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Κυριακή 11 Νοεμβρίου 2018

RNA sequencing-based transcriptomic profiles of embryonic lens development for cataract gene discovery

Abstract

Isolated or syndromic congenital cataracts are heterogeneous developmental defects, making the identification of the associated genes challenging. In the past, mouse lens expression microarrays have been successfully applied in bioinformatics tools (e.g., iSyTE) to facilitate human cataract-associated gene discovery. To develop a new resource for geneticists, we report high-throughput RNA sequencing (RNA-seq) profiles of mouse lens at key embryonic stages (E)10.5 (lens pit), E12.5 (primary fiber cell differentiation), E14.5 and E16.5 (secondary fiber cell differentiation). These stages capture important events as the lens develops from an invaginating placode into a transparent tissue. Previously, in silico whole-embryo body (WB)-subtraction-based "lens-enriched" expression has been effective in prioritizing cataract-linked genes. To apply an analogous approach, we generated new mouse WB RNA-seq datasets and show that in silico WB subtraction of lens RNA-seq datasets successfully identifies key genes based on lens-enriched expression. At ≥2 counts-per-million expression, ≥1.5 log2 fold-enrichment (p < 0.05) cutoff, E10.5 lens exhibits 1401 enriched genes (17% lens-expressed genes), E12.5 lens exhibits 1937 enriched genes (22% lens-expressed genes), E14.5 lens exhibits 2514 enriched genes (31% lens-expressed genes), and E16.5 lens exhibits 2745 enriched genes (34% lens-expressed genes). Biological pathway analysis identified genes associated with lens development, transcription regulation and signaling pathways, among other functional groups. Furthermore, these new RNA-seq data confirmed high expression of established cataract-linked genes and identified new potential regulators in the lens. Finally, we developed new lens stage-specific UCSC Genome Brower annotation tracks and made these publicly accessible through iSyTE (https://research.bioinformatics.udel.edu/iSyTE/) for user-friendly visualization of lens gene expression/enrichment to prioritize genes from high-throughput data from cataract cases.



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