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

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.

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

“…In addition to the dynamics of these lens-enriched genes, the present lens RNA-seq data also validates the “lens signature genes” previously identified by microarray analysis (Kakrana et al 2018). Indeed, the lens signature genes Aldoc , Dhx32 , Fabp5 , Gprc5b , Grifin , Gstm1 , Hmgn3 , Mboat1 , Mocs2 , Npl , Ogn , Pgam2 , Tmem40 and Zbtb8b are found to be highly expressed in the lens by the present analysis as well (Table S1).…”

“…Recently, we demonstrated that for tissue-specific microarray datasets, an approach termed “ in silico WB-subtraction”, involving comparative analysis of the tissue in question to a “reference” WB dataset, provides estimates of tissue-specific enrichment that can be applied for prioritization of candidate genes. For the lens, we showed that tissue-enrichment is an excellent predictor of significance to lens biology, which has led to the identification and/or characterization of several new cataract-associated genes (Lachke et al 2012b; Anand and Lachke 2017; Kakrana et al 2018). Here, we tested the hypothesis that in silico WB-subtraction can be extended to process lens RNA-seq data and prioritize candidates important to lens biology and cataract.…”

“…The in silico WB-subtraction approach, previously described for estimating lens-enrichment of genes from microarray datasets (Lachke et al 2012b; Kakrana et al 2018), was applied to the lens RNA-seq datasets. The newly generated RNA-seq WB data was used as reference and the preferential accumulation of transcripts was computed as log 2 F old- C hange (FC) using the “quasi-likelihood” (QF-) test included in edgeR package for WB vs. lens stages E10.5, E12.5, E14.5 and E16.5 contrasts.…”

“…lens stage vs. WB) identified from all four stages (E10.5, E12.5, E14.5, E16.5). These were used for enrichment level based clustering as previously described (Kakrana et al 2018); S elf- O rganizing T ree Algorithm (SOTA) method was used from the “clValid” package available in the Bioconductor (https://www.bioconductor.org). This analyses identified gene clusters exhibiting distinct lens enrichment patterns across E10.5 to E16.4 developmental window.…”

“…Further, the principle challenge in leveraging high-throughput expression profiles for disease-associated gene discovery lies in the application of effective downstream analysis for the identification of high-priority candidate genes that potentially function in the morphogenesis, homeostasis or pathology of the specific tissue of interest. Recently, we demonstrated that for mouse lens microarray datasets, an approach termed “ in silico WB-subtraction”, involving comparative analysis to a reference mouse whole-embryo body (WB) tissue dataset, allows the identification of genes with lens-enriched expression (Lachke et al 2012b; Kakrana et al 2018). Lens-enriched expression is an indicator of the significance of genes to lens biology and is the basis of the web-tool iSyTE ( i ntegrated Sy stems T ool for E ye gene discovery), which has led to the identification of several new genes as well as the characterization of multiple regulatory pathways associated with cataract and other eye-defects (Lachke et al 2011; Kasaikina et al 2011; Lachke et al 2012a, b; Aldahmesh et al 2012, 2013; Wolf et al 2013b; Manthey et al 2014a; Patel et al 2014; Agrawal et al 2015; Dash et al 2015; Chograni et al 2015; Greenlees et al 2015; Evers et al 2015; Audette et al 2016; Zhang et al 2016; Rothe et al 2017; Patel et al 2017; Cavalheiro et al 2017; Kakrana et al 2018; David et al 2018; Siddam et al 2018; Krall et al 2018).…”