bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential efficacies of Cas nucleases on microsatellites involved in human disorders and associated off-target mutations
Authors: Poggi Lucie , Emmenegger Lisa , Descorps-Declère Stéphane , Dumas Bruno , Richard Guy-Franck 
Published: December 2019

AbstractMicrosatellite expansions are the cause of more than 20 neurological or developmental human disorders. Shortening expanded repeats using specific DNA endonucleases may be envisioned as a gene editing approach. Here, a new assay was developed to test several CRISPR-Cas nucleases on microsatellites involved in human diseases, by measuring at the same time double-strand break rates, DNA end resection and homologous recombination efficacy. Broad variations in nuclease performances were detected on all repeat tracts.Streptococcus pyogenesCas9 was the most efficient of all. All repeat tracts did inhibit double-strand break resection. We demonstrate that secondary structure formation on the guide RNA was a major determinant of nuclease efficacy. Using deep sequencing, off-target mutations were assessed genomewide. Out of 221 CAG/CTG or GAA/TTC trinucleotide repeats of the yeast genome, three were identified as carrying statistically significant low frequency mutations, corresponding to off-target effects.
The rate of de novo CNVs in healthy controls
Authors: Barone Jacopo , Smith Mathew , Kendall Kimberley , Owen Michael J , O’Donovan Michael C , Kirov George 
Published: December 2019

AbstractBackgroundCopy number variation (CNV) is an important cause for human disease. Due to relatively high selection pressure operating against pathogenic CNVs, their rate is maintained in the population by de novo formation. The rates of de novo CNVs are increased in neurodevelopmental disorders. However only a few studies have been performed on relatively healthy individuals, making it problematic to calculate the magnitude of this increased rate.MethodsThe UK Biobank recruited about half a million randomly selected middle-aged members of the general population of the UK. We re-constructed family relationships from the genotypic data and identified 923 parent-offspring trios that passed out quality control filters. Potential de novo CNVs of >100 kb in size were identified and the log R ratios (LRR) and B allele frequency (BAF) traces of the trio members were visually inspected for those regions. We had no opportunity to validate CNVs with a laboratory method, but the traces appeared conclusive.Results and DiscussionWe identified 10 CNVs >100kb in size, a rate of 1.1%. These rates are very similar to those in previous large studies. Using previous large studies, we provide overall rates among 4844 trios for different size ranges that are expected in relatively healthy populations. These rates can be used for comparison in studies on disease populations.
The Role of Scale in the Estimation of Cell-type Proportions
Authors: Hunt Gregory J. , Gagnon-Bartsch Johann A. 
Published: December 2019

ABSTRACTComplex tissues are composed of a large number of different types of cells, each involved in a multitude of biological processes. Consequently, an important component to understanding such processes is understanding the cell-type composition of the tissues. Estimating cell type composition using high-throughput gene expression data is known as cell-type deconvolution. In this paper, we first summarize the extensive deconvolution literature by identifying a common regression-like approach to deconvolution. We call this approach the Unified Deconvolution-as-Regression (UDAR) framework. While methods that fall under this framework all use a similar model, they fit using data on different scales. Two popular scales for gene expression data are logarithmic and linear. Unfortunately, each of these scales has problems in the UDAR framework. Using log-scale gene expressions proposes a biologically implausible model and using linear-scale gene expressions will lead to statistically inefficient estimators. To overcome these problems, we propose a new approach for cell-type deconvolution that works on a hybrid of the two scales. This new approach is biologically plausible and improves statistical efficiency. We compare the hybrid approach to other methods on simulations as well as a collection of eleven real benchmark datasets. Here, we find the hybrid approach to be accurate and robust.deconvolution, gene expression, microarray, RNA-seq
PhenoMIP: High Throughput Phenotyping of Diverse C. elegans Populations via Molecular Inversion Probes
Authors: Mok Calvin , Belmarez Gabriella , Edgley Mark L. , Moerman Donald G. , Waterston Robert H. 
Published: December 2019

AbstractWhether generated within a lab setting or isolated from the wild, variant alleles continue to be an important resource for decoding gene function in model organisms such as Caenorhabditis elegans. With advances in massively parallel sequencing, multiple whole-genome sequenced (WGS) strain collections are now available to the research community. The Million Mutation Project (MMP) for instance, analysed 2007 N2-derived, mutagenized strains. Individually, each strain averages ∼400 single nucleotide variants amounting to ∼80 protein coding variants. The effects of these variants, however, remain largely uncharacterized and querying the breadth of these strains for phenotypic changes requires a method amenable to rapid and sensitive high-throughput analysis. Here we present a pooled competitive fitness approach to quantitatively phenotype subpopulations of sequenced collections via molecular inversion probes (PhenoMIP). We phenotyped the relative fitness of 217 mutant strains on multiple food sources and classified these into five categories. We also demonstrate on a subset of these strains, that their fitness defects can be genetically mapped. Overall, our results suggest that approximately 80% of MMP mutant strains may have a decreased fitness relative to the lab reference, N2. The costs of generating this form of analysis through WGS methods would be prohibitive while PhenoMIP analysis in this manner is accomplished at less than 1% of projected WGS costs. We propose methods for applying PhenoMIP to a broad range of population selection experiments in a cost-efficient manner that would be useful to the community at large.
Brain DNA Methylation Patterns in CLDN5 Associated With Cognitive Decline
Authors: Hüls Anke , Robins Chloe , Conneely Karen N. , Edgar Rachel , De Jager Philip L. , Bennett David A. , Wingo Aliza P. , Epstein Michael P. , Wingo Thomas S. 
Published: December 2019

AbstractObjectiveCognitive decline is a hallmark of dementia; however, the brain epigenetic signature of cognitive decline is unclear. We investigated the associations between brain tissue-based DNA methylation and cognitive trajectory.MethodsWe performed a brain epigenome-wide association study of cognitive trajectory in 636 participants from the Religious Order Study and the Rush Memory and Aging Project (ROS/MAP) using DNA methylation profiles of the dorsal lateral prefrontal cortex (dPFC). To maximize our power to detect epigenetic associations, we used the recently developed Gene Association with Multiple Traits (GAMuT) test to analyze the five measured cognitive domains simultaneously.ResultsWe found an epigenome-wide association for differential methylation of sites in the Claudin-5 (CLDN5) locus and cognitive trajectory (p-value x 9.96 × 10-7), which was robust to adjustment for cell type proportions (p-value = 8.52 x 10-7). This association was primarily driven by association with declines in episodic (p-value = 4.65 x 10-6) and working memory (p-value = 2.54 x 10-7). This association between methylation in CLDN5 and cognitive decline was independent of beta-amyloid and neurofibrillary tangle pathology and present in participants with low levels of neuropathology. In addition, only 13-31% of the association between methylation and cognitive decline was mediated through levels of neuropathology, whereas the major part of the association was independent of it.InterpretationWe identified methylation in CLDN5 as new epigenetic factor associated with cognitive trajectory. Higher levels of methylation in CLDN5 were associated with faster cognitive decline implicating the blood brain barrier in maintenance of cognitive trajectory.
Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data
Authors: Kember Rachel L. , Merikangas Alison K. , Verma Shefali S. , Verma Anurag , Judy Renae ,   Regeneron Genetics Center, Damrauer Scott M. , Ritchie Marylyn D. , Rader Daniel J. , Bućan Maja 
Published: December 2019

AbstractObjectivePrediction of disease risk is a key component of precision medicine. Common, complex traits such as psychiatric disorders have a complex polygenic architecture making the identification of a single risk predictor difficult. Polygenic risk scores (PRS) denoting the sum of an individual’s genetic liability for a disorder are a promising biomarker for psychiatric disorders, but require evaluation in a clinical setting.MethodsWe develop PRS for six psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, anorexia nervosa) and 17 non-psychiatric traits in over 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We perform phenome-wide association analyses to test their association across disease categories.ResultsFour of the six psychiatric PRS were associated with their primary phenotypes (odds ratios between 1.2-1.6). Individuals in the highest quintile of risk had between 1.4-2.9 times higher odds of the disorder than the remaining 80% of individuals. Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRS for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder.ConclusionsWe demonstrate that the genetic architecture of common psychiatric disorders identified in a clinical setting confirms that which has been derived from large consortia. Even though the risk associated is low in this context, these results suggest that as identification of genetic markers proceeds, PRS is a promising approach for prediction of psychiatric disorders and associated conditions in clinical registries.
Sequencing Chemically Induced Mutations in the Mutamouse Lacz Reporter Gene Identifies Human Cancer Mutational Signatures
Authors: Beal Marc A. , Meier Matt J. , LeBlanc Danielle , Maurice Clotilde , O’Brien Jason , Yauk Carole L. , Marchetti Francesco 
Published: December 2019

ABSTRACTTransgenic rodent (TGR) models use bacterial reporter genes to quantifyin vivomutagenesis. Pairing TGR assays with next-generation sequencing (NGS) enables comprehensive mutation spectrum analysis to inform mutational mechanisms. We used this approach to identify 2,751 independentlacZmutations in the bone marrow of MutaMouse animals exposed to four chemical mutagens: benzo[a]pyrene,N-ethyl-N-nitrosourea, procarbazine, and triethylenemelamine. We also collected published data for 706lacZmutations from eight additional environmental mutagens. We demonstrate thatlacZgene sequencing generates chemical-specific mutation signatures observed in human cancers with established environmental causes. For example, the mutation signature of benzo[a]pyrene, a potent carcinogen in tobacco smoke, matched the signature associated with tobacco-induced lung cancers. Our results show that the analysis of chemically induced mutations in thelacZgene shortly after exposure provides an effective approach to characterize human-relevant mechanisms of carcinogenesis and identify novel environmental causes of mutation signatures observed in human cancers.
Developmental plasticity ofBrachypodium distachyonin response to P deficiency: modulation by inoculation with phosphate-solubilizing bacteria
Authors: Baudson Caroline , Delory Benjamin M. , Spaepen Stijn , du Jardin Patrick , Delaplace Pierre 
Published: December 2019

AbstractBackgroundMineral P fertilisers must be used wisely in order to preserve rock phosphate, a limited and non-renewable resource. The use of bio-inoculants to improve soil nutrient availability and trigger an efficient plant response to nutrient deficiency is one potential strategy in the attempt to decrease P inputs in agriculture.MethodA gnotobiotic co-cultivation system was used to study the response ofBrachypodium distachyonto contrasted P supplies (soluble and poorly soluble forms of P) and inoculation with P solubilizing bacteria.Brachypodium’s responses to P conditions and inoculation with bacteria were studied in terms of developmental plasticity and P use efficiency.ResultsBrachypodiumshowed plasticity in its biomass allocation pattern in response to variable P conditions, specifically by prioritizing root development over shoot productivity under poorly soluble P conditions. Despite the ability of the bacteria to solubilize P, shoot productivity was depressed in plants inoculated with bacteria, although the root system development was maintained. The negative impact of bacteria on biomass production inBrachypodiummight be attributed to inadequate C supply to bacteria, an increased competition for P between both organisms under P-limiting conditions, or an accumulation of toxic bacterial metabolites in our cultivation system. Both P and inoculation treatments impacted root system morphology. The modulation ofBrachypodium’s developmental response to P supplies by P solubilizing bacteria did not lead to improved P use efficiency.ConclusionOur results support the hypothesis that plastic responses ofBrachypodiumcultivated under P-limited conditions are modulated by P solubilizing bacteria. The considered experimental context impacts plant–bacteria interactions. Choosing experimental conditions as close as possible to real ones is important in the selection of P solubilizing bacteria. Both persistent homology and allometric analyses proved to be useful tools that should be considered when studying the impact of bio-inoculants on plant development in response to varying nutritional context.
Construction of an inducible amyloid expression circuit in Bacillus megaterium: A case study with CsgA and TasA
Authors: Larsson Elin M. , McManus John B. , Murray Richard M. 
Published: December 2019

AbstractEnvironmental applications of synthetic biology such as water remediation require engineered strains to function robustly in a fluctuating and potentially hostile environment. The construction of synthetic biofilm formation circuits could potentially alleviate this issue by promoting cell survival. Towards this end, we construct a xylose-inducible system for the expression of the functional amyloids CsgA and TasA in the soil bacterium Bacillus megaterium. We find that although both amyloids are expressed, only TasA is successfully exported from the cells. Furthermore, expression of CsgA results in a significant growth penalty for the cells while expression of TasA does not. Finally, we show that TasA expression conveys a small but detectable increase in cells’ adhesion to nickel beads. These results suggest that TasA is a promising candidate for future work on synthetic biofilm formation in B. megaterium.
Fast and Accurate Exhaustive Higher-Order Epistasis Search with BitEpi
Authors: Bayat Arash , Hosking Brendan , Jain Yatish , Hosking Cameron , Kodikara Milindi , Reti Daniel , Twine Natalie A. , Bauer Denis C. 
Published: December 2019

AbstractMotivationComplex genetic diseases may be modulated by a large number of epistatic interactions affecting a polygenic phenotype. Identifying these interactions is difficult due to computational complexity, especially in the case of higher-order interactions where more than two genomic variants are involved.ResultsIn this paper, we present BitEpi, a fast and accurate method to test all possible combinations of up to four bi-allelic variants (i.e. Single Nucleotide Variant or SNV for short). BitEpi introduces a novel bitwise algorithm that is 2.1 and 56 times faster for 3-SNV and 4-SNV search, than established software. The novel entropy statistic used in BitEpi is 44% more accurate to identify interactive SNVs, incorporating a p-value-based significance testing. We demonstrate BitEpi on real world data of 4,900 samples and 87,000 SNPs. We also present EpiExplorer to visualize the potentially large number of individual and interacting SNVs in an interactive Cytoscape graph. EpiExplorer uses various visual elements to facilitate the discovery of true biological events in a complex polygenic environment.
The Structural Basis for Glycerol Permeation by human AQP7
Authors: Zhang Li , Yao Deqiang , Zhou Fu , Zhang Qing , Xia Ying , Wang Qian , Qin An , Zhao Jie , Li Dianfan , Zhou Lu , Cao Yu 
Published: December 2019

AbstractHuman glycerol channel AQP7 conducts glycerol release from adipocyte and entry into the cells in pancreatic islets, muscles and kidney tubule, and thus regulate glycerol metabolism in those tissues. Compared with other human aquaglyceroporins, AQP7 shows a less conserved “NPA” motif in the center cavity, and a pair of aromatic residues at Ar/R selectivity filter. To understand the structural basis for the glycerol conductance, we crystallized the human AQP7 and determined the structure at 3.7 Å. A substrate binding pocket was found near to the Ar/R filter and the bound glycerol molecule stabilized by R229. In vivo functional assay on human AQP7 as well as AQP3 and AQP10 demonstrated strong glycerol transportation activities at physiological condition. The human AQP7 structure reveals a fully closed conformation with its permeation pathway strictly confined by Ar/R filter at the exoplasmic side and the gate at the cytoplasmic side, and the dislocation of the residues at narrowest parts of glycerol pathway in AQP7 play a critical role in controlling the glycerol flux.
Age-related compensatory reconfiguration of PFC connections during episodic memory retrieval
Authors: Deng Lifu , Stanley Mathew L. , Monge Zachary A. , Wing Erik A. , Geib Benjamin R. , Davis Simon W. , Cabeza Roberto 
Published: December 2019

AbstractDuring demanding cognitive tasks, older adults (OAs) frequently show greater prefrontal cortex (PFC) activity than younger adults (YAs). This age-related PFC activity increase is often associated with enhanced cognitive performance, suggesting functional compensation. However, the brain is a complex network of interconnected regions, and it is unclear how network connectivity of PFC regions differs for OAs vs. YAs. To investigate this, we examined the age-related difference in functional brain network mediating episodic memory retrieval. YAs and OAs participants encoded and then recalled visual scenes, and age-related differences in network topology during memory retrieval were investigated as a function of memory performance. We measured both quantitative changes in functional integration and qualitative reconfiguration in connectivity patterns. The study yielded three main findings. First, PFC regions were more functionally integrated with the rest of the brain network in OAs. Critically, this age-related increase in PFC integration was associated with better retrieval performance. Second, PFC regions showed stronger performance-related reconfiguration of connectivity patterns in OAs. Finally, the magnitude of PFC reconfiguration increases in OAs tracked reconfiguration reductions in the medial temporal lobe (MTL) – a core episodic memory region, suggesting that PFC connectivity in OAs may be compensating for MTL deficits.
Testing the effectiveness of principal components in adjusting for relatedness in genetic association studies
Authors: Yao Yiqi , Ochoa Alejandro 
Published: December 2019

AbstractModern genetic association studies require modeling population structure and family relatedness in order to calculate correct statistics. Principal Components Analysis (PCA) is one of the most common approaches for modeling this population structure, but nowadays the Linear Mixed-Effects Model (LMM) is believed by many to be a superior model. Remarkably, previous comparisons have been limited by testing PCA without varying the number of principal components (PCs), by simulating unrealistically simple population structures, and by not always measuring both type-I error control and predictive power. In this work, we thoroughly evaluate PCA with varying number of PCs alongside LMM in various realistic scenarios, including admixture together with family structure, measuring both null p-value uniformity and the area under the precision-recall curves. We find that PCA performs as well as LMM when enough PCs are used and the sample size is large, and find a remarkable robustness to extreme number of PCs. However, we notice decreased performance for PCA relative to LMM when sample sizes are small and when there is family structure, although LMM performance is highly variable. Altogether, our work suggests that PCA is a favorable approach for association studies when sample sizes are large and no close relatives exist in the data, and a hybrid approach of LMM with PCs may be the best of both worlds.
Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models
Authors: Zhang Jie , Petersen Søren D. , Radivojevic Tijana , Ramirez Andrés , Pérez Andrés , Abeliuk Eduardo , Sánchez Benjamín J. , Costello Zachary , Chen Yu , Fero Mike , Martin Hector Garcia , Nielsen Jens , Keasling Jay D. , Jensen Michael K. 
Published: December 2019

SUMMARYIn combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can complement each other and be used in a combined approach to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets and produce a large combinatorial library of metabolic pathway designs with different promoters which, once phenotyped, provide the basis for machine learning algorithms to be trained and used for new design recommendations. The approach enables successful forward engineering of aromatic amino acid metabolism in yeast, with the new recommended designs improving tryptophan production by up to 17% compared to the best designs used for algorithm training, and ultimately producing a total increase of 106% in tryptophan accumulation compared to optimized reference designs. Based on a single high-throughput data-generation iteration, this study highlights the power of combining mechanistic and machine learning models to enhance their predictive power and effectively direct metabolic engineering efforts.