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The impact of gene expression regulation on evolution of extracellular signaling pathways.

Charoensawan V, Adryan B, Martin S, Söllner C, Thisse B, Thisse C, Wright GJ, Teichmann SA - Mol. Cell Proteomics (2010)

Bottom Line: Due to the lack of a comprehensive data set, the evolution of extracellular signaling pathways has remained largely a mystery.We took advantage of known homology between proteins to estimate the relative rates of changes of four parameters after gene duplication, namely extracellular protein interaction, expression pattern, and the divergence of extracellular and intracellular protein sequences.This allows homologous extracellular receptors to attain specialized functions and become specific to tissues and/or developmental stages.

View Article: PubMed Central - PubMed

Affiliation: Medical Research Council Laboratory of Molecular Biology, Cambridge CB20QH, United Kingdom. varodom@mrc-lmb.cam.ac.uk

ABSTRACT
Extracellular protein interactions are crucial to the development of multicellular organisms because they initiate signaling pathways and enable cellular recognition cues. Despite their importance, extracellular protein interactions are often under-represented in large scale protein interaction data sets because most high throughput assays are not designed to detect low affinity extracellular interactions. Due to the lack of a comprehensive data set, the evolution of extracellular signaling pathways has remained largely a mystery. We investigated this question using a combined data set of physical pairwise interactions between zebrafish extracellular proteins, mainly from the immunoglobulin superfamily and leucine-rich repeat families, and their spatiotemporal expression profiles. We took advantage of known homology between proteins to estimate the relative rates of changes of four parameters after gene duplication, namely extracellular protein interaction, expression pattern, and the divergence of extracellular and intracellular protein sequences. We showed that change in expression profile is a major contributor to the evolution of signaling pathways followed by divergence in intracellular protein sequence, whereas extracellular sequence and interaction profiles were relatively more conserved. Rapidly evolving expression profiles will eventually drive other parameters to diverge more quickly because differentially expressed proteins get exposed to different environments and potential binding partners. This allows homologous extracellular receptors to attain specialized functions and become specific to tissues and/or developmental stages.

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Paralogous gene expression patterns evolve rapidly. A, the expression patterns for 27 selected genes (rows) within 11 paralogous clusters were annotated (shaded box represents expressed proteins) using the official anatomical ontology from whole mount in situ hybridization data at both the prim-5 (24 hpf) and long-pec (48 hpf) stages (columns). The genes (rows) were then hierarchically clustered according to the similarity of their expression patterns. The columns were then organized into related tissues (such as different brain regions) as indicated. B, the relationships of the genes clustered according to their expression profiles (taken directly from A) are directly compared with their phylogenetic relationships based on sequence identity. The paralogous clusters are color-coded for ease of comparison.
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Figure 4: Paralogous gene expression patterns evolve rapidly. A, the expression patterns for 27 selected genes (rows) within 11 paralogous clusters were annotated (shaded box represents expressed proteins) using the official anatomical ontology from whole mount in situ hybridization data at both the prim-5 (24 hpf) and long-pec (48 hpf) stages (columns). The genes (rows) were then hierarchically clustered according to the similarity of their expression patterns. The columns were then organized into related tissues (such as different brain regions) as indicated. B, the relationships of the genes clustered according to their expression profiles (taken directly from A) are directly compared with their phylogenetic relationships based on sequence identity. The paralogous clusters are color-coded for ease of comparison.

Mentions: Our previous comparative assessment of the rates of divergence between paralogous and non-paralogous protein pairs suggested that the expression profiles are the most rapidly evolving parameter. In other words, the expression patterns of paralogues were not significantly more conserved than expected when compared with unrelated proteins in the network. To examine this further, we performed a more detailed manual annotation of the expression patterns of 27 genes from 11 paralogous groups that were expressed at the pharyngula and hatching periods of development (Fig. 4). This higher resolution annotation used an average of 24.5 anatomical descriptor terms per gene, compared with 11.2 for the previous annotation, where 10 major organ systems were used (supplemental Fig. S1).


The impact of gene expression regulation on evolution of extracellular signaling pathways.

Charoensawan V, Adryan B, Martin S, Söllner C, Thisse B, Thisse C, Wright GJ, Teichmann SA - Mol. Cell Proteomics (2010)

Paralogous gene expression patterns evolve rapidly. A, the expression patterns for 27 selected genes (rows) within 11 paralogous clusters were annotated (shaded box represents expressed proteins) using the official anatomical ontology from whole mount in situ hybridization data at both the prim-5 (24 hpf) and long-pec (48 hpf) stages (columns). The genes (rows) were then hierarchically clustered according to the similarity of their expression patterns. The columns were then organized into related tissues (such as different brain regions) as indicated. B, the relationships of the genes clustered according to their expression profiles (taken directly from A) are directly compared with their phylogenetic relationships based on sequence identity. The paralogous clusters are color-coded for ease of comparison.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3101855&req=5

Figure 4: Paralogous gene expression patterns evolve rapidly. A, the expression patterns for 27 selected genes (rows) within 11 paralogous clusters were annotated (shaded box represents expressed proteins) using the official anatomical ontology from whole mount in situ hybridization data at both the prim-5 (24 hpf) and long-pec (48 hpf) stages (columns). The genes (rows) were then hierarchically clustered according to the similarity of their expression patterns. The columns were then organized into related tissues (such as different brain regions) as indicated. B, the relationships of the genes clustered according to their expression profiles (taken directly from A) are directly compared with their phylogenetic relationships based on sequence identity. The paralogous clusters are color-coded for ease of comparison.
Mentions: Our previous comparative assessment of the rates of divergence between paralogous and non-paralogous protein pairs suggested that the expression profiles are the most rapidly evolving parameter. In other words, the expression patterns of paralogues were not significantly more conserved than expected when compared with unrelated proteins in the network. To examine this further, we performed a more detailed manual annotation of the expression patterns of 27 genes from 11 paralogous groups that were expressed at the pharyngula and hatching periods of development (Fig. 4). This higher resolution annotation used an average of 24.5 anatomical descriptor terms per gene, compared with 11.2 for the previous annotation, where 10 major organ systems were used (supplemental Fig. S1).

Bottom Line: Due to the lack of a comprehensive data set, the evolution of extracellular signaling pathways has remained largely a mystery.We took advantage of known homology between proteins to estimate the relative rates of changes of four parameters after gene duplication, namely extracellular protein interaction, expression pattern, and the divergence of extracellular and intracellular protein sequences.This allows homologous extracellular receptors to attain specialized functions and become specific to tissues and/or developmental stages.

View Article: PubMed Central - PubMed

Affiliation: Medical Research Council Laboratory of Molecular Biology, Cambridge CB20QH, United Kingdom. varodom@mrc-lmb.cam.ac.uk

ABSTRACT
Extracellular protein interactions are crucial to the development of multicellular organisms because they initiate signaling pathways and enable cellular recognition cues. Despite their importance, extracellular protein interactions are often under-represented in large scale protein interaction data sets because most high throughput assays are not designed to detect low affinity extracellular interactions. Due to the lack of a comprehensive data set, the evolution of extracellular signaling pathways has remained largely a mystery. We investigated this question using a combined data set of physical pairwise interactions between zebrafish extracellular proteins, mainly from the immunoglobulin superfamily and leucine-rich repeat families, and their spatiotemporal expression profiles. We took advantage of known homology between proteins to estimate the relative rates of changes of four parameters after gene duplication, namely extracellular protein interaction, expression pattern, and the divergence of extracellular and intracellular protein sequences. We showed that change in expression profile is a major contributor to the evolution of signaling pathways followed by divergence in intracellular protein sequence, whereas extracellular sequence and interaction profiles were relatively more conserved. Rapidly evolving expression profiles will eventually drive other parameters to diverge more quickly because differentially expressed proteins get exposed to different environments and potential binding partners. This allows homologous extracellular receptors to attain specialized functions and become specific to tissues and/or developmental stages.

Show MeSH