Abstract
BackgroundIntegrated networks hold great promise in a variety of contexts. In a recent study, we have combined expression and interaction data to identify a putative network underlying early human organogenesis that contains two modules, the stemness-relevant module (hStemModule) and the differentiation-relevant module (hDiffModule). However, owing to its hypothetical nature, it remains unclear whether this network allows for comparative transcriptome analysis to advance our understanding of early human development, both in vivo and in vitro.ResultsBased on this integrated network, we here report comparisons with the context-dependent transcriptome data from a variety of sources. By viewing the network and its two modules as gene sets and conducting gene set enrichment analysis, we demonstrate the network's utility as a quantitative monitor of the stem potential versus the differentiation potential. During early human organogenesis, the hStemModule reflects the generality of a gradual loss of the stem potential. The hDiffModule indicates the stage-specific differentiation potential and is therefore not suitable for depicting an extended developmental window. Processing of cultured cells of different types further revealed that the hStemModule is a general indicator that distinguishes different cell types in terms of their stem potential. In contrast, the hDiffModule cannot distinguish between differentiated cells of different types but is able to predict differences in the differentiation potential of pluripotent cells of different origins. We also observed a significant positive correlation between each of these two modules and early embryoid bodies (EBs), which are used as in vitro differentiation models. Despite this, the network-oriented comparisons showed considerable differences between the developing embryos and the EBs that were cultured in vitro over time to try to mimic in vivo processes.ConclusionsWe strongly recommend the use of these two modules either when pluripotent cell types of different origins are involved or when the comparisons made are constrained to the in vivo embryos during early human organogenesis (and an equivalent in vitro differentiation models). Network-based comparative transcriptome analysis will contribute to an increase in knowledge about human embryogenesis, particularly when only transcriptome data are currently available. These advances will add an extra dimension to network applications.
Highlights
Integrated networks hold great promise in a variety of contexts
We focused on three representative developmental contexts, including human embryos [20,21], the stem cell matrix, and embryoid bodies (EBs) models [38,39]
By analyzing transcriptome data from the stem cell matrix, EB models and human embryos, we found that the human organogenesis network (hORGNet) and its two modules can advance our understanding of early human development, both in vivo and in vitro
Summary
Integrated networks hold great promise in a variety of contexts. In a recent study, we have combined expression and interaction data to identify a putative network underlying early human organogenesis that contains two modules, the stemness-relevant module (hStemModule) and the differentiation-relevant module (hDiffModule). Molecular and genetic interaction networks have proven to be useful in a variety of contexts They can potentially be used to predict gene functions [1], to predict perturbation phenotypes [2] and genetic modifier loci [3], to identify human disease genes and drug targets [4], to increase the statistical power in human genetics [5,6], and to study pathogen/virus-host crosstalk [7,8], to name just a few examples. The motivations for building such networks include the following: (i) from a biological perspective, genes are assumed to be interconnected into cohesive networks that control a certain biological process and (ii) from a methodological perspective, the integration of multiple layers of information is more likely to identify biologically relevant signals than analysis of either data source alone These integrated networks hold great promise for explaining the control mechanisms that underlie particular physiological and developmental processes. Because the network is inherently associated with two modules, there is a great need to clarify the circumstances in which it can be used as a reference for evaluating the stem potential versus the differentiation potential
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