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Positive correlation between gene coexpression and positional clustering in the zebrafish genome.

Ng YK, Wu W, Zhang L - BMC Genomics (2009)

Bottom Line: This paper analyzes correlation between the proximity of eukaryotic genes and their transcriptional expression pattern in the zebrafish (Danio rerio) genome using available microarray data and gene annotation.The analyses show that neighbouring genes are significantly coexpressed in the zebrafish genome, and the coexpression level is influenced by the intergenic distance and transcription orientation.This fact is further supported by examining the coexpression level of genes within positional clusters in the neighbourhood model.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mathematics, National University of Singapore, 2 Science Drive 2, Singapore 117543, Singapore. matnyk@nus.edu.sg

ABSTRACT

Background: Co-expressing genes tend to cluster in eukaryotic genomes. This paper analyzes correlation between the proximity of eukaryotic genes and their transcriptional expression pattern in the zebrafish (Danio rerio) genome using available microarray data and gene annotation.

Results: The analyses show that neighbouring genes are significantly coexpressed in the zebrafish genome, and the coexpression level is influenced by the intergenic distance and transcription orientation. This fact is further supported by examining the coexpression level of genes within positional clusters in the neighbourhood model. There is a positive correlation between gene coexpression and positional clustering in the zebrafish genome.

Conclusion: The study provides another piece of evidence for the hypothesis that coexpressed genes do cluster in the eukaryotic genomes.

Show MeSH
Mean of pair-wise R values in blocks of size 3 to 20 (▲), shown with standard error. This is compared to the mean of 100 values obtained similarly, each from the same analysis after a random permutation of: (1) the gene order of the entire genome (△); (2) the order of genes in each chromosome (□); (3) the order of non-overlapping blocks of 3 consecutive genes (■). Plots (△), (□) and (■) are shown with standard deviations. The points in (A) are from analyses with the full dataset, while (B) are from analyses after tandem duplicates are removed.
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Figure 2: Mean of pair-wise R values in blocks of size 3 to 20 (▲), shown with standard error. This is compared to the mean of 100 values obtained similarly, each from the same analysis after a random permutation of: (1) the gene order of the entire genome (△); (2) the order of genes in each chromosome (□); (3) the order of non-overlapping blocks of 3 consecutive genes (■). Plots (△), (□) and (■) are shown with standard deviations. The points in (A) are from analyses with the full dataset, while (B) are from analyses after tandem duplicates are removed.

Mentions: To further explore the coexpression of proximate genes, we partitioned the genes into non-overlapping blocks of k (3 ≤ k ≤ 20) physically adjacent genes according to their start position. For each gene block, we calculated a mean R of the coexpression values; then the mean of all the mean Rs is calculated and plotted in Figure 2. The degree of coexpression first decreases and then becomes stable when the block size k increases from 3 to 20. To verify the significance of the coexpression degree of the genes for each block size, we compared them to what would have been obtained if the genes had been rearranged in each of the following three ways: (1) randomly permuting the gene order over the entire genome; (2) randomly permuting the order of genes within each chromosome; and (3) randomly permuting the order of non-overlapping blocks of 3 consecutive genes. The last rearrangement is used to examine whether the coexpression degree in the larger blocks are dominated mainly by genes that are separated by only one or two genes. The analyses show that there is a significant difference in degree of coexpression between actual and randomized genome (Figure 2). Finally, we remark that the start point for partitioning the genes into non-overlapping blocks has little effect on the analysis presented above because of the way we calculate the mean coexpression value of genes within a block.


Positive correlation between gene coexpression and positional clustering in the zebrafish genome.

Ng YK, Wu W, Zhang L - BMC Genomics (2009)

Mean of pair-wise R values in blocks of size 3 to 20 (▲), shown with standard error. This is compared to the mean of 100 values obtained similarly, each from the same analysis after a random permutation of: (1) the gene order of the entire genome (△); (2) the order of genes in each chromosome (□); (3) the order of non-overlapping blocks of 3 consecutive genes (■). Plots (△), (□) and (■) are shown with standard deviations. The points in (A) are from analyses with the full dataset, while (B) are from analyses after tandem duplicates are removed.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2654907&req=5

Figure 2: Mean of pair-wise R values in blocks of size 3 to 20 (▲), shown with standard error. This is compared to the mean of 100 values obtained similarly, each from the same analysis after a random permutation of: (1) the gene order of the entire genome (△); (2) the order of genes in each chromosome (□); (3) the order of non-overlapping blocks of 3 consecutive genes (■). Plots (△), (□) and (■) are shown with standard deviations. The points in (A) are from analyses with the full dataset, while (B) are from analyses after tandem duplicates are removed.
Mentions: To further explore the coexpression of proximate genes, we partitioned the genes into non-overlapping blocks of k (3 ≤ k ≤ 20) physically adjacent genes according to their start position. For each gene block, we calculated a mean R of the coexpression values; then the mean of all the mean Rs is calculated and plotted in Figure 2. The degree of coexpression first decreases and then becomes stable when the block size k increases from 3 to 20. To verify the significance of the coexpression degree of the genes for each block size, we compared them to what would have been obtained if the genes had been rearranged in each of the following three ways: (1) randomly permuting the gene order over the entire genome; (2) randomly permuting the order of genes within each chromosome; and (3) randomly permuting the order of non-overlapping blocks of 3 consecutive genes. The last rearrangement is used to examine whether the coexpression degree in the larger blocks are dominated mainly by genes that are separated by only one or two genes. The analyses show that there is a significant difference in degree of coexpression between actual and randomized genome (Figure 2). Finally, we remark that the start point for partitioning the genes into non-overlapping blocks has little effect on the analysis presented above because of the way we calculate the mean coexpression value of genes within a block.

Bottom Line: This paper analyzes correlation between the proximity of eukaryotic genes and their transcriptional expression pattern in the zebrafish (Danio rerio) genome using available microarray data and gene annotation.The analyses show that neighbouring genes are significantly coexpressed in the zebrafish genome, and the coexpression level is influenced by the intergenic distance and transcription orientation.This fact is further supported by examining the coexpression level of genes within positional clusters in the neighbourhood model.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Mathematics, National University of Singapore, 2 Science Drive 2, Singapore 117543, Singapore. matnyk@nus.edu.sg

ABSTRACT

Background: Co-expressing genes tend to cluster in eukaryotic genomes. This paper analyzes correlation between the proximity of eukaryotic genes and their transcriptional expression pattern in the zebrafish (Danio rerio) genome using available microarray data and gene annotation.

Results: The analyses show that neighbouring genes are significantly coexpressed in the zebrafish genome, and the coexpression level is influenced by the intergenic distance and transcription orientation. This fact is further supported by examining the coexpression level of genes within positional clusters in the neighbourhood model. There is a positive correlation between gene coexpression and positional clustering in the zebrafish genome.

Conclusion: The study provides another piece of evidence for the hypothesis that coexpressed genes do cluster in the eukaryotic genomes.

Show MeSH