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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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Tissue-specific weighted correlation networks allow elucidation of tissue-specific gene function.Top 20 predicted interactions partners and strongest inter-partner interactions are shown. Genes are colored according to known tissue-specific function: yellow indicates neuronal function, and red indicates involvement in a germ-line/oocyte process. (A) Neuron-specific network around exc-7. An extended SVM algorithm was used to predict tissue-specific functional interactions. Although exc-7 is best characterized as playing a role in the formation of the excretory cell, it has also been shown to regulate cholinergic synaptic transmission. Many of its functional interaction partners are consistent with this neuron-specific function. (B)Tissue-specific networks for let-60. let-60 is the homolog of mammalian Ras protein that is involved, among other processes, in chemosensation and progression through meiosis during oogenesis. The functional interaction partners identified for let-60 are completely different in the neuron and germ line networks, reflecting that this gene plays a different functional role in the context of different tissues.
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pcbi-1000417-g006: Tissue-specific weighted correlation networks allow elucidation of tissue-specific gene function.Top 20 predicted interactions partners and strongest inter-partner interactions are shown. Genes are colored according to known tissue-specific function: yellow indicates neuronal function, and red indicates involvement in a germ-line/oocyte process. (A) Neuron-specific network around exc-7. An extended SVM algorithm was used to predict tissue-specific functional interactions. Although exc-7 is best characterized as playing a role in the formation of the excretory cell, it has also been shown to regulate cholinergic synaptic transmission. Many of its functional interaction partners are consistent with this neuron-specific function. (B)Tissue-specific networks for let-60. let-60 is the homolog of mammalian Ras protein that is involved, among other processes, in chemosensation and progression through meiosis during oogenesis. The functional interaction partners identified for let-60 are completely different in the neuron and germ line networks, reflecting that this gene plays a different functional role in the context of different tissues.

Mentions: Using an SVM-based approach, we are able to integrate microarray data into different tissue-specific functional interaction networks. Such networks link genes that are likely to participate in the same process within a specific tissue context and contain information that may otherwise be overwhelmed in a global view of co-expression. As an example, we considered exc-7, an RNA-binding protein that is involved in the formation of the excretory canal, but that also plays a role in neuronal development, affecting cholinergic synaptic transmission [59]. Several of the interaction partners present in its neuron-specific interaction network support our understanding of exc-7 neuronal function (Figure 6A): hmr-1 is required for the outgrowth of some motor neurons [60]; unc-38 is an acetylcholine receptor [12]; and the mammalian homolog of abl-1 is involved in post-synaptic acetylcholine receptor clustering [61]. Another partner, rhgf-1, a RhoGEF, is known to regulate neurotransmitter release at the neuromuscular junction [62]. Our network results also suggest an interaction between exc-7 and smg-1, a key component of the nonsense-mediated mRNA decay pathway, and spk-1, which is involved in mRNA splicing [12]. The presence of RNA processing genes among the interaction partners is potentially related to exc-7's RNA-binding function. A standard correlation computation produces an entirely different, non-neuron-specific set of genes associated with exc-7, including aquaporins and a gene involved in excretory cell formation (Figure S2). Our technique, on the other hand, automatically identifies a subset of microarray experiments with strong neuronal signals, and thus we are able to uncover neuron-specific functional interactions that are not immediately visible in a global correlation network.


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)

Tissue-specific weighted correlation networks allow elucidation of tissue-specific gene function.Top 20 predicted interactions partners and strongest inter-partner interactions are shown. Genes are colored according to known tissue-specific function: yellow indicates neuronal function, and red indicates involvement in a germ-line/oocyte process. (A) Neuron-specific network around exc-7. An extended SVM algorithm was used to predict tissue-specific functional interactions. Although exc-7 is best characterized as playing a role in the formation of the excretory cell, it has also been shown to regulate cholinergic synaptic transmission. Many of its functional interaction partners are consistent with this neuron-specific function. (B)Tissue-specific networks for let-60. let-60 is the homolog of mammalian Ras protein that is involved, among other processes, in chemosensation and progression through meiosis during oogenesis. The functional interaction partners identified for let-60 are completely different in the neuron and germ line networks, reflecting that this gene plays a different functional role in the context of different tissues.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1000417-g006: Tissue-specific weighted correlation networks allow elucidation of tissue-specific gene function.Top 20 predicted interactions partners and strongest inter-partner interactions are shown. Genes are colored according to known tissue-specific function: yellow indicates neuronal function, and red indicates involvement in a germ-line/oocyte process. (A) Neuron-specific network around exc-7. An extended SVM algorithm was used to predict tissue-specific functional interactions. Although exc-7 is best characterized as playing a role in the formation of the excretory cell, it has also been shown to regulate cholinergic synaptic transmission. Many of its functional interaction partners are consistent with this neuron-specific function. (B)Tissue-specific networks for let-60. let-60 is the homolog of mammalian Ras protein that is involved, among other processes, in chemosensation and progression through meiosis during oogenesis. The functional interaction partners identified for let-60 are completely different in the neuron and germ line networks, reflecting that this gene plays a different functional role in the context of different tissues.
Mentions: Using an SVM-based approach, we are able to integrate microarray data into different tissue-specific functional interaction networks. Such networks link genes that are likely to participate in the same process within a specific tissue context and contain information that may otherwise be overwhelmed in a global view of co-expression. As an example, we considered exc-7, an RNA-binding protein that is involved in the formation of the excretory canal, but that also plays a role in neuronal development, affecting cholinergic synaptic transmission [59]. Several of the interaction partners present in its neuron-specific interaction network support our understanding of exc-7 neuronal function (Figure 6A): hmr-1 is required for the outgrowth of some motor neurons [60]; unc-38 is an acetylcholine receptor [12]; and the mammalian homolog of abl-1 is involved in post-synaptic acetylcholine receptor clustering [61]. Another partner, rhgf-1, a RhoGEF, is known to regulate neurotransmitter release at the neuromuscular junction [62]. Our network results also suggest an interaction between exc-7 and smg-1, a key component of the nonsense-mediated mRNA decay pathway, and spk-1, which is involved in mRNA splicing [12]. The presence of RNA processing genes among the interaction partners is potentially related to exc-7's RNA-binding function. A standard correlation computation produces an entirely different, non-neuron-specific set of genes associated with exc-7, including aquaporins and a gene involved in excretory cell formation (Figure S2). Our technique, on the other hand, automatically identifies a subset of microarray experiments with strong neuronal signals, and thus we are able to uncover neuron-specific functional interactions that are not immediately visible in a global correlation network.

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
Related in: MedlinePlus