The vertebrate retina is comprised of seven major cell types that are generated in overlapping but well-defined intervals. To identify genes that might regulate retinal development, gene expression in the developing retina was profiled at multiple time points using serial analysis of gene expression (SAGE). The expression patterns of 1,051 genes that showed developmentally dynamic expression by SAGE were investigated using in situ hybridization. A molecular atlas of gene expression in the developing and mature retina was thereby constructed, along with a taxonomic classification of developmental gene expression patterns. Genes were identified that label both temporal and spatial subsets of mitotic progenitor cells. For each developing and mature major retinal cell type, genes selectively expressed in that cell type were identified. The gene expression profiles of retinal Müller glia and mitotic progenitor cells were found to be highly similar, suggesting that Müller glia might serve to produce multiple retinal cell types under the right conditions. In addition, multiple transcripts that were evolutionarily conserved that did not appear to encode open reading frames of more than 100 amino acids in length (“noncoding RNAs”) were found to be dynamically and specifically expressed in developing and mature retinal cell types. Finally, many photoreceptor-enriched genes that mapped to chromosomal intervals containing retinal disease genes were identified. These data serve as a starting point for functional investigations of the roles of these genes in retinal development and physiology.

We report testing of the specificity and utility of over 200 antibodies raised against 57 different histone modifications, in Drosophila melanogaster, Caenorhabditis elegans and human cells. While most antibodies performed well, over 25% failed specificity tests by dot blot or western blot. Among specific antibodies, over 20% failed in chromatin immunoprecipitation experiments. We advise rigorous testing of histone-modification antibodies before use and provide a website for posting new test results.

The increase in the number of ME publications and in the number of journals publishing ME articles suggests a supportive environment for a growing field; but variation in journals' foci has implications for readers, editors and authors.

BackgroundIt has been shown that large interdisciplinary teams working across geography are more likely to be impactful. We asked whether the physical proximity of collaborators remained a strong predictor of the scientific impact of their research as measured by citations of the resulting publications.Methodology/Principal FindingsArticles published by Harvard investigators from 1993 to 2003 with at least two authors were identified in the domain of biomedical science. Each collaboration was geocoded to the precise three-dimensional location of its authors. Physical distances between any two coauthors were calculated and associated with corresponding citations. Relationship between distance of coauthors and citations for four author relationships (first-last, first-middle, last-middle, and middle-middle) were investigated at different spatial scales. At all sizes of collaborations (from two authors to dozens of authors), geographical proximity between first and last author is highly informative of impact at the microscale (i.e. within building) and beyond. The mean citation for first-last author relationship decreased as the distance between them increased in less than one km range as well as in the three categorized ranges (in the same building, same city, or different city). Such a trend was not seen in other three author relationships.Conclusions/SignificanceDespite the positive impact of emerging communication technologies on scientific research, our results provide striking evidence for the role of physical proximity as a predictor of the impact of collaborations.

http://cmotifs.tchlab.org.

Whole genome sequencing (WGS) studies are uncovering disease-associated variants in both rare and non-rare diseases. Utilizing the next-generation sequencing for WGS requires a series of computational methods for alignment, variant detection, and annotation, and the accuracy and reproducibility of annotation results are essential for clinical implementation. However, annotating WGS with up to date genomic information is still challenging for biomedical researchers. Here we present one of the fastest and highly scalable annotation, filtering, and analysis pipeline –gNOME – to prioritize phenotype-associated variants while minimizing false positive findings. Intuitive graphical user interface of gNOME facilitates the selection of phenotype associated variants, and the result summaries are provided at variant-, gene-, and genome-levels. Moreover, the enrichment results of specific variants, genes, and gene sets between two groups or compared to population scale WGS datasets that is already integrated in the pipeline can help the interpretation. We found a small number of discordant results between annotation software tools in part due to different reporting strategies for the variants with complex impacts. Using two published whole exome datasets of uveal melanoma and bladder cancer, we demonstrated gNOME's accuracy of variant annotation and the enrichment of loss of function variants in known cancer pathways. gNOME web-server and source codes are freely available to the academic community.

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BackgroundResearch on carcinogens causing occupational cancer has been updated. Further, social interest in occupational cancer has increased. In addition, the standard for recognizing cancer as a work-related disease has also been revised. The present study aims to describe the distribution of occupational cancer claims or its approval rate and their association with work-related variables.MethodsWe analyzed 1299 claim cases for occupational cancer from 2010 to 2016 provided by the Korea Workers’ Compensation and Welfare Service (KCOMWEL). The status of approval rate was shown by year, sex, industry, occupation, age of diagnosis, duration from employment to diagnosis, and cancer site.ResultsThe approval rate was 39.0% from 2010 to 2016 and tended to increase annually since 2011. Both the number of claims and the approval rate were higher in men. Mining and quarrying showed the highest approval rate (78.4%). The approval rates by age of diagnosis and duration from employment to diagnosis increased as the time periods increased. Respiratory organ had the highest number of claims and the highest approval rate by cancer site.ConclusionsThe approval rate of occupational cancer has shown an increasing trend since 2011. The increase of occupational carcinogens and cancer sites and the improvement of social awareness about occupational cancer could have resulted in this trend. The present study provides unique, and the latest and most accurate findings on occupational cancer data of recent 7 years that could be helpful to researchers or policy makers on occupational cancer.