Global Prediction of Tissue-Specific Gene Expression and Context-Dependent Gene Networks in Caenorhabditis elegans

Abstract

Tissue-specific gene expression plays a fundamental role in metazoan biology and is an important aspect of many complex diseases. Nevertheless, an organism-wide map of tissue-specific expression remains elusive due to difficulty in obtaining these data experimentally. Here, we leveraged existing whole-animal Caenorhabditis elegans microarray data representing diverse conditions and developmental stages to generate accurate predictions of tissue-specific gene expression and experimentally validated these predictions. These patterns of tissue-specific expression are more accurate than existing high-throughput experimental studies for nearly all tissues; they also complement existing experiments by addressing tissue-specific expression present at particular developmental stages and in small tissues. We used these predictions to address several experimentally challenging questions, including the identification of tissue-specific transcriptional motifs and the discovery of potential miRNA regulation specific to particular tissues. We also investigate the role of tissue context in gene function through tissue-specific functional interaction networks. To our knowledge, this is the first study producing high-accuracy predictions of tissue-specific expression and interactions for a metazoan organism based on whole-animal data.

Author Summary

In animals, a crucial facet of any gene's function is the tissue or cell type in which that gene is expressed and the proteins that it interacts with in that cell. However, genome-wide identification of expression across the multitude of tissues of varying size and complexity is difficult to achieve experimentally. In this paper, we show that microararray data collected from whole animals can be analyzed to yield high-quality predictions of tissue-specific expression. These predictions are of better or comparable accuracy to tissue-specific expression determined from high-throughput experiments. Our results provide a global view of tissue-specific expression in Caenorhabditis elegans, allowing us to address the question of how expression patterns are regulated and to analyze how the functions of genes that are expressed in several tissues are influenced by the cellular context.