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Coordinated evolution of co-expressed gene clusters in the Drosophila transcriptome.

Mezey JG, Nuzhdin SV, Ye F, Jones CD - BMC Evol. Biol. (2008)

Bottom Line: We used a common microarray platform to measure gene expression in seven closely related species in the Drosophila melanogaster subgroup, accounting for confounding effects of sequence divergence.Our results demonstrate that co-evolution of expression in gene clusters is relatively common among species in the D. melanogaster subgroup.We consider the possibility that local regulation of expression in gene clusters may drive the connection between adaptive sequence and coordinated gene expression evolution.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA. jgm45@cornell.edu

ABSTRACT

Background: Co-expression of genes that physically cluster together is a common characteristic of eukaryotic transcriptomes. This organization of transcriptomes suggests that coordinated evolution of gene expression for clustered genes may also be common. Clusters where expression evolution of each gene is not independent of their neighbors are important units for understanding transcriptome evolution.

Results: We used a common microarray platform to measure gene expression in seven closely related species in the Drosophila melanogaster subgroup, accounting for confounding effects of sequence divergence. To summarize the correlation structure among genes in a chromosomal region, we analyzed the fraction of variation along the first principal component of the correlation matrix. We analyzed the correlation for blocks of consecutive genes to assess patterns of correlation that may be manifest at different scales of coordinated expression. We find that expression of physically clustered genes does evolve in a coordinated manner in many locations throughout the genome. Our analysis shows that relatively few of these clusters are near heterochromatin regions and that these clusters tend to be over-dispersed relative to the rest of the genome. This suggests that these clusters are not the byproduct of local gene clustering. We also analyzed the pattern of co-expression among neighboring genes within a single Drosophila species: D. simulans. For the co-expression clusters identified within this species, we find an under-representation of genes displaying a signature of recurrent adaptive amino acid evolution consistent with previous findings. However, clusters displaying co-evolution of expression among species are enriched for adaptively evolving genes. This finding points to a tie between adaptive sequence evolution and evolution of the transcriptome.

Conclusion: Our results demonstrate that co-evolution of expression in gene clusters is relatively common among species in the D. melanogaster subgroup. We consider the possibility that local regulation of expression in gene clusters may drive the connection between adaptive sequence and coordinated gene expression evolution.

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Heat map of p-values resulting from the sliding window analysis within D. simulans projected onto the D. melanogaster genome. Color coding follows Figure 2.
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Figure 3: Heat map of p-values resulting from the sliding window analysis within D. simulans projected onto the D. melanogaster genome. Color coding follows Figure 2.

Mentions: Similar results were obtained for the analysis of within species co-expression for D. simulans (Table 2, Figure 3). Many windows on all chromosomes at all scales were significant. Interestingly, the test of a genome-wide pattern produced significant results for window sizes of 2 (p-value < 0.04) and 10 (p-value < 0.01). While this could be interpreted as an artifact of microaray design [36,37], there is no regular spacing to the distribution of significant windows [28]. Interestingly, there was little overlap between the significant windows identified as evolving across species and being co-expressed within D. simulans (Table 3). The number of overlapping windows obtained when comparing repeated analysis of mean expression levels for all species and the number of overlapping windows for repeated analysis of the D. simulans data (i.e. non-overlap due to permutation effects) are presented for comparison. Given that many of the co-evolving expression clusters and the co-expression clusters identified within D. simulans may reflect false positives, a small fraction of overlap between these cluster types might be expected. However, even at a conservative cutoff (p-value < 0.001) the absolute number of overlapping clusters is still very low (Table 3) indicating that there is little correspondence. It therefore appears that completely different sets of genes are involved in the pattern of co-expression within species compared to those where expression evolves in a coordinated manner across species.


Coordinated evolution of co-expressed gene clusters in the Drosophila transcriptome.

Mezey JG, Nuzhdin SV, Ye F, Jones CD - BMC Evol. Biol. (2008)

Heat map of p-values resulting from the sliding window analysis within D. simulans projected onto the D. melanogaster genome. Color coding follows Figure 2.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2266709&req=5

Figure 3: Heat map of p-values resulting from the sliding window analysis within D. simulans projected onto the D. melanogaster genome. Color coding follows Figure 2.
Mentions: Similar results were obtained for the analysis of within species co-expression for D. simulans (Table 2, Figure 3). Many windows on all chromosomes at all scales were significant. Interestingly, the test of a genome-wide pattern produced significant results for window sizes of 2 (p-value < 0.04) and 10 (p-value < 0.01). While this could be interpreted as an artifact of microaray design [36,37], there is no regular spacing to the distribution of significant windows [28]. Interestingly, there was little overlap between the significant windows identified as evolving across species and being co-expressed within D. simulans (Table 3). The number of overlapping windows obtained when comparing repeated analysis of mean expression levels for all species and the number of overlapping windows for repeated analysis of the D. simulans data (i.e. non-overlap due to permutation effects) are presented for comparison. Given that many of the co-evolving expression clusters and the co-expression clusters identified within D. simulans may reflect false positives, a small fraction of overlap between these cluster types might be expected. However, even at a conservative cutoff (p-value < 0.001) the absolute number of overlapping clusters is still very low (Table 3) indicating that there is little correspondence. It therefore appears that completely different sets of genes are involved in the pattern of co-expression within species compared to those where expression evolves in a coordinated manner across species.

Bottom Line: We used a common microarray platform to measure gene expression in seven closely related species in the Drosophila melanogaster subgroup, accounting for confounding effects of sequence divergence.Our results demonstrate that co-evolution of expression in gene clusters is relatively common among species in the D. melanogaster subgroup.We consider the possibility that local regulation of expression in gene clusters may drive the connection between adaptive sequence and coordinated gene expression evolution.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA. jgm45@cornell.edu

ABSTRACT

Background: Co-expression of genes that physically cluster together is a common characteristic of eukaryotic transcriptomes. This organization of transcriptomes suggests that coordinated evolution of gene expression for clustered genes may also be common. Clusters where expression evolution of each gene is not independent of their neighbors are important units for understanding transcriptome evolution.

Results: We used a common microarray platform to measure gene expression in seven closely related species in the Drosophila melanogaster subgroup, accounting for confounding effects of sequence divergence. To summarize the correlation structure among genes in a chromosomal region, we analyzed the fraction of variation along the first principal component of the correlation matrix. We analyzed the correlation for blocks of consecutive genes to assess patterns of correlation that may be manifest at different scales of coordinated expression. We find that expression of physically clustered genes does evolve in a coordinated manner in many locations throughout the genome. Our analysis shows that relatively few of these clusters are near heterochromatin regions and that these clusters tend to be over-dispersed relative to the rest of the genome. This suggests that these clusters are not the byproduct of local gene clustering. We also analyzed the pattern of co-expression among neighboring genes within a single Drosophila species: D. simulans. For the co-expression clusters identified within this species, we find an under-representation of genes displaying a signature of recurrent adaptive amino acid evolution consistent with previous findings. However, clusters displaying co-evolution of expression among species are enriched for adaptively evolving genes. This finding points to a tie between adaptive sequence evolution and evolution of the transcriptome.

Conclusion: Our results demonstrate that co-evolution of expression in gene clusters is relatively common among species in the D. melanogaster subgroup. We consider the possibility that local regulation of expression in gene clusters may drive the connection between adaptive sequence and coordinated gene expression evolution.

Show MeSH
Related in: MedlinePlus