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Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans.

Chikina MD, Huttenhower C, Murphy CT, Troyanskaya OG - PLoS Comput. Biol. (2009)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.

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.

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Motifs over-represented in the promoters of top predictions.(*) indicates motifs that have not been previously reported to be enriched in promoters of tissue-specific genes in C. elegans.
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pcbi-1000417-g004: Motifs over-represented in the promoters of top predictions.(*) indicates motifs that have not been previously reported to be enriched in promoters of tissue-specific genes in C. elegans.

Mentions: Our ability to make high-quality predictions also provided potential insights regarding the transcriptional regulation associated with the tissue-specific expression signal in whole animal data. We used a motif-finding program, FIRE [37], to identify motifs that are overrepresented in the upstream regions of our top-scoring predictions for each of the major tissues (Figure 4). While no genome-wide study of hypodermal expression has been published thus far, we were able to use our predictions to uncover motifs that are promising candidates for regulators of hypodermal transcription. A GATA-like motif was enriched among our top hypodermal predictions. This is consistent with previous studies showing that GATA transcription factors are essential for hypodermal cell specification, and that a GATA consensus sequence is required for hypodermal expression [38],[39]. In addition, we have identified a motif that is similar to the binding site for the CF1/USP-like nuclear hormone receptor that affects molting and developmental transitions in insects [40]. An intriguing possibility is that this motif and a functional USP homolog are involved in the nematode molting process as well, despite the fact that no direct USP homologs have been detected in the genome [41].


Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans.

Chikina MD, Huttenhower C, Murphy CT, Troyanskaya OG - PLoS Comput. Biol. (2009)

Motifs over-represented in the promoters of top predictions.(*) indicates motifs that have not been previously reported to be enriched in promoters of tissue-specific genes in C. elegans.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2692103&req=5

pcbi-1000417-g004: Motifs over-represented in the promoters of top predictions.(*) indicates motifs that have not been previously reported to be enriched in promoters of tissue-specific genes in C. elegans.
Mentions: Our ability to make high-quality predictions also provided potential insights regarding the transcriptional regulation associated with the tissue-specific expression signal in whole animal data. We used a motif-finding program, FIRE [37], to identify motifs that are overrepresented in the upstream regions of our top-scoring predictions for each of the major tissues (Figure 4). While no genome-wide study of hypodermal expression has been published thus far, we were able to use our predictions to uncover motifs that are promising candidates for regulators of hypodermal transcription. A GATA-like motif was enriched among our top hypodermal predictions. This is consistent with previous studies showing that GATA transcription factors are essential for hypodermal cell specification, and that a GATA consensus sequence is required for hypodermal expression [38],[39]. In addition, we have identified a motif that is similar to the binding site for the CF1/USP-like nuclear hormone receptor that affects molting and developmental transitions in insects [40]. An intriguing possibility is that this motif and a functional USP homolog are involved in the nematode molting process as well, despite the fact that no direct USP homologs have been detected in the genome [41].

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.

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.

Show MeSH