Regulation of Meiotic Cohesion and Chromosome Core Morphogenesis during Pachytene in Drosophila Oocytes

During meiosis, cohesion between sister chromatids is required for normal levels of homologous recombination, maintenance of chiasmata and accurate chromosome segregation during both divisions. In Drosophila, null mutations in the ord gene abolish meiotic cohesion, although how ORD protein promotes cohesion has remained elusive. We show that SMC subunits of the cohesin complex colocalize with ORD at centromeres of ovarian germ-line cells. In addition, cohesin SMCs and ORD are visible along the length of meiotic chromosomes during pachytene and remain associated with chromosome cores following DNase I digestion. In flies lacking ORD activity, cohesin SMCs fail to accumulate at oocyte centromeres. Although SMC1 and SMC3 localization along chromosome cores appears normal during early pachytene in ord mutant oocytes, the cores disassemble as meiosis progresses. These data suggest that cohesin loading and/or accumulation at centromeres versus arms is under differential control during Drosophila meiosis. Our experiments also reveal that the alpha-kleisin C(2)M is required for the assembly of chromosome cores during pachytene but is not involved in recruitment of cohesin SMCs to the centromeres. We present a model for how chromosome cores are assembled during Drosophila meiosis and the role of ORD in meiotic cohesion, chromosome core maintenance and homologous recombination

Bounded Search for de Novo Identification of Degenerate Cis-Regulatory Elements

The identification of statistically overrepresented sequences in the upstream regions of coregulated genes should theoretically permit the identification of potential cis-regulatory elements. However, in practice many cis-regulatory elements are highly degenerate, precluding the use of an exhaustive word-counting strategy for their identification. While numerous methods exist for inferring base distributions using a position weight matrix, recent studies suggest that the independence assumptions inherent in the model, as well as the inability to reach a global optimum, limit this approach

A Novel Ensemble Learning Method for de Novo Computational Identification of DNA Binding Sites

Despite the diversity of motif representations and search algorithms, the de novo computational identification of transcription factor binding sites remains constrained by the limited accuracy of existing algorithms and the need for user-specified input parameters that describe the motif being sought.ResultsWe present a novel ensemble learning method, SCOPE, that is based on the assumption that transcription factor binding sites belong to one of three broad classes of motifs: non-degenerate, degenerate and gapped motifs. SCOPE employs a unified scoring metric to combine the results from three motif finding algorithms each aimed at the discovery of one of these classes of motifs. We found that SCOPE\u27s performance on 78 experimentally characterized regulons from four species was a substantial and statistically significant improvement over that of its component algorithms. SCOPE outperformed a broad range of existing motif discovery algorithms on the same dataset by a statistically significant margin

InVERT molding for scalable control of tissue microarchitecture

Complex tissues contain multiple cell types that are hierarchically organized within morphologically and functionally distinct compartments. Construction of engineered tissues with optimized tissue architecture has been limited by tissue fabrication techniques, which do not enable versatile microscale organization of multiple cell types in tissues of size adequate for physiological studies and tissue therapies. Here we present an ‘Intaglio-Void/Embed-Relief Topographic molding’ method for microscale organization of many cell types, including induced pluripotent stem cell-derived progeny, within a variety of synthetic and natural extracellular matrices and across tissues of sizes appropriate for in vitro, pre-clinical, and clinical studies. We demonstrate that compartmental placement of non-parenchymal cells relative to primary or induced pluripotent stem cell-derived hepatocytes, compartment microstructure, and cellular composition modulate hepatic functions. Configurations found to sustain physiological function in vitro also result in survival and function in mice for at least 4 weeks, demonstrating the importance of architectural optimization before implantation.National Institutes of Health (U.S.) (EB008396)National Institutes of Health (U.S.) (DK56966)National Cancer Institute (U.S.) (Cancer Center Support Core Grant P30-CA14051)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (1F32DK091007)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (1F32DK095529)National Science Foundation (U.S.). Graduate Research Fellowship Program (1122374

β[beta]-Catenin and FGFR2 regulate postnatal rosette-based adrenocortical morphogenesis

Rosettes are widely used in epithelial morphogenesis during embryonic development and organogenesis. However, their role in postnatal development and adult tissue maintenance remains largely unknown. Here, we show zona glomerulosa cells in the adult adrenal cortex organize into rosettes through adherens junction-mediated constriction, and that rosette formation underlies the maturation of adrenal glomerular structure postnatally. Using genetic mouse models, we show loss of beta-catenin results in disrupted adherens junctions, reduced rosette number, and dysmorphic glomeruli, whereas beta-catenin stabilization leads to increased adherens junction abundance, more rosettes, and glomerular expansion. Furthermore, we uncover numerous known regulators of epithelial morphogenesis enriched in beta-catenin-stabilized adrenals. Among these genes, we show Fgfr2 is required for adrenal rosette formation by regulating adherens junction abundance and aggregation. Together, our data provide an example of rosette-mediated postnatal tissue morphogenesis and a framework for studying the role of rosettes in adult zona glomerulosa tissue maintenance and function

TBI lesion segmentation in head CT: impact of preprocessing and data augmentation

Automatic segmentation of lesions in head CT provides keyinformation for patient management, prognosis and disease monitoring.Despite its clinical importance, method development has mostly focusedon multi-parametric MRI. Analysis of the brain in CT is challengingdue to limited soft tissue contrast and its mono-modal nature. We studythe under-explored problem of fine-grained CT segmentation of multiplelesion types (core, blood, oedema) in traumatic brain injury (TBI). Weobserve that preprocessing and data augmentation choices greatly impactthe segmentation accuracy of a neural network, yet these factors arerarely thoroughly assessed in prior work. We design an empirical studythat extensively evaluates the impact of different data preprocessing andaugmentation methods. We show that these choices can have an impactof up to 18% DSC. We conclude that resampling to isotropic resolutionyields improved performance, skull-stripping can be replaced by using theright intensity window, and affine-to-atlas registration is not necessaryif we use sufficient spatial augmentation. Since both skull-stripping andaffine-to-atlas registration are susceptible to failure, we recommend theiralternatives to be used in practice. We believe this is the first work toreport results for fine-grained multi-class segmentation of TBI in CT. Ourfindings may inform further research in this under-explored yet clinicallyimportant task of automatic head CT lesion segmentation

Label-free segmentation of co-cultured cells on a nanotopographical gradient

The function and fate of cells is influenced by many different factors, one of which is surface topography of the support culture substrate. Systematic studies of nanotopography and cell response have typically been limited to single cell types and a small set of topographical variations. Here, we show a radical expansion of experimental throughput using automated detection, measurement, and classification of co-cultured cells on a nanopillar array where feature height changes continuously from planar to 250 nm over 9 mm. Individual cells are identified and characterized by more than 200 descriptors, which are used to construct a set of rules for label-free segmentation into individual cell types. Using this approach we can achieve label-free segmentation with 84% confidence across large image data sets and suggest optimized surface parameters for nanostructuring of implant devices such as vascular stents

Intronic Non-CG DNA hydroxymethylation and alternative mRNA splicing in honey bees

Abstract Background Previous whole-genome shotgun bisulfite sequencing experiments showed that DNA cytosine methylation in the honey bee (Apis mellifera) is almost exclusively at CG dinucleotides in exons. However, the most commonly used method, bisulfite sequencing, cannot distinguish 5-methylcytosine from 5-hydroxymethylcytosine, an oxidized form of 5-methylcytosine that is catalyzed by the TET family of dioxygenases. Furthermore, some analysis software programs under-represent non-CG DNA methylation and hydryoxymethylation for a variety of reasons. Therefore, we used an unbiased analysis of bisulfite sequencing data combined with molecular and bioinformatics approaches to distinguish 5-methylcytosine from 5-hydroxymethylcytosine. By doing this, we have performed the first whole genome analyses of DNA modifications at non-CG sites in honey bees and correlated the effects of these DNA modifications on gene expression and alternative mRNA splicing. Results We confirmed, using unbiased analyses of whole-genome shotgun bisulfite sequencing (BS-seq) data, with both new data and published data, the previous finding that CG DNA methylation is enriched in exons in honey bees. However, we also found evidence that cytosine methylation and hydroxymethylation at non-CG sites is enriched in introns. Using antibodies against 5-hydroxmethylcytosine, we confirmed that DNA hydroxymethylation at non-CG sites is enriched in introns. Additionally, using a new technique, Pvu-seq (which employs the enzyme PvuRts1l to digest DNA at 5-hydroxymethylcytosine sites followed by next-generation DNA sequencing), we further confirmed that hydroxymethylation is enriched in introns at non-CG sites. Conclusions Cytosine hydroxymethylation at non-CG sites might have more functional significance than previously appreciated, and in honey bees these modifications might be related to the regulation of alternative mRNA splicing by defining the locations of the introns

BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature

With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php

Real-time imaging of hepatitis C virus infection using a fluorescent cell-based reporter system

Author Manuscript 2010 August 1Hepatitis C virus (HCV), which infects 2–3% of the world population, is a causative agent of chronic hepatitis and the leading indication for liver transplantation1. The ability to propagate HCV in cell culture (HCVcc) is a relatively recent breakthrough and a key tool in the quest for specific antiviral therapeutics. Monitoring HCV infection in culture generally involves bulk population assays, use of genetically modified viruses and/or terminal processing of potentially precious samples. Here we develop a cell-based fluorescent reporter system that allows sensitive distinction of individual HCV-infected cells in live or fixed samples. We demonstrate use of this technology for several previously intractable applications, including live-cell imaging of viral propagation and host response, as well as visualizing infection of primary hepatocyte cultures. Integration of this reporter with modern image-based analysis methods could open new doors for HCV research.New York (State). Dept. of Health (Empire State Stem Cell Fund Contract C023046)United States. Public Health Service (Grant R01 DK56966)National Institutes of Health (U.S.) (Roadmap for Medical Research Grant 1 R01 DK085713-01)Howard Hughes Medical Institute (Investigator