bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reconstructing the human first trimester fetal–maternal interface using single cell transcriptomics
Authors: Vento-Tormo Roser , Efremova Mirjana , Botting Rachel A. , Turco Margherita Y. , Vento-Tormo Miquel , Meyer Kerstin B. , Park Jongeun , Stephenson Emily , Polański Krzysztof , Payne Rebecca P. , Goncalves Angela , Zou Angela , Henriksson Johan , Wood Laura , Lisgo Steve , Filby Andrew , Wright Gavin J. , Stubbington Michael J. T. , Haniffa Muzlifah , Moffett Ashley , Teichmann Sarah A. 
Published: September 2018

SummaryDuring the early weeks of human pregnancy, the fetal placenta implants into the uterine mucosa (decidua) where placental trophoblast cells intermingle and communicate with maternal cells. Here, we profile transcriptomes of ∼50,000 single cells from this unique microenvironment, sampling matched first trimester maternal blood and decidua, and fetal cells from the placenta itself. We define the cellular composition of human decidua, revealing five distinct subsets of decidual fibroblasts with differing growth factors and hormone production profiles, and show that fibroblast states define two distinct decidual layers. Among decidual NK cells, we resolve three subsets, each with a different immunomodulatory and chemokine profile. We develop a repository of ligand-receptor pairs (www.CellPhoneDB.org) and a statistical tool to predict the probability of cell-cell interactions via these pairs, highlighting specific interactions between decidual NK cells and invading fetal extravillous trophoblast cells, maternal immune and stromal cells. Our single cell atlas of the maternal-fetal interface reveals the cellular organization and interactions critical for placentation and reproductive success.
Alternative translation initiation generates a functionally distinct isoform of the stress-activated kinase MK2
Authors: Trulley Philipp , Snieckute Goda , Bekker-Jensen Dorte , Menon Manoj B. , Freund Robert , Kotlyarov Alexey , Olsen Jesper V. , Diaz-Muñoz Manuel D. , Turner Martin , Bekker-Jensen Simon , Gaestel Matthias , Tiedje Christopher 
Published: September 2018

AbstractShaping of the proteome by alternative translation is an important mechanism of post-transcriptional gene regulation. It can lead to the expression of multiple protein isoforms originating from the same mRNA. Here we show that a novel, abundant and long isoform of the stress/p38MAPK-activated kinase MK2, a key regulator of transcription, migration, death signaling and post-transcriptional gene regulation, is constitutively translated from an alternative CUG translation initiation start site located in the 5′UTR of its mRNA. GC-rich sequences and putative G-quadruplex structures influence the usage of that codon as a translation initiation start site and the RNA helicase eIF4A1 is needed to ensure alternative isoform translation. We recapitulated the usage of the alternative start codon and determined the molecular properties of the short and a long MK2 isoforms. Phenotypically, only the short isoform phosphorylated Hsp27, supported migration and stress-induced immediate early gene (IEG) expression. Interaction profiling by quantitative mass-spectrometry revealed short isoform-specific binding partners that were associated with migration. In contrast, the long isoform contains additional putative phosphorylation sites in its unique N-terminus. In sum, our data reveal a longer and previously non-described isoform of MK2 with distinct physiological properties originating from alternative translation.
Group ICA for Identifying Biomarkers in Schizophrenia: ‘Adaptive’ Networks via Spatially Constrained ICA Show More Sensitivity to Group Differences than Spatio-temporal Regression
Authors: Salman Mustafa S , Du Yuhui , Lin Dongdong , Fu Zening , Damaraju Eswar , Sui Jing , Chen Jiayu , Yu Qingbao , Mayer Andrew , Posse Stefan , Mathalon Daniel , Ford Judith M. , Van Erp Theodorus , Calhoun Vince D 
Published: September 2018

AbstractBrain functional networks identified from fMRI data can provide potential biomarkers for brain disorders. Group independent component analysis (GICA) is popular for extracting brain functional networks from multiple subjects. In GICA, different strategies exist for reconstructing subject-specific networks from the group-level networks. However, it is unknown whether these strategies have different sensitivities to group differences and abilities in distinguishing patients. Among GICA, spatio-temporal regression (STR) and spatially constrained ICA approaches such as group information guided ICA (GIG-ICA) can be used to propagate components (indicating networks) to a new subject that is not included in the original subjects. In this study, based on the same a priori network maps, we reconstructed subject-specific networks using these two methods separately from resting-state fMRI data of 151 schizophrenia patients (SZs) and 163 healthy controls (HCs). We investigated group differences in the estimated functional networks and the functional network connectivity (FNC) obtained by each method. The networks were also used as features in a cross-validated support vector machine (SVM) for classifying SZs and HCs. We selected features using different strategies to provide a comprehensive comparison between the two methods. GIG-ICA generally showed greater sensitivity in statistical analysis and better classification performance (accuracy 76.45±8.9%, sensitivity 0.74±0.11, specificity 0.79±0.11) than STR (accuracy 67.45±8.13%, sensitivity 0.65±0.11, specificity 0.71±0.11). Importantly, results were also consistent when applied to an independent dataset including 82 HCs and 82 SZs. Our work suggests that the functional networks estimated by GIG-ICA are more sensitive to group differences, and GIG-ICA is promising for identifying image-derived biomarkers of brain disease.
Pathogen Detection and Microbiome Analysis of Infected Wheat Using a Portable DNA Sequencer
Authors: Hu Yiheng , Green Gamran S. , Milgate Andrew W. , Stone Eric A. , Rathjen John P. , Schwessinger Benjamin 
Published: September 2018

ABSTRACTFungal diseases of plants are responsible for major losses in agriculture, highlighting the need for rapid and accurate identification of plant pathogens. Disease outcomes are often defined not only by the main pathogen but are influenced by diverse microbial communities known as the microbiome at sites of infection. Here we present the first use of whole genome shot-gun sequencing with a portable DNA sequencing device as a method for the detection of fungal pathogens from wheat(Triticum aestivum)in a standard molecular biology laboratory. The data revealed that our method is robust and applicable to the diagnosis of fungal diseases including wheat stripe rust (caused byPuccinia striiformisf. sp.tritici),septoria tritici blotch (caused byZymoseptoria tritici)and yellow leaf spot (caused byPyrenophora tritici repentis).We also identified the bacterial genusPseudomonasco-present withPucciniaandZymoseptoriabut notPyrenophorainfections. One limitation of the method is the over-representation of redundant wheat genome sequences from samples. This could be addressed by long-range amplicon-based sequencing approaches in future studies, which specifically target non-host organisms. Our work outlines a new approach for detection of a broad range of plant pathogens and associated microbes using a portable sequencer in a standard laboratory, providing the basis for future development of an on-site disease monitoring system.
Comparison of tri-exponential decay vs. bi-exponential decay and full fitting vs. segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI
Authors: Chevallier Olivier , Zhou Nan , Cercueil Jean-Pierre , He Jian , Loffroy Romaric , Wáng Yì Xiáng J. 
Published: September 2018

AbstractPurposeTo determine whether bi- or tri-exponential models, and full or segmented fittings, better fit IVIM imaging signal of healthy livers.Materials and methodsDiffusion-weighted images were acquired with a 3-T scanner using respiratory-triggered echo-planar sequence and 16 b-values (0∼800 s/mm2). Eighteen healthy volunteers had liver scanned twice in the same session, and then once again in another session. Region of interest (ROI)-based measurements were processed with bi-exponential model full fitting and segmented fitting (threshold b-value = 80 s/mm2), as well as tri-exponential model full fitting and segmented fitting (threshold b-value = 200 s/mm2).ResultsWith all scans’ signal averaged, bi-exponential model full fitting showed Dslow=1.14, Dfast=193.6×10-3 mm2/s, and PF=16.9%, and segmented fitting showed Dslow=1.03, Dfast=56.7×10-3 mm2/s, and PF=21.3%. IVIM parameters derived from tri-exponential model were similar for full fitting and segmented fitting, with a slow (D’slow=0.98×10-3 mm2/s; F’slow=76.4 or 76.6%), a fast (D’fast=15.1 or 15.4×10-3 mm2/s; F’fast=11.8 or 11.7%) and a very fast (D’Vfast=445.0 or 448.8×10-3 mm2/s; F’Vfast=11.8 or 11.7 %) diffusion compartments. Tri-exponential model provided an overall better fit than bi-exponential model. For bi-exponential model, full fitting provided better fit at very low and low b-values compared with segmented fitting with the later tended to underestimate Dfast, however, segmented method demonstrated lower error in signal prediction for high b-values. Compared with full fitting, tri-exponential segmented fitting offered better scan-rescan reproducibility.ConclusionFor healthy liver, tri-exponential modelling is preferred than bi-exponential modelling. For bi-exponential model, segmented fitting underestimates Dfast, but offers more accurate estimation of Dslow.
LTMG: A novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data
Authors: Wan Changlin , Chang Wennan , Zhang Yu , Shah Fenil , Lu Xiaoyu , Zang Yong , Zhang Anru , Cao Sha , Fishel Melissa L. , Ma Qin , Zhang Chi 
Published: September 2018

ABSTRACTA key challenge in modeling single-cell RNA-seq (scRNA-seq) data is to capture the diverse gene expression states regulated by different transcriptional regulatory inputs across single cells, which is further complicated by a large number of observed zero and low expressions. We developed a left truncated mixture Gaussian (LTMG) model that stems from the kinetic relationships between the transcriptional regulatory inputs and metabolism of mRNA and gene expression abundance in a cell. LTMG infers the expression multi-modalities across single cell entities, representing a gene’s diverse expression states; meanwhile the dropouts and low expressions are treated as left truncated, specifically representing an expression state that is under suppression. We demonstrated that LTMG has significantly better goodness of fitting on an extensive number of single-cell data sets, comparing to three other state of the art models. In addition, our systems kinetic approach of handling the low and zero expressions and correctness of the identified multimodality are validated on several independent experimental data sets. Application on data of complex tissues demonstrated the capability of LTMG in extracting varied expression states specific to cell types or cell functions. Based on LTMG, a differential gene expression test and a co-regulation module identification method, namely LTMG-DGE and LTMG-GCR, are further developed. We experimentally validated that LTMG-DGE is equipped with higher sensitivity and specificity in detecting differentially expressed genes, compared with other five popular methods, and that LTMG-GCR is capable to retrieve the gene co-regulation modules corresponding to perturbed transcriptional regulations. A user-friendly R package with all the analysis power is available at https://github.com/zy26/LTMGSCA.
SMARTer single cell total RNA sequencing
Authors: Karen Verboom , Celine Everaert , Nathalie Bolduc , Kenneth Livak J. , Nurten Yigit , Dries Rombaut , Jasper Anckaert , Morten Venø T , Jørgen Kjems , Frank Speleman , Pieter Mestdagh , Jo Vandesompele 
Published: September 2018

AbstractSingle cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3’ end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes.
Specificity for deubiquitination of monoubiquitinated FANCD2 is driven by the N-terminus of USP1
Authors: Arkinson Connor , Chaugule Viduth K. , Toth Rachel , Walden Helen 
Published: September 2018

AbstractThe DNA damage response depends on ubiquitin signalling to orchestrate DNA repair. The Fanconi Anemia pathway for interstrand crosslink repair, and the translesion synthesis pathway for DNA damage tolerance, both require cycles of monoubiquitination and deubiquitination. The ubiquitin specific protease USP1 regulates both these pathways by deubiquitinating monoubiquitinated PCNA, FANCD2 and FANCI. Loss of USP1 activity gives rise to chromosomal instability. While many USPs hydrolyse ubiquitin-ubiquitin linkages, USP1 targets ubiquitin-substrate conjugates at specific sites. The molecular basis of USP1’s specificity for multiple substrates is poorly understood. Here we show that the molecular determinants for substrate deubiquitination by USP1 reside within the highly conserved and extended N-terminus. We find that the N-terminus of USP1 harbours a FANCD2-specific binding sequence required for deubiquitination of K561 on FANCD2. In contrast, the N-terminus is not required for PCNA or FANCI deubiquitination. Furthermore, we show that the N-terminus of USP1 is sufficient to engineer specificity in a more promiscuous USP.
Mutational impact of culturing human pluripotent and adult stem cells
Authors: Kuijk Ewart , Jager Myrthe , Roest Bastiaan van der , Locati Mauro , Hoeck Arne Van , Korzelius Jerome , Janssen Roel , Besselink Nicolle , Boymans Sander , Boxtel Ruben van , Cuppen Edwin 
Published: September 2018

AbstractGenetic changes acquired during in vitro culture pose a potential risk for the successful application of stem cells in regenerative medicine. To assess mutation accumulation risks induced by culturing, we determined genetic aberrations in individual human induced pluripotent stem cells (iPS cells) and adult stem cells (ASCs) by whole genome sequencing analyses. Individual iPS cells, intestinal ASCs and liver ASCs accumulated 3.5±0.5, 7.2±1.0 and 8.4±3.6 base substitutions per population doubling, respectively. The annual in vitro mutation accumulation rate of ASCs adds up to ∼1600 base pair substitutions, which is ∼40-fold higher than the in vivo rate of ∼40 base pair substitutions per year. Mutational analysis revealed a distinct in vitro induced mutational signature that is irrespective of stem cell type and distinct from the in vivo mutational signature. This in vitro signature is characterized by C to A changes that have previously been linked to oxidative stress conditions. Additionally, we observed stem cell-specific mutational signatures and differences in transcriptional strand bias, indicating differential activity of DNA repair mechanisms between stem cell types in culture. We demonstrate that the empirically defined mutation rates, spectra, and genomic distribution enable risk assessment by modelling the accumulation of specific oncogenic mutations during typical in vitro expansion, manipulation or screening experiments using human stem cells. Taken together, we have here for the first time accurately quantified and characterized in vitro mutation accumulation in human iPS cells and ASCs in a direct comparison. These results provide insights for further optimization of culture conditions for safe in vivo utilization of these cell types for regenerative purposes.
Fine-scale recombination landscapes between a freshwater and marine population of threespine stickleback fish
Authors: Shanfelter Alice F. , Archambeault Sophie L. , White Michael A. 
Published: September 2018

AbstractMeiotic recombination is a highly conserved process that has profound effects on genome evolution. Recombination rates can vary drastically at a fine-scale across genomes and often localize to small recombination “hotspots” with highly elevated rates surrounded by regions with little recombination. Hotspot targeting to specific genomic locations is variable across species. In some mammals, hotspots have divergent landscapes between closely related species which is directed by the binding of the rapidly evolving protein, PRDM9. In many species outside of mammals, hotspots are generally conserved and tend to localize to regions with open chromatin such as transcription start sites. It remains unclear if the location of recombination hotspots diverge in taxa outside of mammals. Threespine stickleback fish (Gasterosteus aculeatus) are an excellent model to examine the evolution of recombination over short evolutionary timescales. Using an LD-based approach, we found recombination rates varied at a fine-scale across the genome, with many regions organized into narrow hotspots. Hotspots had divergent landscapes between stickleback populations, where only ~15% were shared, though part of this divergence could be due to demographic history. Additionally, we did not detect a strong association of PRDM9 with recombination hotspots in threespine stickleback fish. Our results suggest fine-scale recombination rates may be diverging between closely related populations of threespine stickleback fish and argue for additional molecular characterization to verify the extent of the divergence.
Escalation and constraints of antagonistic armaments in water striders
Authors: Crumière Antonin Jean Johan , Armisén David , Vargas-Lowman Aïdamalia , Kubarakos Martha , Moreira Felipe Ferraz Figueiredo , Khila Abderrahman 
Published: September 2018

AbstractSexual conflict may result in the escalating coevolution of sexually antagonistic traits. However, our understanding of the evolutionary dynamics of antagonistic traits and their role in association with sex-specific escalation remains limited. Here we study sexually antagonistic coevolution in a genus of water striders calledRhagovelia. We identified a set of male grasping traits and female anti-grasping traits used during pre-mating struggles and show that natural variation of these traits is associated with variation in mating performance in the direction expected for antagonistic co-evolution. Phylogenetic mapping detected signals of escalation of these sexually antagonistic traits suggesting an ongoing arms race. Moreover, their escalation appears to be constrained by a trade-off with dispersal through flight in both sexes. Altogether our results highlight how sexual interactions may have shaped sex-specific antagonistic traits and how constraints imposed by natural selection may have influenced their evolution.
Lovastatin, not simvastatin, corrects core phenotypes in the fragile X mouse model
Authors: Muscas Melania , Louros Susana R. , Osterweil Emily K. 
Published: September 2018

AbstractThe cholesterol-lowering drug lovastatin corrects neurological phenotypes in animal models of fragile X syndrome (FX), a commonly identified genetic cause of autism and intellectual disability. The therapeutic efficacy of lovastatin is being tested in clinical trials for FX, however the structurally similar drug simvastatin has been proposed as an alternative due to an increased potency and brain penetrance. Here, we perform a side-by-side comparison of the effects of lovastatin and simvastatin treatment on two core phenotypes in the Fmr1-/y mouse model. We find that while lovastatin normalizes excessive hippocampal protein synthesis and reduces audiogenic seizures (AGS) in the Fmr1-/y mouse, simvastatin does not correct either phenotype. These results caution against the assumption that simvastatin is a valid alternative to lovastatin for the treatment of FX.
Plants maximize competition while minimizing competitors belowground: a theoretical analysis of incentives for root competition in space
Authors: Farrior Caroline E. 
Published: September 2018

AbstractRecent research shows that shared access to belowground resources drives plants to overproliferate fine roots competitively, limiting community-level aboveground biomass. Models of this phenomenon are commonly based on an assumption that belowground resources and fine roots are thoroughly well mixed. In reality, of course, fine roots are spatially structured by individual. Here we investigate how costs of sending roots through horizontal space influence incentives for fine-root overproliferation. We find that these costs restrain overproliferation to the net benefit of community aboveground biomass. And further, the costs eliminate incentives for individuals to grow fine roots beyond their closest neighbors. Plants that interact with the fewest competitors benefit the most in relative fitness from overproliferation of fine roots. Effectively, individual-based optimization of root allocation in space increases the effects of competition while decreasing the number of individual competitors for each individual.Because an individual’s optimal competitive network consists of only the closest neighbors, we predict the full effects of competition are achieved just shortly after disturbance, making competition belowground an almost inescapable pressure on plants. Together these results have important implications for predicting plant interaction networks, patterns of carbon allocation, and ecosystem carbon storage.
Panton-Valentine leucocidin is the key determinant of Staphylococcus aureus pyomyositis in a bacterial genome-wide association study
Authors: Young Bernadette C , Earle Sarah G , Soeng Sona , Sar Poda , Kumar Varun , Hor Songly , Sar Vuthy , Bousfield Rachel , Sanderson Nicholas D , Barker Leanne , Stoesser Nicole , Emary Katherine RW , Parry Christopher M , Nickerson Emma K , Turner Paul , Bowden Rory , Crook Derrick , Wyllie David , Day Nicholas PJ , Wilson Daniel J , Moore Catrin E 
Published: September 2018

AbstractPyomyositis is a severe bacterial infection of skeletal muscle, commonly affecting children in tropical regions and predominantly caused by Staphylococcus aureus. To understand the contribution of bacterial genomic factors to pyomyositis, we conducted a genome-wide association study of S. aureus cultured from 101 children with pyomyositis and 417 children with asymptomatic nasal carriage attending the Angkor Hospital for Children in Cambodia. We found a strong relationship between bacterial genetic variation and pyomyositis, with estimated heritability 63.8% (95% CI 49.2-78.4%). The presence of the Panton-Valentine leucocidin (PVL) locus increased the odds of pyomyositis 130-fold (p =10-17.9). The signal of association mapped both to the PVL-coding sequence and the sequence immediately upstream. Together these regions explained > 99.9% of heritability. Our results establish staphylococcal pyomyositis, like tetanus and diphtheria, as critically dependent on expression of a single toxin and demonstrate the potential for association studies to identify specific bacterial genes promoting severe human disease.