bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeted Enrichment of Large Gene Families for Phylogenetic Inference: Phylogeny and Molecular Evolution of Photosynthesis Genes in the Portullugo (Caryophyllales)
Authors: Moore Abigail J. , de Vos Jurriaan M. , Hancock Lillian P. , Goolsby Eric , Edwards Erika J. 
Published: June 2017

ABSTRACTHybrid enrichment is an increasingly popular approach for obtaining hundreds of loci for phylogenetic analysis across many taxa quickly and cheaply. The genes targeted for sequencing are typically single-copy loci, which facilitate a more straightforward sequence assembly and homology assignment process. However, single copy loci are relatively uncommon elements of most genomes, and as such may provide a biased evolutionary history. Furthermore, this approach limits the inclusion of most genes of functional interest, which often belong to multi-gene families. Here we demonstrate the feasibility of including large gene families in hybrid enrichment protocols for phylogeny reconstruction and subsequent analyses of molecular evolution, using a new set of bait sequences designed for the “portullugo” (Caryophyllales), a moderately sized lineage of flowering plants (~2200 species) that includes the cacti and harbors many evolutionary transitions to C4and CAM photosynthesis. Including multi-gene families allowed us to simultaneously infer a robust phylogeny and construct a dense sampling of sequences for a major enzyme of C4and CAM photosynthesis, which revealed the accumulation of adaptive amino acid substitutions associated with C4and CAM origins in particular paralogs. Our final set of matrices for phylogenetic analyses included 75–218 loci across 74 taxa, with ~50% matrix completeness across datasets. Phylogenetic resolution was greatly improved across the tree, at both shallow and deep levels. Concatenation and coalescent-based approaches both resolve with strong support the sister lineage of the cacti: Anacampserotaceae + Portulacaceae, two lineages of mostly diminutive succulent herbs of warm, arid regions. In spite of this congruence, BUCKy concordance analyses demonstrated strong and conflicting signals across gene trees for the resolution of the sister group of the cacti. Our results add to the growing number of examples illustrating the complexity of phylogenetic signals in genomic-scale data.
Evaluation ofin silicoalgorithms for use with ACMG/AMP clinical variant interpretation guidelines
Authors: Ghosh Rajarshi , Oak Ninad , Plon Sharon E. 
Published: June 2017

AbstractBackgroundThe American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among allin silicoalgorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants.ResultsUsing 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation wherein silicopredictions are opposite to the evidence provided by other sources. We identified recently developed algorithms with high predictive power and robust to variables like disease mechanism, gene constraint and mode of inheritance, although poorer performing algorithms are more frequently used based on review of the clinical genetics literature (2011-2017).ConclusionsOur analyses identify algorithms with high performance characteristics independent of underlying disease mechanisms. We describe combinations of algorithms with increased concordance that should improvein silicoalgorithm usage during assessment of clinically relevant variants using the ACMG/AMP guidelines.
Uncovering thematic structure to link co-occurring taxa and predicted functional content in 16S rRNA marker gene surveys
Authors: Woloszynek Stephen , Mell Joshua Chang , Simpson Gideon , O’Connor Michael P. , Rosen Gail L. 
Published: June 2017

ABSTRACTBackgroundAnalysis of microbiome data involves identifying co-occurring groups of taxa associated with sample features of interest (e.g., disease state). But elucidating key associations is often difficult since microbiome data are compositional, high dimensional, and sparse. Also, the configuration of co-occurring taxa may represent overlapping subcommunities that contribute to, for example, host status. Preserving the configuration of co-occurring microbes rather than detecting specific indicator species is more likely to facilitate biologically meaningful interpretations. In addition, analyses that utilize both taxonomic and predicted functional abundances typically independently characterize the taxonomic and functional profiles before linking them to sample information. This prevents investigators from identifying the specific functional components associate with which subsets of co-occurring taxa.ResultsWe provide an approach to explore co-occurring taxa using “topics” generated via a topic model and then link these topics to specific sample classes (e.g., diseased versus healthy). Rather than inferring predicted functional content independently from taxonomic abundances, we instead focus on inference of functional content within topics, which we parse by estimating pathway-topic interactions through a multilevel, fully Bayesian regression model. We apply our methods to two large publically available 16S amplicon sequencing datasets: an inflammatory bowel disease (IBD) dataset from Gevers et al. and data from the American Gut (AG) project. When applied to the Gevers et al. IBD study, we demonstrate that a topic highly associated with Crohn’s disease (CD) diagnosis is (1) dominated by a cluster of bacteria known to be linked with CD and (2) uniquely enriched for a subset of lipopolysaccharide (LPS) synthesis genes. In the AG data, our approach found that individuals with plant-based diets were enriched with Lachnospiraceae, Roseburia, Blautia, and Ruminococcaceae, as well as fluorobenzoate degradation pathways, whereas pathways involved in LPS biosynthesis were depleted.ConclusionsWe introduce an approach for uncovering latent thematic structure in the context of sample features for 16S rRNA surveys. Using our topic-model approach, investigators can (1) capture groups of co-occurring taxa termed topics, (2) uncover within-topic functional potential, and (3) identify gene sets that may guide future inquiry. These methods have been implemented in a freely available R package https://github.com/EESI/themetagenomics.
Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks
Authors: Pan Xiaoyong , Rijnbeek Peter , Yan Junchi , Shen Hong-Bin 
Published: June 2017

AbstractRNA regulation is significantly dependent on its binding protein partner, which is known as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs are still not well characterized, especially on the structure point of view. Informative signals hiding and interdependencies between sequence and structure specificities are two challenging problems for both predicting RBP binding sites and accurate sequence and structure motifs mining.In this study, we propose a deep learning-based method, iDeepS, to simultaneously identify the binding sequence and structure motifs from RNA sequences using convolutional neural networks (CNNs) and a bidirectional long short term memory network (BLSTM). We first perform one-hot encoding for both the sequence and predicted secondary structure, which are appropriate for subsequent convolution operations. To reveal the hidden binding knowledge from the observations, the CNNs are applied to learn the abstract motif features. Considering the close relationship between sequences and predicted structures, we use the BLSTM to capture the long range dependencies between binding sequence and structure motifs identified by the CNNs. Finally, the learned weighted representations are fed into a classification layer to predict the RBP binding sites. We evaluated iDeepS on verified RBP binding sites derived from large-scale representative CLIP-seq datasets, and the results demonstrate that iDeepS can reliably predict the RBP binding sites on RNAs, and outperforms the state-of-the-art methods. An important advantage is that iDeepS is able to automatically extract both binding sequence and structure motifs, which will improve our transparent understanding of the mechanisms of binding specificities of RBPs. iDeepS is available athttps://github.com/xypan1232/iDeepS.
Inference of Adaptive Shifts for Multivariate Correlated Traits
Authors: Bastide Paul , Ané Cécile , Robin Stéphane , Mariadassou Mahendra 
Published: June 2017

AbstractTo study the evolution of several quantitative traits, the classical phylogenetic comparative framework consists of a multivariate random process running along the branches of a phylogenetic tree. The Ornstein-Uhlenbeck (OU) process is sometimes preferred to the simple Brownian Motion (BM) as it models stabilizing selection toward an optimum. The optimum for each trait is likely to be changing over the long periods of time spanned by large modern phylogenies. Our goal is to automatically detect the position of these shifts on a phylogenetic tree, while accounting for correlations between traits, which might exist because of structural or evolutionary constraints. We show that, in the presence shifts, phylogenetic Principal Component Analysis (pPCA) fails to decorrelate traits efficiently, so that any method aiming at finding shift needs to deal with correlation simultaneously. We introduce here a simplification of the full multivariate OU model, named scalar OU (scOU), which allows for noncausal correlations and is still computationally tractable. We extend the equivalence between the OU and a BM on a re-scaled tree to our multivariate framework. We describe an Expectation Maximization algorithm that allows for a maximum likelihood estimation of the shift positions, associated with a new model selection criterion, accounting for the identifiability issues for the shift localization on the tree. The method, freely available as an R-package (PhylogeneticEM) is fast, and can deal with missing values. We demonstrate its efficiency and accuracy compared to another state-of-the-art method (ℓ1ou) on a wide range of simulated scenarios, and use this new framework to re-analyze recently gathered datasets on New World Monkeys andAnolislizards.
Network integration of multi-tumour omics data suggests novel targeting strategies
Authors: Valle Ítalo Faria do , Menichetti Giulia , Simonetti Giorgia , Bruno Samantha , Zironi Isabella , Fernandes Durso Danielle , Mombach José C M , Martinelli Giovanni , Castellani Gastone , Remondini Daniel 
Published: June 2017

AbstractWe characterize different tumour types in the search for multi-tumour drug targets, in particular aiming for drug repurposing or novel drug combinations. Starting from 11 tumour types from The Cancer Genome Atlas, we obtain three clusters based on transcriptomic correlation profiles. A network-based analysis, integrating gene expression profiles and protein interactions of cancer-related genes, allowed us to define three cluster-specific signatures, with genes belonging to NF-ĸB signaling, chromosomal instability, ubiquitin-proteasome system, DNA metabolism, and apoptosis biological processes. These signatures have been characterized by different approaches based on mutational, pharmacological and clinical evidences, demonstrating the validity of our selection. Moreover, we defined new pharmacological strategies validated byin vitroexperiments that showed inhibition of cell growth in two tumour cell lines, with significant synergistic effect. Our study thus provides a list of genes and pathways with the potential to be used, singularly or in combination, for the design of novel treatment strategies.
Distinct neuronal activity patterns induce different gene expression programs
Authors: Tyssowski Kelsey M. , Saha Ramendra N. , DeStefino Nicholas R. , Cho Jin-Hyung , Jones Richard D. , Chang Sarah M. , Romeo Palmyra , Wurzelmann Mary K. , Ward James M. , Dudek Serena M. , Gray Jesse M. 
Published: June 2017

SUMMARYBrief and sustained neuronal activity patterns can have opposite effects on synaptic strength that both require activity-regulated gene (ARG) expression. However, whether distinct patterns of activity induce different sets of ARGs is unknown. In genome-scale experiments, we reveal that a neuron’s activity-pattern history can be predicted from the ARGs it expresses. Surprisingly, brief activity selectively induces a small subset of the ARG program that that corresponds precisely to the first of three temporal waves of genes induced by sustained activity. These first-wave genes are distinguished by an open chromatin state, proximity to rapidly activated enhancers, and a requirement for MAPK/ERK signaling for their induction. MAPK/ERK mediates rapid RNA polymerase recruitment to promoters, as well as enhancer RNA induction but not histone acetylation at enhancers. Thus, the same mechanisms that establish the multi-wave temporal structure of ARG induction also enable different sets of genes to be induced by distinct activity patterns.
The Evolutionary Genomics of Grape (Vitis viniferassp.vinifera) Domestication
Authors: Zhou Yongfeng , Massonnet Mélanie , Sanjak Jaleal , Cantu Dario , Gaut Brandon S. 
Published: June 2017

ABSTRACTWe gathered genomic data from grapes (Vitis viniferassp.vinifera), a clonally propagated perennial crop, to address three ongoing mysteries about plant domestication. The first is the duration of domestication; archaeological evidence suggests that domestication occurs over millennia, but genetic evidence indicates it can occur rapidly. We estimated that our wild and cultivated grape samples diverged ~22,000 years ago and that the cultivated lineage experienced a steady decline in population size (Ne) thereafter. The long decline may reflect low intensity management by humans prior to domestication. The second mystery is the identification of genes that contribute to domestication phenotypes. In cultivated grapes, we identified candidate-selected genes that function in sugar metabolism, flower development and stress responses. In contrast, candidate selected genes in the wild sample were limited to abiotic and biotic stress responses. A genomic region of high divergence corresponded to the sex determination region and included a candidate male sterility factor and additional genes with sex-specific expression. The third mystery concerns the cost of domestication. Annual crops accumulate putatively deleterious variants, in part due to strong domestication bottlenecks. The domestication of perennial crops differs from annuals in several ways, including the intensity of bottlenecks, and it is not yet clear if they accumulate deleterious variants. We found that grape accessions contained 5.2% more deleterious variants than wild individuals, and these were more often in a heterozygous state. Using forward simulations, we confirm that clonal propagation leads to the accumulation of recessive deleterious mutations but without decreasing fitness.Significance StatementWe generated genomic data to estimate the population history of grapes, the most economically important horticultural crop in the world. Domesticated grapes experienced a protracted, 22,000 year population decline prior to domestication; we hypothesize that this decline reflects low intensity cultivation by humans prior to domestication. Domestication altered the mating system of grapes. The sex determination region is detectable as a region of heightened genetic divergence between wild and cultivated accessions. Based on gene expression analyses, we propose new candidate genes that alter sex determination. Finally, grapes contain more deleterious mutations in heterozygous states than their wild ancestors. The accumulation of deleterious mutations is due in part to clonal propagation, which shelters deleterious, recessive mutations.
Riparian plant guilds become simpler and most likely fewer following flow regulation
Authors: Bejarano Maria Dolores , Nilsson Christer , Aguiar Francisca Constança 
Published: June 2017

Abstract

River regulation affects riparian systems world‐wide and conservation and restoration efforts are essential to retain biodiversity, and the functioning and services of riverine ecosystems. Effects of regulation on plant species richness have been widely addressed, but the filtering effect of regulation on guilds has received less attention.

We used a functional trait approach to identify adaptive plant strategies through regulation‐tolerant traits and predict shifts of riparian vegetation communities in response to regulation. We analysed variation in functional diversity across gradients of hydrological alteration in northern Sweden in relation to modified timing and infrequent major floods, along with frequent short‐term inundation.

Functional richness was similar in all study sites, but species richness declined with increasing intensity of regulation, and the species lost were largely functionally redundant (i.e. co‐existing species that have similar contribution to an ecosystem function). Guilds of species intolerant to waterlogging were particularly unsuccessful in most regulated sites as they were affected by hydropower dams which replace major fluvial disturbances with frequent short inundation events. We predict that this guild will disappear, with likely consequences for the entire riverine ecosystem.

Synthesis and applications. We conclude that functional traits tolerant to waterlogging or submergence and lack of major fluvial disturbances were key to understanding our results. We suggest that the functional trait approach can be integrated with knowledge of other ecosystem components to provide an understanding of ecosystem function that can be used to guide fluvial ecosystem management.
VapC toxins drive cellular dormancy under uranium stress for the extreme thermoacidophile Metallosphaera prunae
Authors: Mukherjee Arpan , Wheaton Garrett H. , Counts James A. , Ijeomah Brenda , Desai Jigar , Kelly Robert M. 
Published: June 2017

SummaryWhen abruptly exposed to toxic levels of hexavalent uranium, the extremely thermoacidophilic archaeon Metallosphaera prunae, originally isolated from an abandoned uranium mine, ceased to grow, and concomitantly exhibited heightened levels of cytosolic ribonuclease activity that corresponded to substantial degradation of cellular RNA. The M. prunae transcriptome during ‘uranium‐shock’ implicated VapC toxins as possible causative agents of the observed RNA degradation. Identifiable VapC toxins and PIN‐domain proteins encoded in the M. prunae genome were produced and characterized, three of which (VapC4, VapC7, VapC8) substantially degraded M. prunae rRNA in vitro. RNA cleavage specificity for these VapCs mapped to motifs within M. prunae rRNA. Furthermore, based on frequency of cleavage sequences, putative target mRNAs for these VapCs were identified; these were closely associated with translation, transcription, and replication. It is interesting to note that Metallosphaera sedula, a member of the same genus and which has a nearly identical genome sequence but not isolated from a uranium‐rich biotope, showed no evidence of dormancy when exposed to this metal. M. prunae utilizes VapC toxins for post‐transcriptional regulation under uranium stress to enter a cellular dormant state, thereby providing an adaptive response to what would otherwise be a deleterious environmental perturbation.
Mycobacterium bovis hosted by free‐living‐amoebae permits their long‐term persistence survival outside of host mammalian cells and remain capable of transmitting disease to mice
Authors: Sanchez‐Hidalgo Andrea , Obregón‐Henao Andrés , Wheat William H. , Jackson Mary , Gonzalez‐Juarrero Mercedes 
Published: June 2017

SummaryBovine tuberculosis (TB) is a zoonotic disease caused by Mycobacterium bovis. Despite intensive TB control campaigns, there are sporadic outbreaks of bovine TB in regions declared TB free. It is unclear how M. bovis is able to survive in the environment for long periods of time. We hypothesized that Free‐living amoebae (FLA), as ubiquitous inhabitants of soil and water, may act as long‐term reservoirs of M. bovis in the environment. In our model, M. bovis would be taken up by amoebal trophozoites, which are the actively feeding, replicating and mobile form of FLA. Upon exposure to hostile environmental conditions, infected FLA will encyst and provide an intracellular niche allowing their M. bovis cargo to persist for extended periods of time. Here, we show that five FLA species (Acanthamoeba polyphaga, Acanthamoeba castellanii, Acanthamoeba lenticulata, Vermamoeba vermiformis and Dictyostellium discoideum) are permissive to M. bovis infection and that the M. bovis bacilli may survive within the cysts of four of these species for over 60 days. We further show that exposure of M. bovis‐infected trophozoites and cysts to Balb/c mice leads to pulmonary TB. This work describes for the first time that FLA carrying M. bovis can transmit TB.
Quantitative biogeography of picoprasinophytes establishes ecotype distributions and significant contributions to marine phytoplankton
Authors: Limardo Alexander J. , Sudek Sebastian , Choi Chang Jae , Poirier Camille , Rii Yoshimi M. , Blum Marguerite , Roth Robyn , Goodenough Ursula , Church Matthew J. , Worden Alexandra Z. 
Published: June 2017

SummaryBathycoccus and Ostreococcus are broadly distributed marine picoprasinophyte algae. We enumerated small phytoplankton using flow cytometry and qPCR assays for phylogenetically distinct Bathycoccus clades BI and BII and Ostreococcus clades OI and OII. Among 259 photic‐zone samples from transects and time‐series, Ostreococcus maxima occurred in the North Pacific coastal upwelling for OI (36 713 ± 1485 copies ml−1) and the Kuroshio Front for OII (50 189 ± 561 copies ml−1) and the two overlapped only in frontal regions. The Bathycoccus overlapped more often with maxima along Line‐P for BI (10 667 ± 1299 copies ml−1) and the tropical Atlantic for BII (4125 ± 339 copies ml−1). Only BII and OII were detected at warm oligotrophic sites, accounting for 34 ± 13% of 1589 ± 448 eukaryotic phytoplankton cells ml−1 (annual average) at Station ALOHA's deep chlorophyll maximum. Significant distributional and molecular differences lead us to propose that Bathycoccus clade BII represents a separate species which tolerates higher temperature oceanic conditions than Bathycoccus prasinos (BI). Morphological differences were not evident, but quick‐freeze deep‐etch electron microscopy provided insight into Bathycoccus scale formation. Our results highlight the importance of quantitative seasonal abundance data for inferring ecological distributions and demonstrate significant, differential picoprasinophyte contributions in mesotrophic and open‐ocean waters.