bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fast and accurate shared segment detection and relatedness estimation in un-phased genetic data using TRUFFLE
Authors: Dimitromanolakis Apostolos , Paterson Andrew D. , Sun Lei 
Published: November 2018

AbstractRelationship estimation and segment detection between individuals is an important aspect of disease gene mapping. Existing methods are either tailored for computational efficiency, or require phasing to improve accuracy. We developed TRUFFLE, a method that integrates computational techniques and statistical principles for the identification and visualization of identity-by-descent (IBD) segments using un-phased data. By skipping the haplotype phasing step and, instead, relying on a simpler region-based approach, our method is computationally efficient while maintaining inferential accuracy. In addition, an error model corrects for segment break-ups that occur as a consequence of genotyping errors. TRUFFLE can estimate relatedness for 3.1 million pairs from the 1000 Genomes Project data in a few minutes on a typical laptop computer. Consistent with expectation, we identified only three second cousin or closer pairs across different populations, while commonly used methods identified a large number of such pairs. Similarly, within populations, we identified much fewer related pairs. Compared to methods relying on phased data, TRUFFLE has comparable accuracy but is drastically faster and has fewer broken segments. We also identified specific local genomic regions that are commonly shared within populations, suggesting selection. When applied to pedigree data, we observed 99.6% accuracy in detecting 1st to 5th degree relationships. As genomic datasets become much larger, TRUFFLE can enable disease gene mapping through implicit shared haplotypes by accurate IBD segment detection.
NeuroRoots, a bio-inspired, seamless Brain Machine Interface device for long-term recording
Authors: Ferro Marc D. , Proctor Christopher M. , Gonzalez Alexander , Zhao Eric , Slezia Andrea , Pas Jolien , Dijk Gerwin , Donahue Mary J. , Williamson Adam , Malliaras Georges G. , Giocomo Lisa , Melosh Nicholas A. 
Published: November 2018

AbstractMinimally invasive electrodes of cellular scale that approach a bio-integrative level of neural recording could enable the development of scalable brain machine interfaces that stably interface with the same neural populations over long period of time.In this paper, we designed and created NeuroRoots, a bio-mimetic multi-channel implant sharing similar dimension (10µm wide, 1.5µm thick), mechanical flexibility and spatial distribution as axon bundles in the brain. A simple approach of delivery is reported based on the assembly and controllable immobilization of the electrode onto a 35µm microwire shuttle by using capillarity and surface-tension in aqueous solution. Once implanted into targeted regions of the brain, the microwire was retracted leaving NeuroRoots in the biological tissue with minimal surgical footprint and perturbation of existing neural architectures within the tissue. NeuroRoots was implanted using a platform compatible with commercially available electrophysiology rigs and with measurements of interests in behavioral experiments in adult rats freely moving into maze. We demonstrated that NeuroRoots electrodes reliably detected action potentials for at least 7 weeks and the signal amplitude and shape remained relatively constant during long-term implantation.This research represents a step forward in the direction of developing the next generation of seamless brain-machine interface to study and modulate the activities of specific sub-populations of neurons, and to develop therapies for a plethora of neurological diseases.
Graphlet Laplacians: graphlet-based neighbourhoods highlight topology-function and topology-disease relationships
Authors: Windels Sam F. L. , Malod-Dognin Noël , Pržulj Nataša 
Published: November 2018

AbstractMotivationLaplacian matrices capture the global structure of networks and are widely used to study biological networks. However, the local structure of the network around a node can also capture biological information. Local wiring patterns are typically quantified by counting how often a node touches different graphlets (small, connected, induced sub-graphs). Currently available graphlet-based methods do not consider whether nodes are in the same network neighbourhood.ContributionTo combine graphlet-based topological information and membership of nodes to the same network neighbourhood, we generalize the Laplacian to the Graphlet Laplacian, by considering a pair of nodes to be ‘adjacent’ if they simultaneously touch a given graphlet.ResultsWe utilize Graphlet Laplacians to generalize spectral embedding, spectral clustering and network diffusion. Applying our generalization of spectral clustering to model networks and biological networks shows that Graphlet Laplacians capture different local topology corresponding to the underlying graphlet. In biological networks, clusters obtained by using different Graphlet Laplacians capture complementary sets of biological functions. By diffusing pan-cancer gene mutation scores based on different Graphlet Laplacians, we find complementary sets of cancer driver genes. Hence, we demonstrate that Graphlet Laplacians capture topology-function and topology-disease relationships in biological networks
Family-based quantitative trait meta-analysis implicates rare noncoding variants inDENND1Ain pathogenesis of polycystic ovary syndrome
Authors: Dapas Matthew , Sisk Ryan , Legro Richard S. , Urbanek Margrit , Dunaif Andrea , Hayes M. Geoffrey 
Published: November 2018

ABSTRACTPolycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5-15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. PCOS is a leading risk factor for type 2 diabetes in young women. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date. To test the hypothesis that rare genetic variants contribute to PCOS pathogenesis, we performed whole-genome sequencing on DNA from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis. We found rare variants inDENND1A(P=5.31×10−5,Padj=0.019) that were significantly associated with reproductive and metabolic traits in PCOS families. Common variants inDENND1Ahave previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated thatDENND1Ais an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence thatDENND1Aplays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.
Cytokit: A single-cell analysis toolkit for high dimensional fluorescent microscopy imaging
Authors: Czech Eric , Aksoy Bulent Arman , Aksoy Pinar , Hammerbacher Jeff 
Published: November 2018

AbstractBackgroundMultiplexed in-situ fluorescent imaging offers several advantages over single-cell assays that do not preserve the spatial characteristics of biological samples. This spatial information, in addition to morphological properties and extensive intracellular or surface marker profiling, comprise promising avenues for rapid advancements in the understanding of disease progression and diagnosis. As protocols for conducting such imaging experiments continue to improve, it is the intent of this study to provide and validate software for processing the large quantity of associated data in kind.ResultsCytokit offers (i) an end-to-end, GPU-accelerated image processing pipeline; (ii) efficient input/output (I/O) strategies for operations specific to high dimensional microscopy; and (iii) an interactive user interface for cross filtering of spatial, graphical, expression, and morphological cell properties within the 100+ GB image datasets common to multiplexed immunofluorescence. Image processing operations supported in Cytokit are generally sourced from existing deep learning models or are at least in part adapted from open source packages to run in a single or multi-GPU environment. The efficacy of these operations is demonstrated through several imaging experiments that pair Cytokit results with those from an independent but comparable assay. A further validation also demonstrates that previously published results can be reproduced from a publicly available multiplexed image dataset.ConclusionCytokit is a collection of open source tools for quantifying and analyzing properties of individual cells in large fluorescent microscopy datasets that are often, but not necessarily, generated from multiplexed antibody labeling protocols over many fields of view or time periods. This project is best suited to bioinformaticians or other technical users that wish to analyze such data in a batch-oriented, high-throughput setting. All source code, documentation, and data generated for this article are available under the Apache License 2.0 at https://github.com/hammerlab/cytokit.
Coccinellid host morphology dictates morphological diversity of the parasitoid waspDinocampus coccinellae
Authors: Vansant Hannah , Vasquez Yumary M , Obrycki John J , Sethuraman Arun 
Published: November 2018

AbstractPararsitoid-host interactions involving host species that are newly introduced into the range of a generalist parasitoid provide systems that can be examined for phenotypic plasticity and evolutionary changes in parasitoid-host dynamics. The solitary Braconid parasitoid wasp,Dinocampus coccinellae, has a cosmopolitan distribution and parasitizes approximately 50 species of predatory lady beetles (ladybirds) in the family Coccinellidae. In this study we quantified the effect of six (4 native North American and 2 non-native North American) host species on the morphometrics ofD. coccinellae. Adult lady beetles were collected from 13 locations in the United States and reared in the laboratory untilD.coccinellaeexited from their adult beetle hosts. Eighty-nine individualD. coccinellaefemales and their associated host were weighed and morphometric measurements were taken. The smallest lady beetle hostHippodamia parenthesisproduced the smallest adult wasps; the largest host species,Coccinella septempunctata, produced the largest female wasps. A directional cline in morphology of wasps and their coccinellid hosts was also observed in a dry-weight regression (R2= 0.4066, p-value < 0.0001). Two underlying mechanisms may explain the results of our study: (1) morphometric variation inD. coccinellaeis governed by phenotypic plasticity with the size of the emerging offspring contingent on the size of the coccinellid host, and/or (2) that morphometric variation inD. coccinellaeis governed by genomic adaptation to coccinellid host populations.
Killer meiotic drive and dynamic evolution of thewtfgene family
Authors: Eickbush Michael T. , Young Janet M. , Zanders Sarah E. 
Published: November 2018

AbstractNatural selection works best when the two alleles in a diploid organism are transmitted to offspring at equal frequencies. Despite this, selfish loci known as meiotic drivers that bias their own transmission into gametes are found throughout eukaryotes. Drive is thought to be a powerful evolutionary force, but empirical evolutionary analyses of drive systems are limited by low numbers of identified meiotic drive genes. Here, we analyze the evolution of thewtfgene family ofSchizosaccharomyces pombethat contains both killer meiotic drive genes and suppressors of drive. We completed assemblies of allwtfgenes for two S.pombestrains, as well as a subset ofwtfgenes from over 50 strains. We find thatwtfcopy number can vary greatly between strains, and that amino acid substitutions, expansions and contractions of DNA sequence repeats, and nonallelic gene conversion between family members all contribute to dynamicwtfgene evolution. This work demonstrates the power of meiotic drive to foster rapid evolution and identifies a recombination mechanism through which transposons can indirectly mobilize meiotic drivers.
On-site integrated production of cellulases and β-glucosidases by Trichoderma reesei Rut C30 using steam-pretreated sugarcane bagasse
Authors: Fernandes de Souza Marcella , Pinto da Silva Bon Elba , Ana da Silvab Ayla Sant’ 
Published: November 2018

AbstractThe high cost of commercial cellulases still hampers the economic competitiveness of the production of fuels and chemicals from lignocellulosic biomasses. This cost may be decreased by the on-site production of cellulases with the integrated use of the lignocellulosic biomass as carbon source. This integrated approach was evaluated in the present study whereby steam-pretreated sugarcane bagasse (SPSB) was used as carbon source for the production of cellulases by Trichoderma reesei Rut C30 and the produced enzymes were subsequently used for SPSB hydrolysis. An enzyme preparation with a high cellulase activity, of 1.93 FPU/mL, was obtained, and a significant β-glucosidase activity was achieved in buffered media, indicating the importance of pH control during enzyme production. The hydrolysis of SPSB with the laboratory-made mixture resulted in a glucose yield of 80%, which was equivalent to those observed for control experiments using commercial enzymes. Even though the supplementation of this mixture with external β-glucosidase from Aspergillus awamori was found to increase the initial hydrolysis rates, it had no impact on the final hydrolysis yield. It was shown that SPSB is a promising carbon source for the production of cellulases and β-glucosidases by T. reesei Rut C30 and that the enzyme preparation obtained is effective for the hydrolysis of SPSB, supporting the on-site integrated approach to decrease the cost of the enzymatic hydrolysis of lignocellulosic biomass.
Basal stem cell fate specification is mediated by SMAD signaling in the developing human lung
Authors: Miller Alyssa J. , Yu Qianhui , Czerwinski Michael , Tsai Yu-Hwai , Conway Renee F. , Wu Angeline , Holloway Emily M. , Walker Taylor , Glass Ian A. , Treutlein Barbara , Camp J. Gray , Spence Jason R. 
Published: November 2018

AbstractBasal stem cells (basal cells), located in the bronchi and trachea of the human lung epithelium, play a critical role in normal airway homeostasis and repair, and have been implicated in the development of diseases such as cancer1-4. Additionally, basal-like cells contribute to alveolar regeneration and fibrosis following severe injury5-8. However, the developmental origin of basal cells in humans is unclear. Previous work has shown that specialized progenitor cells exist at the tips of epithelial tubes during lung branching morphogenesis, and in mice, give rise to all alveolar and airway lineages9,10. These ‘bud tip progenitor cells’ have also been described in the developing human lung11-13, but the mechanisms controlling bud tip differentiation into specific cell lineages, including basal cells, are unknown. Here, we interrogated the bud tip-to-basal cell transition using human tissue specimens, bud tip progenitor organoid cultures11, and single-cell transcriptomics. We used single-cell mRNA sequencing (scRNAseq) of developing human lung specimens from 15-21 weeks gestation to identify molecular signatures and cell states in the developing human airway epithelium. We then inferred differentiation trajectories during bud tip-to-airway differentiation, which revealed a previously undescribed transitional cell state (‘hub progenitors’) and implicated SMAD signaling as a regulator of the bud tip-to-basal cell transition. We used bud tip progenitor organoids to show that TGFT1 and BMP4 mediated SMAD signaling robustly induced the transition into functional basal-like cells, and thesein vitro-derived basal cells exhibited clonal expansion, self-renewal and multilineage differentiation. This work provides a framework for deducing and validating key regulators of cell fate decisions using single cell transcriptomics and human organoid models. Further, the identification of SMAD signaling as a critical regulator of newly born basal cells in the lung may have implications for regenerative medicine, basal cell development in other organs, and understanding basal cell misregulation in disease.
First Osteosarcoma Reported from a New World Elapid Snake and Review of Reptilian Bony Tumors
Authors: Hall Alexander S. , Jacobs Justin L. , Smith Eric N. 
Published: November 2018

AbstractCancer chiefly occurs in vertebrates. Rare in amphibians, and perhaps common in reptiles, various neoplasms and malignant cancers have been reported with erratic frequency by museums, paleontologists, veterinarians, and pet hobbyists. Unsurprisingly, most herpetofaunal diversity has never been systematically surveyed for the presence of neoplasms owing to the extreme rarity or obscurity of many species. Museum collections can fill these gaps in knowledge, especially when researchers use non-destructive techniques. In this study, we used X-ray computed tomography to discover and characterize an osteosarcoma of the spine in a rare South American coralsnake, Micrurus ancoralis. Two spinal vertebrae were completely fused and adjacent vertebrae showed evidence of corruption. The fused vertebrae contained a hollow inner network thought to be vascular tissue. We also review previous reports of tumors in the Elapidae and all bony tumors in non-avian reptiles. The rarely reported technique of X-ray CT for tumor discovery could greatly improve our understanding of the species diversity and perhaps underlying causes of neoplasia.
Perturbations of transcription and gene expression-associated processes alter distribution of cell size values inSaccharomyces cerevisiae
Authors: Maitra Nairita , Anandhakumar Jayamani , Blank Heidi M. , Kaplan Craig D. , Polymenis Michael 
Published: November 2018

ABSTRACTThe question of what determines whether cells are big or small has been the focus of many studies because it is thought that such determinants underpin the coupling of cell growth with cell division. In contrast, what determines the overall pattern of how cell size is distributed within a population of wild type or mutant cells has received little attention. Knowing how cell size varies around a characteristic pattern could shed light on the processes that generate such a pattern and provide a criterion to identify its genetic basis. Here, we show that cell size values of wild typeSaccharomyces cerevisiaecells fit a gamma distribution, in haploid and diploid cells, and under different growth conditions. To identify genes that influence this pattern, we analyzed the cell size distributions of all single-gene deletion strains inSaccharomyces cerevisiae.We found that yeast strains which deviate the most from the gamma distribution are enriched for those lacking gene products functioning in gene expression, especially those in transcription or transcription-linked processes. We also show that cell size is increased in mutants carrying altered activity substitutions in Rpo21p/Rpb1, the largest subunit of RNA polymerase II (Pol II). Lastly, the size distribution of cells carrying extreme altered activity Pol II substitutions deviated from the expected gamma distribution. Our results are consistent with the idea that genetic defects in widely acting transcription factors or Pol II itself compromise both cell size homeostasis and how the size of individual cells is distributed in a population.
ENvironmental Dynamics Underlying Responsive Extreme Survivors (ENDURES) of Glioblastoma: a Multi-disciplinary Team-based, Multifactorial Analytical Approach
Authors: Johnston Sandra K. , Whitmire Paula , Massey Susan Christine , Kumthekar Priya , Porter Alyx B. , Raghunand Natarajan , Gonzalez-Cuyar Luis F. , Mrugala Maciej M. , Hawkins-Daarud Andrea , Jackson Pamela R. , Hu Leland S. , Sarkaria Jann N. , Wang Lei , Gatenby Robert A. , Egan Kathleen M. , Canoll Peter , Swanson Kristin R. 
Published: November 2018

AbstractAlthough glioblastoma is a fatal primary brain cancer with a short median survival of 15 months, a small number of patients survive more than 5 years after diagnosis; they are known as extreme survivors (ES). Due to their rarity, very little is known about what differentiates these outliers from other glioblastoma patients. For the purpose of identifying unknown drivers of extreme survivorship in glioblastoma, we developed the ENDURES consortium (ENvironmental Dynamics Underlying Responsive Extreme Survivors of glioblastoma). This consortium is a multicenter collaborative network of investigators focused on the integration of multiple types of clinical data and the creation of patient-specific models of tumor growth informed by radiographic and histological parameters. Leveraging our combined resources, the goals of the ENDURES consortium are two-fold: (1) to build a curated, searchable, multilayered repository housing clinical and outcome data on a large cohort of ES patients with glioblastoma and (2) to leverage the ENDURES repository for new insights on tumor behavior and novel targets for prolonging survival for all glioblastoma patients. In this article, we review the available literature and discuss what is already known about ES. We then describe the creation of our consortium and some of our preliminary results.FundingThis review was financially supported by a grant from the James S. McDonnell FoundationConflicts of InterestThe authors have declared that no conflicts of interest exist.AuthorshipConceptualized consortium: LW, RG, KME, PC, and KRS. Built consortium: SKJ, PK, NR, JS, KME, PC, and KRS. Wrote the manuscript: SKJ, PW, SCM, PK, AP, and KME. Reviewed and edited the manuscript: LFGC, MMM, AHD, PRJ, and LSH. Contributed to writing, provided feedback, and approved of final manuscript: All authors.Link to website for ENDUREShttp://mathematicalneurooncology.org/?page_id=2125
Big DNA as a tool to dissect an age-related macular degeneration-associated haplotype
Authors: Laurent Jon M , Fu Xin , German Sergei , Maurano Matthew T , Zhang Kang , Boeke Jef D 
Published: November 2018

AbstractAge-related Macular Degeneration (AMD) is a leading cause of blindness in the developed world, especially in aging populations, and is therefore an important target for new therapeutic development. Recently, there have been several studies demonstrating strong associations between AMD and sites of heritable genetic variation at multiple loci, including a highly significant association at 10q26. The 10q26 risk region contains two genes, HTRA1 and ARMS2, both of which have been separately implicated as causative for the disease, as well as dozens of sites of non-coding variation. To date, no studies have successfully pinpointed which of these variant sites are functional in AMD, nor definitively identified which genes in the region are targets of such regulatory variation. In order to efficiently decipher which sites are functional in AMD phenotypes, we describe a general framework for combinatorial assembly of large ‘synthetic haplotypes’ along with delivery to relevant disease cell types for downstream functional analysis. We demonstrate the successful and highly efficient assembly of a first-draft 119kb wild-type ‘assemblon’ covering the HTRA1/ARMS2 risk region. We further propose the parallelized assembly of a library of combinatorial variant synthetic haplotypes covering the region, delivery and analysis of which will identify functional sites and their effects, leading to an improved understanding of AMD development. We anticipate that the methodology proposed here is highly generalizable towards the difficult problem of identifying truly functional variants from those discovered via GWAS or other genetic association studies.