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MicroRNA profiling of rhesus macaque embryonic stem cells.

Sun Z, Wei Q, Zhang Y, He X, Ji W, Su B - BMC Genomics (2011)

Bottom Line: We established three rESC lines and profiled microRNA using Solexa sequencing resulting in 304 known and 66 novel miRNAs.MiRNA expression patterns are generally conserved between species.However, species and/or lineage specific miRNA regulation changed during evolution.

View Article: PubMed Central - HTML - PubMed

Affiliation: State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.

ABSTRACT

Background: MicroRNAs (miRNAs) play important roles in embryonic stem cell (ESC) self-renewal and pluripotency. Numerous studies have revealed human and mouse ESC miRNA profiles. As a model for human-related study, the rhesus macaque is ideal for delineating the regulatory mechanisms of miRNAs in ESCs. However, studies on rhesus macaque (r)ESCs are lacking due to limited rESC availability and a need for systematic analyses of fundamental rESC characteristics.

Results: We established three rESC lines and profiled microRNA using Solexa sequencing resulting in 304 known and 66 novel miRNAs. MiRNA profiles were highly conserved between rESC lines and predicted target genes were significantly enriched in differentiation pathways. Further analysis of the miRNA-target network indicated that gene expression regulated by miRNAs was negatively correlated to their evolutionary rate in rESCs. Moreover, a cross-species comparison revealed an overall conservation of miRNA expression patterns between human, mouse and rhesus macaque ESCs. However, we identified three miRNA clusters (miR-467, the miRNA cluster in the imprinted Dlk1-Dio3 region and C19MC) that showed clear interspecies differences.

Conclusions: rESCs share a unique miRNA set that may play critical roles in self-renewal and pluripotency. MiRNA expression patterns are generally conserved between species. However, species and/or lineage specific miRNA regulation changed during evolution.

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The degree of genes regulated by miRNAs is negatively correlated with their evolutionary rate in rESCs. (A): The correlation coefficient (r = -0.564 with P = 0.018 based on Pearson's correlation) between dN/dS ratios and degrees of genes regulated by miRNAs in rESCs; (B): The correlation coefficient (r = -0.556 with P = 0.039 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 1 kb; (C): The correlation coefficient (r = -0.533 with P = 0.019 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 2 kb; (D): The degree of miRNAs and their targets in the random network is significantly lower (p < 2.2e-16 with a Wilcoxon rank sum test) compared with those in the MT network.
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Figure 4: The degree of genes regulated by miRNAs is negatively correlated with their evolutionary rate in rESCs. (A): The correlation coefficient (r = -0.564 with P = 0.018 based on Pearson's correlation) between dN/dS ratios and degrees of genes regulated by miRNAs in rESCs; (B): The correlation coefficient (r = -0.556 with P = 0.039 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 1 kb; (C): The correlation coefficient (r = -0.533 with P = 0.019 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 2 kb; (D): The degree of miRNAs and their targets in the random network is significantly lower (p < 2.2e-16 with a Wilcoxon rank sum test) compared with those in the MT network.

Mentions: A systematic survey of miRNAs that interacted with targets may provide a better understanding of miRNA regulation in stem cells. Thus, we analyzed potential interactions between miRNAs and their targets, which is termed as the miRNA-target network (MT network). All miRNAs and their targets were used to generate a bipartite graph of miRNA-target interactions.. Nodes represent miRNAs or target genes and edges correspond to interactions between miRNAs with target genes. Node degree in the MT network is the number of connections or edges with other nodes. For each target gene node, degrees represent the number of miRNAs targeting the gene. Globally, the MT network was comprised of 8,934 nodes with 48,546 edges. Using MT network degree analysis (see methods), the degree of genes regulated by miRNAs was negatively correlated (r = -0.564 with p = 0.018 based on Pearson's correlation) with their evolutionary rate (dN/dS) (Figure 4A). Similarly, a previous study reported a negative correlation between the degree and evolutionary rate of proteins in a protein-protein interaction network [27].


MicroRNA profiling of rhesus macaque embryonic stem cells.

Sun Z, Wei Q, Zhang Y, He X, Ji W, Su B - BMC Genomics (2011)

The degree of genes regulated by miRNAs is negatively correlated with their evolutionary rate in rESCs. (A): The correlation coefficient (r = -0.564 with P = 0.018 based on Pearson's correlation) between dN/dS ratios and degrees of genes regulated by miRNAs in rESCs; (B): The correlation coefficient (r = -0.556 with P = 0.039 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 1 kb; (C): The correlation coefficient (r = -0.533 with P = 0.019 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 2 kb; (D): The degree of miRNAs and their targets in the random network is significantly lower (p < 2.2e-16 with a Wilcoxon rank sum test) compared with those in the MT network.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3117859&req=5

Figure 4: The degree of genes regulated by miRNAs is negatively correlated with their evolutionary rate in rESCs. (A): The correlation coefficient (r = -0.564 with P = 0.018 based on Pearson's correlation) between dN/dS ratios and degrees of genes regulated by miRNAs in rESCs; (B): The correlation coefficient (r = -0.556 with P = 0.039 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 1 kb; (C): The correlation coefficient (r = -0.533 with P = 0.019 based on Pearson's correlation) between dN/dS ratios and degrees with normalization of 3'UTR length per 2 kb; (D): The degree of miRNAs and their targets in the random network is significantly lower (p < 2.2e-16 with a Wilcoxon rank sum test) compared with those in the MT network.
Mentions: A systematic survey of miRNAs that interacted with targets may provide a better understanding of miRNA regulation in stem cells. Thus, we analyzed potential interactions between miRNAs and their targets, which is termed as the miRNA-target network (MT network). All miRNAs and their targets were used to generate a bipartite graph of miRNA-target interactions.. Nodes represent miRNAs or target genes and edges correspond to interactions between miRNAs with target genes. Node degree in the MT network is the number of connections or edges with other nodes. For each target gene node, degrees represent the number of miRNAs targeting the gene. Globally, the MT network was comprised of 8,934 nodes with 48,546 edges. Using MT network degree analysis (see methods), the degree of genes regulated by miRNAs was negatively correlated (r = -0.564 with p = 0.018 based on Pearson's correlation) with their evolutionary rate (dN/dS) (Figure 4A). Similarly, a previous study reported a negative correlation between the degree and evolutionary rate of proteins in a protein-protein interaction network [27].

Bottom Line: We established three rESC lines and profiled microRNA using Solexa sequencing resulting in 304 known and 66 novel miRNAs.MiRNA expression patterns are generally conserved between species.However, species and/or lineage specific miRNA regulation changed during evolution.

View Article: PubMed Central - HTML - PubMed

Affiliation: State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.

ABSTRACT

Background: MicroRNAs (miRNAs) play important roles in embryonic stem cell (ESC) self-renewal and pluripotency. Numerous studies have revealed human and mouse ESC miRNA profiles. As a model for human-related study, the rhesus macaque is ideal for delineating the regulatory mechanisms of miRNAs in ESCs. However, studies on rhesus macaque (r)ESCs are lacking due to limited rESC availability and a need for systematic analyses of fundamental rESC characteristics.

Results: We established three rESC lines and profiled microRNA using Solexa sequencing resulting in 304 known and 66 novel miRNAs. MiRNA profiles were highly conserved between rESC lines and predicted target genes were significantly enriched in differentiation pathways. Further analysis of the miRNA-target network indicated that gene expression regulated by miRNAs was negatively correlated to their evolutionary rate in rESCs. Moreover, a cross-species comparison revealed an overall conservation of miRNA expression patterns between human, mouse and rhesus macaque ESCs. However, we identified three miRNA clusters (miR-467, the miRNA cluster in the imprinted Dlk1-Dio3 region and C19MC) that showed clear interspecies differences.

Conclusions: rESCs share a unique miRNA set that may play critical roles in self-renewal and pluripotency. MiRNA expression patterns are generally conserved between species. However, species and/or lineage specific miRNA regulation changed during evolution.

Show MeSH
Related in: MedlinePlus