via sex-specific differences in Illumina sequencing coverage. Additionally, a majority of theD. plexippusgenome assembly was assigned to chromosomes based on counts of 1-to-1 orthologs relative to the butterflyMelitaea cinxia(with replication using two other lepidopteran species), in which genome scaffolds have been mapped to linkage groups. Sequencing-coverage based assessments of Z-linkage combined with homology based chromosomal assignments provided strong evidence for a Z-autosome fusion in theDanauslineage, involving the autosome homologous to chromosome 21 inM. cinxia. Coverage analysis also identified three notable assembly errors resulting in chimeric Z-autosome scaffolds. Cytogenetic analysis further revealed a large W-chromosome that is partially euchromatic, consistent with being a neo-W chromosome. The discovery of a neo-Z and the provisional assignment of chromosome linkage for >90% ofD. plexippusgenes lays the foundation for novel insights concerning sex chromosome evolution in this female-heterogametic model species for functional and evolutionary genomics.
Mutation signatures reveal biological processes in human cancer
Authors: R. Covington Kyle , Shinbrot Eve , A. Wheeler David 
Published: January 2016

AbstractReplication errors in the genome accumulate from a variety of mutational processes, which leave a history of mutations on the affected genome. The relative contribution of each mutational process has been characterized by non-negative matrix factorization and has lead to deeper insight into both mutational and repair processes contributing to cancer. However current implementations of NMF have left unresolved some specific patterns that should be present in the mutation data and have not generated signatures designed for classification. Here, we use a variant of NMF, termed non-smooth NMF, to generate sparse matrix factorizations of somatic mutation profiles present in 7129 tumors. nsNMF factorization revealed 21 mutational signatures. We found three APOBEC mutational processes clearly segregating with the published APOBEC enzymology and trans-lesion repair processes. We discovered several signatures differed between geographic locations even between closely related tissues.
A novel mutation in the nucleoporin NUP35 causes murine degenerative colonic smooth muscle myopathy
Authors: Parish Ian A. , Stamp Lincon A. , Lorenzo Ayla May D. , Fowler Suzanne M. , Sontani Yovina , Miosge Lisa A. , Howard Debbie R. , Goodnow Christopher C. , Young Heather M. , Furness John B. 
Published: January 2016

AbstractChronic Intestinal Pseudo-Obstruction (CIPO) is a rare, but life-threatening, disease characterized by severe intestinal dysmotility. Histopathological studies of CIPO patients have identified several different mechanisms that appear to be responsible for the dysmotility, including defects in neurons, smooth muscle or interstitial cells of Cajal. Currently there are few mouse models of the various forms of CIPO. We generated a mouse with a point mutation in the RNA Recognition Motif of theNup35gene, which encodes a component of the nuclear pore complex.Nup35mutants developed a severe megacolon and exhibited reduced lifespan. Histopathological examination revealed a degenerative myopathy that developed after birth and specifically affected smooth muscle in the colon; smooth muscle in the small bowel and the bladder were not affected. Furthermore, no defects were found in enteric neurons or interstitial cells of Cajal.Nup35mice are likely to be a valuable model for the sub-type of CIPO characterized by degenerative myopathy. Our study also raises the possibility thatNup35polymorphisms could contribute to some cases of CIPO.Significance StatementChronic Intestinal Pseudo-Obstruction (CIPO) is a disabling bowel disorder in which the symptoms resemble those caused by mechanical obstruction, but no physical obstruction is present. Some patients with CIPO have defects in intestinal neurons while in other CIPO patients the muscle cells in the bowel wall appear to degenerate, but the underlying cause of these defects is unknown in most CIPO patients. We generated a mouse that has a mutation inNup35, which encodes a component of the pores found within the membrane of the cell nucleus. The mutant mice developed intestinal obstruction, which we showed was due to degeneration of the muscle cells in the colon. This mouse is likely to provide new insights into some forms of CIPO.
An Ancestry Based Approach for Detecting Interactions
Authors: Park Danny S. , Eskin Itamar , Kang Eun Yong , Gamazon Eric R. , Eng Celeste , Gignoux Christopher R. , Galanter Joshua M. , Burchard Esteban , Ye Chun J. , Aschard Hugues , Eskin Eleazar , Halperin Eran , Zaitlen Noah 
Published: January 2016

IAbstractBackground:Epistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies.Results:In this work, we develop a new statistical approach to address these issues that leverages genetic ancestry in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals respectively, identifying nine interactions that were significant atp< 5×10−8, we show that two of the interactions in methylation data replicate, and the remaining six are significantly enriched for low p-values (p< 1.8×10−6).Conclusion:We show that genetic ancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits.
Can social networks increase households’ contribution to public-good provision in rural China?
Authors: Cai Qihua , Zhu Yuchun , Chen Qihui 
Published: January 2016

Purpose– The purpose of this paper is to examine the roles social networks play in households’ contribution to the provision of small hydraulic facilities (SHFs) in rural China.Design/methodology/approach– This paper adopts a sample-selection ordered probit model (Greene and Hensher, 2010) to estimate the impacts of overall social-network intensity, of the number of strong ties (relatives), and of the number of weak ties (friends), using data on 1,064 representative households collected from three provinces (Inner Mongolia, Ningxia, and Shandong).Findings– The numbers of strong ties and weak ties both have significant impacts on households’ willingness to contribute to SHFs provision, but only the latter has a significant impact on their level of contribution. More specifically, a one standard deviation increase in the number of weak ties (i.e. friends) is associated with a 6.6 percent increase in households’ propensity of contributing more than 550 yuan and a 8.2 percent decrease in their propensity of contributing less than 100 yuan.Originality/value– This paper is the first to examine the impacts of social networks on households’ contribution to SHFs provision in rural China. Its finding is of great policy relevance-fostering and maintaining social networks (e.g. through rural cooperatives) can significantly increase households’ contribution to public-good provision.