Regulation of Tissue-Specific Expression in the C. Elegans Embryo

Development proceeds through many stages, and requires genes to function at particular places and times. Knowing when and where a gene is expressed can predict its function. Furthermore, tissue-specific gene expression is regulated by many factors, whose expression patterns often overlap. Understanding this regulation would be helped by finding examples of regulatory targets of these factors, throughout the genome. The nematode C. elegans provides a model of how parts combine to form an organism. It develops into 558 cells during embryogenesis via an invariant lineage (pattern of divisions). Fluorescent markers are available for many well-defined groups of cells. Therefore, we asked how well we could “deconvolute” the expression genome-wide in each individual cell, based on expression measurements in overlapping sets of cells. Using simulated data, we compared the performance of several different methods for solving this problem. We found that we could estimate the possible range of expression throughout the embryo, using far fewer measurements than there are cells. Based on the performance simulations, we measured expression in eighteen populations of cells, flow-sorted by fluorescent markers expressed in the C. elegans embryo. Applying our deconvolution methods allowed us to estimate every gene’s expression in every cell, although the accuracy of these predictions with our current sample size are not yet high enough to make them broadly useful. We clustered this dataset, and found that many genes known to be expressed in particular tissues cluster together. Comparison with existing annotation suggests that over a hundred of these clusters of genes are expressed in a tissue-specific manner. RNA-FISH confirms some of these expression predictions. Motifs corresponding to known C. elegans transcription factors were enriched upstream of the genes in many of these clusters. By combining motif enrichment with coexpression, we obtain many novel predictions about gene regulation. We have validated several of these predictions using RT-PCR in a mutant background. Our data and analysis provides a resource for improving our knowledge of tissue-specific expression and its regulation throughout C. elegans development. Furthermore, our results suggest a framework for inferring changes in gene expression and cell type composition in complex tissues

A quantitative model of normal Caenorhabditis elegans embryogenesis and its disruption after stress

AbstractThe invariant lineage of Caenorhabditis elegans has powerful potential for quantifying developmental variability in normal and stressed embryos. Previous studies of division timing by automated lineage tracing suggested that variability in cell cycle timing is low in younger embryos, but manual lineage tracing of specific lineages suggested that variability may increase for later divisions. We developed improved automated lineage tracing methods that allowroutine lineage tracing through the last round of embryonic cell divisions and we applied these methods to trace the lineage of 18 wild-type embryos. Cell cycle lengths, division axes and cell positions are remarkably consistent among these embryos at all stages, with only slight increase in variability later in development. The resulting quantitative 4-dimensional model of embryogenesis provides a powerful reference dataset to identify defects in mutants or in embryos that have experienced environmental perturbations. We also traced the lineages of embryos imaged at higher temperatures to quantify the decay in developmental robustness under temperature stress. Developmental variability increases modestly at 25°C compared with 22°C and dramatically at 26°C, and we identify homeotic transformations in a subset of embryos grown at 26°C. The deep lineage tracing methods provide a powerful tool for analysis of normal development, gene expression and mutants and we provide a graphical user interface to allow other researchers to explore the average behavior of arbitrary cells in a reference embryo

Dual Learning in an Emergency Medicine Clerkship Improves Student Performance

BackgroundThe emergency department (ED) is an ideal environment to teach learners about the "undifferentiated patient." Student learning may be inconsistent because of inherent variability in the ED. Previous research has suggested that standardizing the emergency medicine (EM) clerkship by implementing didactics and requiring students to see patients with particular chief complaints improves educational outcomes.ObjectiveTo compare knowledge acquisition after a new curriculum to the traditional curriculum.MethodsThis was a prospective, quasiexperimental study of senior medical students in an EM clerkship. Students were assigned to the dual learning (DL) group or standard learning (SL) groups based on month of rotation. All were required to see patients with 10 specific chief complaints and were lent an EM textbook. The SL group was instructed to read about the required cases. The DL group attended a 2-hour didactic session covering 5 of the 10 required cases. All students completed an identical pre- and postclerkship multiple choice knowledge test.ResultsData from 51 medical students (DL = 27; SL = 24) were analyzed. Mean pretest scores were comparable between groups. A 2 (groups) by 2 (sessions) mixed-design analysis of variance yielded a significant group by session interaction effect (p < 0.001). The DL group significantly increased its mean score from 8.7 (standard deviation [SD] = 1.8) pretest to 11.6 (SD = 1.9) posttest; there was no improvement in the SL group (pretest: 9.3 [SD = 1.5], posttest: 10.0 [SD = 2.0]).ConclusionA DL model combining clinical and enhanced didactic requirements for an EM clerkship led to greater knowledge gain than the standard curriculum. This model may suggest ways to improve the educational experience in the EM clerkship

The Role of Fibrocytes in Sickle Cell Lung Disease

<div><h3>Background</h3><p>Interstitial lung disease is a frequent complication in sickle cell disease and is characterized by vascular remodeling and interstitial fibrosis. Bone marrow-derived fibrocytes have been shown to contribute to the pathogenesis of other interstitial lung diseases. The goal of this study was to define the contribution of fibrocytes to the pathogenesis of sickle cell lung disease.</p> <h3>Methodology/Principal Findings</h3><p>Fibrocytes were quantified and characterized in subjects with sickle cell disease or healthy controls, and in a model of sickle cell disease, the NY1DD mouse. The role of the chemokine ligand CXCL12 in trafficking of fibrocytes and phenotype of lung disease was examined in the animal model. We found elevated concentration of activated fibrocytes in the peripheral blood of subjects with sickle cell disease, which increased further during vaso-occlusive crises. There was a similar elevations in the numbers and activation phenotype of fibrocytes in the bone marrow, blood, and lungs of the NY1DD mouse, both at baseline and under conditions of hypoxia/re-oxygenation. In both subjects with sickle cell disease and the mouse model, fibrocytes expressed a hierarchy of chemokine receptors, with CXCR4 expressed on most fibrocytes, and CCR2 and CCR7 expressed on a smaller subset of cells. Depletion of the CXCR4 ligand, CXCL12, in the mouse model resulted in a marked reduction of fibrocyte trafficking into the lungs, reduced lung collagen content and improved lung compliance and histology.</p> <h3>Conclusions</h3><p>These data support the notion that activated fibrocytes play a significant role in the pathogenesis of sickle cell lung disease.</p> </div

Author Correction:Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article

Polymorphic Variation in Human Meiotic Recombination

In this study, our phenotype of interest is meiotic recombination. Using genotypes of ∼6,000 SNP markers in members of the Centre d'Étude du Polymorphisme Humain Utah pedigrees, we found extensive individual variation in the number of female and male recombination events. The locations and frequencies of these recombination events vary along the genome. In both female and male meiosis, the regions with the most recombination events are found at the ends of the chromosomes. Our analysis also shows that there are polymorphic differences among individuals in the activity of the recombination “jungles”; these preferred sites of meiotic recombination differ greatly among individuals. These findings have important implications for understanding genetic disorders that result from improper chromosome segregation

In silico method for inferring genotypes in pedigrees.

Our genotype inference method combines sparse marker data from a linkage scan and high-resolution SNP genotypes for several individuals to infer genotypes for related individuals. We illustrate the method&apos;s utility by inferring over 53 million SNP genotypes for 78 children in the Centre d&apos;Etude du Polymorphisme Humain families. The method can be used to obtain high-density genotypes in different family structures, including nuclear families commonly used in complex disease gene mapping studies. Even though groups such as The SNP Consortium 1 and the International HapMap Consortium 2,3 have identified millions of polymorphic markers and stimulated the development of high-throughput genotyping techniques 4-6 , genotyping of polymorphic markers remains a labor-intensive and costly step in genetic mapping studies. To decrease the cost of family-based genetic studies, we developed a computational approach that uses high-density genotype data for a subset of individuals in a pedigree to infer genotypes for the remaining relatives (se