Integrative analysis of the mouse embryonic transcriptome

Abstract

Monitoring global gene expression provides insight into how genes and regulatory signals work together to guide embryo development. The fields of developmental biology and teratology are now confronted with the need for automated access to a reference library of gene-expression signatures that benchmark programmed (genetic) and adaptive (environmental) regulation of the embryonic transcriptome. Such a library must be constructed from highly-distributed microarray data. Birth Defects Systems Manager (BDSM), an open access knowledge management system, provides custom software to mine public microarray data focused on developmental health and disease. The present study describes tools for seamless data integration in the BDSM library (MetaSample, MetaChip, CIAeasy) using the QueryBDSM module. A field test of the prototype was run using published microarray data series derived from a variety of laboratories, experiments, microarray platforms, organ systems, and developmental stages. The datasets focused on several developing systems in the mouse embryo, including preimplantation stages, heart and nerve development, testis and ovary development, and craniofacial development. Using BDSM data integration tools, a gene-expression signature for 346 genes was resolved that accurately classified samples by organ system and developmental sequence. The module builds a potential for the BDSM approach to decipher a large number developmental processes through comparative bioinformatics analysis of embryological systems at-risk for specific defects, using multiple scenarios to define the range of probabilities leading from molecular phenotype to clinical phenotype. We conclude that an integrative analysis of global gene-expression of the developing embryo can form the foundation for constructing a reference library of signaling pathways and networks for normal and abnormal regulation of the embryonic transcriptome. These tools are available free of charge from the web-site http://systemsanalysis.louisville.edu requiring only a short registration process.

Figure 1

Workflow schema for the QueryBDSM module of BDSM. Individual files of normalized microarray data are selected from the BDSM library. QueryBDSM determines the number of distinct microarray platforms in the sample queue and merges the data as follows: if all samples come from the same platform, then MetaSample is used; if multiple platforms are represented, then MetaChip is used. CIAeasy compares joint trends in expression data for the same samples run on different platform

Figure 2

Cross-platform comparison of expression profiles using CIAeasy. Class comparison of secondary analysis of GSE321 data from [10], using CIAeasy. Expression values were from statistical (ANOVA) analysis returning 4417 (MOE430Av2, alpha = 0.0001), 1614 (MOE430Bv2, alpha = 0.0001), and 2400 (MG-U74Av2, alpha = 0.001) probes. UPPER PANEL: Clustering of samples: Oocyte (Oo), 1-cell embryo (1C), 2-cell embryo (2C), 8-cell embryo (8C), and blastocyst (BL). For each platform a boxplot shows the log2 distribution of expression values for the probes at each stage (line = median, box = 75%, whiskers = 95%, and dots = outliers) and a histogram plots the cumulative distribution of probes in each expression bin. LOWER PANEL: The first two axes of ordination were projected by CIA. The horizontal axis reflects the first axis of the inertia and the vertical axis is the second axis of inertia. Circles (dots) and arrowheads (arrows) represent the projected coordinates of each platform being compared, with length of the line joining them being proportional to their divergence, e.g., shorter arrows indicate stronger joint trends between the platforms. The left compares joint trends in MOE430Av2 (dot) versus MOE430Bv2 (arrow), measure of global similarity, RV = 0.976; middle compares MOE430Av2 (dot) versus MG-U74Av2 (arrow), RV = 0.999; right compares MOE430Bv2 (dot) versus MG-U74Av2 (arrow), RV = 0.970

Figure 3

Hierarchy of molecular phenotypes in developing mouse embryos. In five GEO platforms (160 samples), 346 genes were found differentially expressed in BDSM profiles: preimplantation mouse embryo (GSE1749) [10], heart (GSE1479) GD10 - GD18 [11] nerve (GSE972) GD9.5 – birth [12]; ovary (GSE1359) and testis (GSE1358) GD11.5 – birth [13]; orofacial (GSE1624) [14] and palate [15] between GD13-15. Each developing organ system was properly ordered by its natural chronology, based on the 346 gene-expression signature and an unsupervised clustering algorithm with Pearson correlation. Gene colors are mapped by K-means clustering (6 sets).