bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic regression of claw keratin, taste receptor and light-associated genes inform biology and evolutionary origins of snakes
Authors: Emerling Christopher A. 
Published: April 2017

AbstractRegressive evolution of anatomical traits corresponds with the regression of genomic loci underlying such characters. As such, studying patterns of gene loss can be instrumental in addressing questions of gene function, resolving conflicting results from anatomical studies, and understanding the evolutionary history of clades. The origin of snakes coincided with the regression of a number of anatomical traits, including limbs, taste buds and the visual system. By studying the genomes of snakes, I was able to test three hypotheses associated with the regression of these features. The first concerns two keratins that are putatively specific to claws. Both genes that encode these keratins were pseudogenized/deleted in snake genomes, providing additional evidence of claw- specificity. The second hypothesis is whether snakes lack taste buds, an issue complicated by unequivocal, conflicting results in the literature. I found evidence that different snakes have lost one or more taste receptors, but all snakes examined retained at least some capacity for taste. The final hypothesis I addressed is that the earliest snakes were adapted to a dim light niche. I found evidence of deleted and pseudogenized genes with light- associated functions in snakes, demonstrating a pattern of gene loss similar to other historically nocturnal clades. Together these data also provide some bearing on the ecological origins of snakes, including molecular dating estimates that suggest dim light adaptation preceded the loss of limbs.
GlnK facilitates the dynamic regulation of bacterial nitrogen assimilation
Authors: Gosztolai Adam , Schumacher Jörg , Behrends Volker , Bundy Jacob G , Heydenreich Franziska , Bennett Mark H , Buck Martin , Barahona Mauricio 
Published: April 2017

AbstractAmmonium assimilation inE. coliis regulated by two paralogous proteins (GlnB and GlnK), which orchestrate interactions with regulators of gene expression, transport proteins and metabolic pathways. Yet how they conjointly modulate the activity of glutamine synthetase (GS), the key enzyme for nitrogen assimilation, is poorly understood. We combine experiments and theory to study the dynamic roles of GlnB and GlnK during nitrogen starvation and upshift. We measure time-resolvedin vivoconcentrations of metabolites, total and post-translationally modified proteins, and develop a concise biochemical model of GlnB and GlnK that incorporates competition for active and allosteric sites, as well as functional sequestration of GlnK. The model predicts the responses of GS, GlnB and GlnK under time-varying external ammonium level in the wild type and two genetic knock-outs. Our results show that GlnK is tightly regulated under nitrogen-rich conditions, yet it is expressed during ammonium run-out and starvation. This suggests a role for GlnK as a buffer of nitrogen shock after starvation, and provides a further functional link between nitrogen and carbon metabolisms.
Genomics-enabled analysis of the emergent disease cotton bacterial blight
Authors: Phillips Anne Z. , Berry Jeffrey C. , Wilson Mark C. , Vijayaraghavan Anupama , Burke Jillian , Bunn J. Imani , Allen Tom W. , Wheeler Terry , Bart Rebecca 
Published: April 2017

AbstractCotton bacterial blight (CBB), an important disease of (Gossypium hirsutum) in the early 20th century, had been controlled by resistant germplasm for over half a century. Recently, CBB re-emerged as an agronomic problem in the United States. Here, we report analysis of cotton variety planting statistics that indicate a steady increase in the percentage of susceptible cotton varieties grown each year since 2009. Phylogenetic analysis revealed that strains from the current outbreak cluster with race 18 Xanthomonas citri pv. malvacearum (Xcm) strains.Illumina based draft genomes were generated for thirteen Xcm isolates and analyzed along with 4 previously published Xcm genomes. These genomes encode 24 conserved and nine variable type three effectors. Strains in the race 18 clade contain 3 to 5 more effectors than other Xcm strains. SMRT sequencing of two geographically and temporally diverse strains of Xcm yielded circular chromosomes and accompanying plasmids. These genomes encode eight and thirteen distinct transcription activator-like effector genes. RNA-sequencing revealed 52 genes induced within two cotton cultivars by both tested Xcm strains. This gene list includes a homeologous pair of genes, with homology to the known susceptibility gene, MLO. In contrast, the two strains of Xcm induce different clade III SWEET sugar transporters. Subsequent genome wide analysis revealed patterns in the overall expression of homeologous gene pairs in cotton after inoculation by Xcm. These data reveal host-pathogen specificity at the genetic level and strategies for future development of resistant cultivars.Author SummaryCotton bacterial blight (CBB), caused by Xanthomonas citri pv. malvacearum (Xcm), significantly limited cotton yields in the early 20th century but has been controlled by classical resistance genes for more than 50 years. In 2011, the pathogen re-emerged with a vengeance. In this study, we compare diverse pathogen isolates and cotton varieties to further understand the virulence mechanisms employed by Xcm and to identify promising resistance strategies. We generate fully contiguous genome assemblies for two diverse Xcm strains and identify pathogen proteins used to modulate host transcription and promote susceptibility. RNA-Sequencing of infected cotton reveals novel putative gene targets for the development of durable Xcm resistance. Together, the data presented reveal contributing factors for CBB re-emergence in the U.S. and highlight several promising routes towards the development of durable resistance including classical resistance genes and potential manipulation of susceptibility targets.
StateHub-StatePaintR: rapid and reproducible chromatin state evaluation for custom genome annotation
Authors: Coetzee Simon G. , Ramjan Zachary , Dinh Huy Q. , Berman Benjamin P. , Hazelett Dennis J. 
Published: April 2017

AbstractGenome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and easily interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database,StateHub. In addition, we created an annotation tool for bioconductor,StatePaintR, which accesses these models and uses them to rapidly (on the order of seconds) produce chromatin state segmentations in standard genome browser formats. Annotations are fully documented with change history and versioning, authorship information, and original source files.StatePaintRcalculates ranks for each state from next-gen sequencing peak statistics, facilitating variant prioritization, enrichment testing, and other types of quantitative analysis.StateHubhosts annotation tracks for major public consortia as a resource, and allows users to submit their own alternative models.
CRAST Leads to Homologous-ncRNA Search in Genomic Scale
Authors: Tagashira Masaki 
Published: April 2017

ABSTRACTMotivationNon-coding RNAs (ncRNAs) play important roles in various biological processes. In past, homologousncRNA search in genomic scale (e.g., search all house mouse ncRNAs for several human ones) is difficult since explicit consideration of secondary structure in alignment leads to impractical complexity on both of time and space.ResultsIn this study, building the programCRAST(Context RNA Alignment Search Tool, available at “https://github.com/heartsh/crast” including the used validation/test set), we developed the CRAST algorithm, a“seed-and-extend”alignment one based on adaptive seed and RNA secondary structure context (motif probabilities) as in Fig. 1. The algorithm isO(n:a sum of lengths of target sequences) on time through help of adaptive seed, implicitly considering both of sequence and secondary structure; it provides computation time comparable with other BLAST-like tools, significantly reduced from any variant of the Sankoff algorithm for alignment with the explicit consideration. It detects homologs as many as other BLAST-like tools and the lowest number of non-homologous ncRNAs.
GeoDiver: Differential Gene Expression Analysis & Gene-Set Analysis For GEO Datasets
Authors: Moghul Ismail , Hewapathirana Suresh , Nawaz Nazrath , Rashid Anisatu , Priebe Marian , Vieira Bruno , Smeraldi Fabrizio , Bessant Conrad 
Published: April 2017

ABSTRACTSummaryGeoDiver is an online web application for performing Differential Gene Expression Analysis (DGEA) and Generally Applicable Gene-set Enrichment Analysis (GAGE) on gene expression datasets from the publicly available Gene Expression Omnibus (GEO). The output produced includes numerous high quality interactive graphics, allowing users to easily explore and examine complex datasets instantly. Furthermore, the results produced can be reviewed at a later date and shared with collaborators.AvailabilityGeoDiver is freely available online athttp://www.geodiver.co.uk. The source code is available on Github:https://github.com/GeoDiver/GeoDiverand a docker image is available for easy installation.
Challenges and emerging directions in single-cell analysis
Authors: Yuan Guo-Cheng , Cai Long , Elowitz Michael , Enver Tariq , Fan Guoping , Guo Guoji , Irizarry Rafael , Kharchenko Peter , Kim Junhyong , Orkin Stuart , Quackenbush John , Saadatpour Assieh , Schroeder Timm , Shivdasani Ramesh , Tirosh Itay 
Published: April 2017

AbstractSingle-cell analysis is a rapidly evolving approach to characterize genome-scale molecular information at the individual cell level. Development of single-cell technologies and computational methods has enabled systematic investigation of cellular heterogeneity in a wide range of tissues and cell populations, yielding fresh insights into the composition, dynamics, and regulatory mechanisms of cell states in development and disease. Despite substantial advances, significant challenges remain in the analysis, integration, and interpretation of single-cell omics data. Here, we discuss the state of the field and recent advances, and look to future opportunities.
Changes in LXRα phosphorylation promote a novel diet-induced transcriptome that alters the transition from fatty liver to steatohepatitis
Authors: Becares Natalia , Gage Matthew C , Martin-Gutierrez Lucia , Shrestha Elina , Louie Rikah , Pourcet Benoit , Pello Oscar M , Luong Tu Vinh , Goñi Saioa , Liang Ning , Pichardo Cesar , Røberg-Larsen Hanne , Diaz Vanessa , Steffensen Knut R. , Garabedian Michael J. , Rombouts Krista , Treuter Eckardt , Pineda-Torra Inés 
Published: April 2017

SUMMARYUnderstanding the transition from fatty liver (steatosis) to inflammatory and fibrotic steatohepatitis, is key to define strategies that alter its progression. Here we show that, when challenged with a high fat-high cholesterol diet, mice carrying a mutation that abolishes phosphorylation at Ser196 (S196A) in the liver X receptor alpha (LXRα) exhibit reduced hepatic inflammation and fibrosis despite displaying enhanced steatosis. This is associated with a marked protection against cholesterol accumulation. Reduced steatohepatitis in S196A mice involves unique reprogramming of the liver transcriptome in response to the diet. Remarkably, impaired LXRα phosphorylation uncovers novel diet-specific/phosphorylation-sensitive genes, whose regulation does not simply mirror ligand-induced LXR activation. Regulation of these unique, dually responsive genes, is associated with the promotion of LXR and cofactor occupancy under a cholesterol-rich diet. Therefore, Ser196-LXRα phosphorylation acts as a novel nutritional sensor that triggers a unique diet-induced transcriptome, thereby modulating metabolic, inflammatory and fibrotic responses important in the transition to steatohepatitis.
Cell-type specific burst firing interacts with theta and beta activity in prefrontal cortex during attention states
Authors: Voloh B. , Womelsdorf T. 
Published: April 2017

AbstractPopulation-level theta and beta band activity in anterior cingulate and prefrontal cortex (ACC/PFC) are prominent signatures of endogenously controlled, adaptive behaviors. But how these rhythmic activities are linked to cell-type specific activity has remained unclear. Here, we suggest such a cell-to-systems level linkage. We found that the rate of burst spiking events is enhanced particularly during attention states and that attention-specific burst spikes have a unique temporal relationship to local theta and beta band population level activities. For the 5-10Hz theta frequency range, bursts coincided with transient increases of local theta power relative to non-bursts, particularly for bursts of putative interneurons. For the 16-30Hz beta frequency, bursts of putative interneurons phase synchronized stronger than nonbursts, and were associated with larger beta power modulation. In contrast, burst of putative pyramidal cells were overall similarly beta-synchronized than nonbursts, but were linked with stronger beta power only when they occurred early in the beta cycle. These findings suggests that in the ACC/PFC during attention states, mechanisms underlying burst firing are intimately linked to narrow band population level activities, providing a cell-type specific window into the emergence, resetting, or termination of oscillatory activities.
InDel assembly: A novel framework for engineering protein loops through length and compositional variation
Authors: Tizei Pedro A. G. , Harris Emma , Renders Marleen , Pinheiro Vitor B. 
Published: April 2017

AbstractInsertions and deletions (indels) are known to affect function, biophysical properties and substrate specificity of enzymes, and they play a central role in evolution. Despite such clear significance, this class of mutation remains an underexploited tool in protein engineering with no available platforms capable of systematically generating or analysing libraries of varying sequence composition and length. We present a novel DNA assembly platform (InDel assembly), based on cycles of endonuclease restriction and ligation of standardised dsDNA building blocks, that can generate libraries exploring both composition and sequence length variation. In addition, we developed a framework to analyse the output of selection from InDel-generated libraries, combining next generation sequencing and alignment-free strategies for sequence analysis. We demonstrate the approach by engineering the well-characterized TEM-1 β-lactamase Ω-loop, involved in substrate specificity, identifying multiple novel extended spectrum β-lactamases with loops of modified length and composition areas of the sequence space not previously explored. Together, the InDel assembly and analysis platforms provide an efficient route to engineer protein loops or linkers where sequence length and composition are both essential functional parameters.
Debt policy and firm performance of family firms: the impact of economic adversity
Authors: Vieira Elisabete Simões 
Published: April 2017

PurposeThe purpose of this paper is to analyse the relationship between debt policy and performance among family firms (FF), providing evidence on whether FF differ from non-family firms (NFF). It also focusses on the possibility of asymmetrical debt policy impact on performance between periods of stability and economic adversity.Design/methodology/approachThe paper employs panel data regression, considering a sample of Portuguese listed firms for the period between 1999 and 2014.FindingsOverall, the author find evidence that debt contributes negatively to firms’ performance, which is consistent with the pecking order prediction, and that the relationship between debt and performance do not differ significantly between FF and NFF. After addressing the endogeneity issue, the author conclude that firms’ performance is negatively influenced by both short- and long-term debt. Considering the total debt, the negative relationship between the two variables differs from family and non-family companies. The results show that age and size influences positively, and the independence of the board directors influences negatively the firms’ performance. The empirical findings suggest that under economic adversity, the firms’ performance is negatively affected. Finally, the author conclude that return on assets appear to fit better than return on equity or MB when you want to relate debt and firm performance.Research limitations/implicationsA limitation of this study is the small size of the Euronext Lisbon that results in a small sample.Originality/valueThis paper offers some insights on the relationship between debt policy and firm performance from a country with weak protection of minority shareholders, concentrated ownership and a significant family control. It also gives the opportunity to analyse whether firm performance differs according to market conditions.
Knowledge strategy planning: an integrated approach to manage uncertainty, turbulence, and dynamics
Authors: Bolisani Ettore , Bratianu Constantin 
Published: April 2017

Purpose
Knowledge strategy and its planning are affected by uncertainty and environmental turbulence. This paper aims to discuss these issues and present knowledge strategy planning as an integrated approach for facing these conditions.

Design/methodology/approach
Based on an extensive survey and an original re-elaboration of the literature, the paper addresses these research questions: What is the meaning of knowledge strategy, and how can it be related to concepts such as strategic thinking, business strategy and knowledge management (KM) in organizations? What are the limitations of a pure rational approach to knowledge strategy in turbulent environments and under uncertainty? and What approaches can be consequently proposed to formulate knowledge strategies?

Findings
The study provides a critical reading of the current literature. Also, it proposes an integrated approach that sees planning as a continuous effort of learning and adaptation to needs and opportunities that dynamically emerge from daily practices.

Research limitations/implications
The proposed framework can inspire a new research agenda to detect how knowledge strategies are planned in companies and how they are continuously adapted on the basis of a dialog between rational contributions and perceptions of reality, practical views, intuitions and emotions. This can also inspire a new agenda for company strategists and KM professionals.

Originality/value
In the literature, little attention has been devoted to knowledge strategy planning. The paper contributes to fill this gap and proposes a new way to see knowledge strategy as an integration of rational thinking and dynamic learning.
Managing extracted knowledge from big social media data for business decision making
Authors: He Wu , Wang Feng-Kwei , Akula Vasudeva 
Published: April 2017

Purpose
This paper aims to propose a knowledge management (KM) framework for leveraging big social media data to help interested organizations integrate Big Data technology, social media and KM systems to store, share and leverage their social media data. Specifically, this research focuses on extracting valuable knowledge on social media by contextually comparing social media knowledge among competitors.

Design/methodology/approach
A case study was conducted to analyze nearly one million Twitter messages associated with five large companies in the retail industry (Costco, Walmart, Kmart, Kohl’s and The Home Depot) to extract and generate new knowledge and to derive business decisions from big social media data.

Findings
This case study confirms that this proposed framework is sensible and useful in terms of integrating Big Data technology, social media and KM in a cohesive way to design a KM system and its process. Extracted knowledge is presented visually in a variety of ways to discover business intelligence.

Originality/value
Practical guidance for integrating Big Data, social media and KM is scarce. This proposed framework is a pioneering effort in using Big Data technologies to extract valuable knowledge on social media and discover business intelligence by contextually comparing social media knowledge among competitors.
Diffusion of integrated reporting in an emerging South Asian (SAARC) nation
Authors: Gunarathne Nuwan , Senaratne Samanthi 
Published: April 2017

PurposeThis paper aims to examine how and why integrated reporting (IR) as a managerial technology is diffused in Sri Lanka, an emerging South Asian (South Asian Association for Regional Cooperation) nation, from an expansion diffusion perspective.Design/methodology/approachThe study followed two analytical steps. First, the adopter groups of IR of the country’s stock exchange were identified based on their annual reports. Second, the key stakeholders (both internal and external) in the process of IR diffusion in the country were interviewed. Thereafter, a content analysis of these semi-structured interviews was carried out based on the demand-pull and supply-push sides of the diffusion theory of innovation.FindingsThe temporal trend of IR suggests that the country is currently in the diffusion stage with many first time adopters are likely to join the bandwagon of IR. In the primary stage, its early adoption has been driven by the efficient-choice perspective. However, in the diffusion stage, most of the adopters are driven by fashion setting, which is mainly attributable to the active propagators in the supply side of IR diffusion. IR has been mainly a transition evolving through the incremental changes in sustainability reporting. Many firms have not internalized the IR principles with the danger of IR becoming a mere reporting mechanism.Originality/valueThe application of both demand-pull and supply-push sides of the diffusion theory of innovation is still limited, particularly in the case of new reporting mechanisms. The study provides new insights into how these two forces contribute to creating a “practice-reporting portrayal gap” in IR.