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      iSyTE 2.0: a database for expression-based gene discovery in the eye

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          Abstract

          Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE ( integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches.

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          Most cited references42

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          Functional organization of the transcriptome in human brain.

          The enormous complexity of the human brain ultimately derives from a finite set of molecular instructions encoded in the human genome. These instructions can be directly studied by exploring the organization of the brain's transcriptome through systematic analysis of gene coexpression relationships. We analyzed gene coexpression relationships in microarray data generated from specific human brain regions and identified modules of coexpressed genes that correspond to neurons, oligodendrocytes, astrocytes and microglia. These modules provide an initial description of the transcriptional programs that distinguish the major cell classes of the human brain and indicate that cell type-specific information can be obtained from whole brain tissue without isolating homogeneous populations of cells. Other modules corresponded to additional cell types, organelles, synaptic function, gender differences and the subventricular neurogenic niche. We found that subventricular zone astrocytes, which are thought to function as neural stem cells in adults, have a distinct gene expression pattern relative to protoplasmic astrocytes. Our findings provide a new foundation for neurogenetic inquiries by revealing a robust and previously unrecognized organization to the human brain transcriptome.
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            Cat-Map: putting cataract on the map

            Lens opacities, or cataract(s), may be inherited as a classic Mendelian disorder usually with early-onset or, more commonly, acquired with age as a multi-factorial or complex trait. Many genetic forms of cataract have been described in mice and other animal models. Considerable progress has been made in mapping and identifying the genes and mutations responsible for inherited forms of cataract, and genetic determinants of age-related cataract are beginning to be discovered. To provide a convenient and accurate summary of current information focused on the increasing genetic complexity of Mendelian and age-related cataract we have created an online chromosome map and reference database for cataract in humans and mice (Cat-Map).
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              Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms

              The growth in popularity of RNA expression microarrays has been accompanied by concerns about the reliability of the data especially when comparing between different platforms. Here, we present an evaluation of the reproducibility of microarray results using two platforms, Affymetrix GeneChips and Illumina BeadArrays. The study design is based on a dilution series of two human tissues (blood and placenta), tested in duplicate on each platform. The results of a comparison between the platforms indicate very high agreement, particularly for genes which are predicted to be differentially expressed between the two tissues. Agreement was strongly correlated with the level of expression of a gene. Concordance was also improved when probes on the two platforms could be identified as being likely to target the same set of transcripts of a given gene. These results shed light on the causes or failures of agreement across microarray platforms. The set of probes we found to be most highly reproducible can be used by others to help increase confidence in analyses of other data sets using these platforms.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2018
                19 September 2017
                19 September 2017
                : 46
                : Database issue , Database issue
                : D875-D885
                Affiliations
                Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19711, USA
                Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia
                St. Vincent's Clinical School, The University of New South Wales, Sydney, NSW 2052, Australia
                Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
                Department of Electrical Engineering, University of Delaware, Newark, DE 19716, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 617 9599193; Fax: +1 302 8312281; Email: salil@ 123456udel.edu . Correspondence may also be addressed to Joshua W. K. Ho. Tel: +61 2 9295 8645; Fax: +61 2 9295 8601; Email: j.ho@ 123456victorchang.edu.au

                These authors contributed equally to the paper as first authors.

                Article
                gkx837
                10.1093/nar/gkx837
                5753381
                29036527
                d0780b87-b41f-4493-a0fe-56b7665ac1a3
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 11 September 2017
                : 01 September 2017
                : 10 August 2017
                Page count
                Pages: 11
                Categories
                Database Issue

                Genetics
                Genetics

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