Dataset Information

EdgeScaping: Mapping the spatial distribution of pairwise gene expression intensities.

ABSTRACT: Gene co-expression networks (GCNs) are constructed from Gene Expression Matrices (GEMs) in a bottom up approach where all gene pairs are tested for correlation within the context of the input sample set. This approach is computationally intensive for many current GEMs and may not be scalable to millions of samples. Further, traditional GCNs do not detect non-linear relationships missed by correlation tests and do not place genetic relationships in a gene expression intensity context. In this report, we propose EdgeScaping, which constructs and analyzes the pairwise gene intensity network in a holistic, top down approach where no edges are filtered. EdgeScaping uses a novel technique to convert traditional pairwise gene expression data to an image based format. This conversion not only performs feature compression, making our algorithm highly scalable, but it also allows for exploring non-linear relationships between genes by leveraging deep learning image analysis algorithms. Using the learned embedded feature space we implement a fast, efficient algorithm to cluster the entire space of gene expression relationships while retaining gene expression intensity. Since EdgeScaping does not eliminate conventionally noisy edges, it extends the identification of co-expression relationships beyond classically correlated edges to facilitate the discovery of novel or unusual expression patterns within the network. We applied EdgeScaping to a human tumor GEM to identify sets of genes that exhibit conventional and non-conventional interdependent non-linear behavior associated with brain specific tumor sub-types that would be eliminated in conventional bottom-up construction of GCNs. Edgescaping source code is available at https://github.com/bhusain/EdgeScaping under the MIT license.

SUBMITTER: Husain B

PROVIDER: S-EPMC6684082 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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EdgeScaping: Mapping the spatial distribution of pairwise gene expression intensities.

Husain Benafsh B Feltus F Alex FA

PloS one 20190806 8

Gene co-expression networks (GCNs) are constructed from Gene Expression Matrices (GEMs) in a bottom up approach where all gene pairs are tested for correlation within the context of the input sample set. This approach is computationally intensive for many current GEMs and may not be scalable to millions of samples. Further, traditional GCNs do not detect non-linear relationships missed by correlation tests and do not place genetic relationships in a gene expression intensity context. In this rep ...[more]

PMID: 31386677

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Project description:Alzheimer's disease (AD) is a neurodegenerative disorder defined by the progressive formation and spread of fibrillar aggregates of Aβ peptide and tau protein. Polymorphic forms of these aggregates may contribute to disease in varying ways since different neuropathologies appear to be associated with different sets of fibrillar structures and follow distinct pathological trajectories that elicit characteristic clinical phenotypes. The molecular mechanisms underlying the spread of these aggregates in disease may include nucleation, replication, and migration all of which could vary with polymorphic form, stage of disease, and region of brain. Given the linkage between mechanisms of progression and distribution of polymorphs, mapping the distribution of fibrillar structures in situ has the potential to discriminate between mechanisms of progression. However, the means of carrying out this mapping are limited. Optical microscopy lacks the resolution to discriminate between polymorphs in situ, and higher resolution tools such as ssNMR and cryoEM require the isolation of fibrils from tissue, destroying relevant spatial information. Here, we demonstrate the use of scanning x-ray microdiffraction (XMD) to map the locations of fibrillar polymorphs of Aβ peptides and tau protein in histological thin sections of human brain tissue. Coordinated examination of serial sections by immunohistochemistry was used to aid in the interpretation of scattering patterns and to put the observations in a broader anatomical context. Scattering from lesions in tissue shown to be rich in Aβ fibrils by immunohistochemistry exhibited scattering patterns with a prototypical 4.7 Å cross-β peak, and overall intensity distribution that compared well with that predicted from high resolution structures. Scattering from lesions in tissue with extensive tau pathology also exhibited a 4.7 Å cross-β peak but with intensity distributions that were distinct from those seen in Aβ-rich regions. In summary, these observations demonstrate that XMD is a rich source of information on the distribution of fibrillar polymorphs in diseased human brain tissue. When used in coordination with neuropathological examination it has the potential to provide novel insights into the molecular mechanisms underlying disease.

Project description:BackgroundAedes aegypti mosquitoes are the main vectors of dengue viruses to humans. Understanding their biology and interactions with the pathogen are prerequisites for development of dengue transmission control strategies. Mosquito salivary glands are organs involved directly in pathogen transmission to vertebrate hosts. Information on the spatial distribution of gene expression in these organs is expected to assist in the development of novel disease control strategies, including those that entail the release of transgenic mosquitoes with impaired vector competence.ResultsWe report here the hybridization in situ patterns of 30 transcripts expressed in the salivary glands of adult Ae. aegypti females. Distinct spatial accumulation patterns were identified. The products of twelve genes are localized exclusively in the proximal-lateral lobes. Among these, three accumulate preferentially in the most anterior portion of the proximal-lateral lobe. This pattern revealed a salivary gland cell type previously undescribed in Ae. aegypti, which was validated by transmission electron microscopy. Five distinct gene products accumulate in the distal-lateral lobes and another five localize in the medial lobe. Seven transcripts are found in the distal-lateral and medial lobes. The transcriptional product of one gene accumulates in proximal- and distal-lateral lobes. Seven genes analyzed by quantitative PCR are expressed constitutively. The most abundant salivary gland transcripts are those localized within the proximal-lateral lobes, while previous work has shown that the distal-lateral lobes are the most active in protein synthesis. This incongruity suggests a role for translational regulation in mosquito saliva production.ConclusionsTransgenic mosquitoes with reduced vector competence have been proposed as tools for the control of dengue virus transmission. Expression of anti-dengue effector molecules in the distal-lateral lobes of Ae. aegypti salivary glands has been shown to reduce prevalence and mean intensities of viral infection. We anticipate greater efficiency of viral suppression if effector genes are expressed in all lobes of the salivary glands. Based on our data, a minimum of two promoters is necessary to drive the expression of one or more anti-dengue genes in all cells of the female salivary glands.

Dataset Information

EdgeScaping: Mapping the spatial distribution of pairwise gene expression intensities.

Publications

EdgeScaping: Mapping the spatial distribution of pairwise gene expression intensities.

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