Advancing the understanding of the embryo transcriptome co-regulation using meta-, functional, and gene network analysis tools

Abstract

Embryo development is a complex process orchestrated by hundreds of genes and influenced by multiple environmental factors. We demonstrate the application of simple and effective meta-study and gene network analyses strategies to characterize the co-regulation of the embryo transcriptome in a systems biology framework. A meta-analysis of nine microarray experiments aimed at characterizing the effect of agents potentially harmful to mouse embryos improved the ability to accurately characterize gene co-expression patterns compared with traditional within-study approaches. Simple overlap of significant gene lists may result in under-identification of genes differentially expressed. Sample-level meta-analysis techniques are recommended when common treatment levels or samples are present in more than one study. Otherwise, study-level meta-analysis of standardized estimates provided information on the significance and direction of the differential expression. Cell communication pathways were highly represented among the genes differentially expressed across studies. Mixture and dependence Bayesian network approaches were able to reconstruct embryo-specific interactions among genes in the adherens junction, axon guidance, and actin cytoskeleton pathways. Gene networks inferred by both approaches were mostly consistent with minor differences due to the complementary nature of the methodologies. The top-down approach used to characterize gene networks can offer insights into the mechanisms by which the conditions studied influence gene expression. Our work illustrates that further examination of gene expression information from microarray studies including meta-and gene network analyses can help characterize transcript co-regulation and identify biomarkers for the reproductive and embryonic processes under a wide range of conditions. Reproduction (2008) 135 213-224

The pathway not taken: understanding ‘omics data in the perinatal context

“…There is a small body of literature on bioinformatics approaches to embryo and single-blastomere transcriptomics, but these studies focus largely on non-human embryos rather than human fetuses, and did not utilize functional analysis tools such as GSEA or IPA. 36,37 …”

Transferase activity function and system development process are critical in cattle embryo development

“…A detailed description of the complementary properties of these approaches is provided in Rodriguez-Zas et al (2008) and Adams et al (2008). In the first approach, the data from each experiment was analyzed separately (individual-experiment analyses).…”

“…The goal of this study was to obtain a more comprehensive understanding of genes, molecular functions and biological processes associated with cattle embryo development and viability. To accomplish this, the information from four cattle microarray experiments was integrated using two sets of meta-analyses that provided complementary understanding (Adams et al 2008; Rodriguez-Zas et al 2008). The first set of meta-analyses offered broad insights into the differential gene expression between AI and NT technologies regardless of developmental stage or tissue source.…”

Phenotyping structural abnormalities in mouse embryos using high-resolution episcopic microscopy

“…When combined with existing and well-documented gene expression data (e.g. Horsch et al, 2008; Rodriguez-Zas et al, 2008; Seltmann et al, 2005; Zhu et al, 2007), such malformations provide a clue to the developmental function of genes and an entry point for further research. In addition, about half of all affected embryos reach a stage of development (after 14 days of gestation) when normal organogenesis is largely complete and much of the adult-like body plan is established.…”