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Identification and Expression Analysis of Ribosome Biogenesis Factor Co-orthologs in Solanum lycopersicum.

Simm S, Fragkostefanakis S, Paul P, Keller M, Einloft J, Scharf KD, Schleiff E - Bioinform Biol Insights (2015)

Bottom Line: In combination with existing expression profiles, we can conclude that co-orthologs of RBFs by large account for a preferential function in different tissue or at distinct developmental stages.In addition, co-regulated clusters of RBF and RP coding genes have been observed.The relevance of these results is discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Biosciences, Molecular Cell Biology of Plants, Goethe University, Frankfurt/Main, Germany. ; Cluster of Excellence Frankfurt, Goethe University, Frankfurt/Main, Germany.

ABSTRACT
Ribosome biogenesis involves a large inventory of proteinaceous and RNA cofactors. More than 250 ribosome biogenesis factors (RBFs) have been described in yeast. These factors are involved in multiple aspects like rRNA processing, folding, and modification as well as in ribosomal protein (RP) assembly. Considering the importance of RBFs for particular developmental processes, we examined the complexity of RBF and RP (co-)orthologs by bioinformatic assignment in 14 different plant species and expression profiling in the model crop Solanum lycopersicum. Assigning (co-)orthologs to each RBF revealed that at least 25% of all predicted RBFs are encoded by more than one gene. At first we realized that the occurrence of multiple RBF co-orthologs is not globally correlated to the existence of multiple RP co-orthologs. The transcript abundance of genes coding for predicted RBFs and RPs in leaves and anthers of S. lycopersicum was determined by next generation sequencing (NGS). In combination with existing expression profiles, we can conclude that co-orthologs of RBFs by large account for a preferential function in different tissue or at distinct developmental stages. This notion is supported by the differential expression of selected RBFs during male gametophyte development. In addition, co-regulated clusters of RBF and RP coding genes have been observed. The relevance of these results is discussed.

No MeSH data available.


Clustering of RP and RBF genes based on their expression. (A) Mean of the expression values of clustered genes normalized to the TPM determined for MACE leaf sample. Clusters were generated by k-means analysis. Error bars indicate the standard deviation. The clusters are ordered according to the number of factors present (first value) and the median of the cluster for the leaves (second value) is indicated. The two clusters on the top represent the set of genes that could not be related to a specific profile. (B) The Spearman correlation between the cluster profiles of RPs and RBFs was calculated, and the highest value for each column and each row is shown. Only values with strong correlation (above 0.5) are highlighted.
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f7-bbi-9-2015-001: Clustering of RP and RBF genes based on their expression. (A) Mean of the expression values of clustered genes normalized to the TPM determined for MACE leaf sample. Clusters were generated by k-means analysis. Error bars indicate the standard deviation. The clusters are ordered according to the number of factors present (first value) and the median of the cluster for the leaves (second value) is indicated. The two clusters on the top represent the set of genes that could not be related to a specific profile. (B) The Spearman correlation between the cluster profiles of RPs and RBFs was calculated, and the highest value for each column and each row is shown. Only values with strong correlation (above 0.5) are highlighted.

Mentions: We used the information on transcript abundance established previously33 to analyze the expression profiles of RBF and RP coding genes. The expression profiles of the genes encoding for RPs and RBFs have been assigned to six clusters (see Methods). While each cluster contains RPs or RBFs with distinct profiles, one cluster for each set (21 rp and 68 rbf) represents a collection of genes that did not match (extremely high error bars) the profiles of any of the other clusters (Fig. 7A; 21 RP genes and 68 RBF genes). Subsequently, the correlations between the profiles of RP and RBF genes have been determined excluding the above-mentioned cluster (Fig. 7B). We realized that two profiles are highly correlative (Fig. 7B, black), with a correlation value of 0.97. The genes of these two clusters show a moderate expression in roots and stem tissues; a lower expression in leaves, anthers, and flowers; and a higher but by large similar expression in all analyzed fruit samples. These genes encode for 15 RPLs, 12 RPSs, 8 90S RBFs, 7 60S RBFs, 1 40S RBF, 1 Exonuclease RBF, 1 Exosome RBF, 1 TRAMP complex RBF, and one not assigned RBF. This might point toward a specific functional relation between these RPs and RFBs, which is discussed below.


Identification and Expression Analysis of Ribosome Biogenesis Factor Co-orthologs in Solanum lycopersicum.

Simm S, Fragkostefanakis S, Paul P, Keller M, Einloft J, Scharf KD, Schleiff E - Bioinform Biol Insights (2015)

Clustering of RP and RBF genes based on their expression. (A) Mean of the expression values of clustered genes normalized to the TPM determined for MACE leaf sample. Clusters were generated by k-means analysis. Error bars indicate the standard deviation. The clusters are ordered according to the number of factors present (first value) and the median of the cluster for the leaves (second value) is indicated. The two clusters on the top represent the set of genes that could not be related to a specific profile. (B) The Spearman correlation between the cluster profiles of RPs and RBFs was calculated, and the highest value for each column and each row is shown. Only values with strong correlation (above 0.5) are highlighted.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4325683&req=5

f7-bbi-9-2015-001: Clustering of RP and RBF genes based on their expression. (A) Mean of the expression values of clustered genes normalized to the TPM determined for MACE leaf sample. Clusters were generated by k-means analysis. Error bars indicate the standard deviation. The clusters are ordered according to the number of factors present (first value) and the median of the cluster for the leaves (second value) is indicated. The two clusters on the top represent the set of genes that could not be related to a specific profile. (B) The Spearman correlation between the cluster profiles of RPs and RBFs was calculated, and the highest value for each column and each row is shown. Only values with strong correlation (above 0.5) are highlighted.
Mentions: We used the information on transcript abundance established previously33 to analyze the expression profiles of RBF and RP coding genes. The expression profiles of the genes encoding for RPs and RBFs have been assigned to six clusters (see Methods). While each cluster contains RPs or RBFs with distinct profiles, one cluster for each set (21 rp and 68 rbf) represents a collection of genes that did not match (extremely high error bars) the profiles of any of the other clusters (Fig. 7A; 21 RP genes and 68 RBF genes). Subsequently, the correlations between the profiles of RP and RBF genes have been determined excluding the above-mentioned cluster (Fig. 7B). We realized that two profiles are highly correlative (Fig. 7B, black), with a correlation value of 0.97. The genes of these two clusters show a moderate expression in roots and stem tissues; a lower expression in leaves, anthers, and flowers; and a higher but by large similar expression in all analyzed fruit samples. These genes encode for 15 RPLs, 12 RPSs, 8 90S RBFs, 7 60S RBFs, 1 40S RBF, 1 Exonuclease RBF, 1 Exosome RBF, 1 TRAMP complex RBF, and one not assigned RBF. This might point toward a specific functional relation between these RPs and RFBs, which is discussed below.

Bottom Line: In combination with existing expression profiles, we can conclude that co-orthologs of RBFs by large account for a preferential function in different tissue or at distinct developmental stages.In addition, co-regulated clusters of RBF and RP coding genes have been observed.The relevance of these results is discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Biosciences, Molecular Cell Biology of Plants, Goethe University, Frankfurt/Main, Germany. ; Cluster of Excellence Frankfurt, Goethe University, Frankfurt/Main, Germany.

ABSTRACT
Ribosome biogenesis involves a large inventory of proteinaceous and RNA cofactors. More than 250 ribosome biogenesis factors (RBFs) have been described in yeast. These factors are involved in multiple aspects like rRNA processing, folding, and modification as well as in ribosomal protein (RP) assembly. Considering the importance of RBFs for particular developmental processes, we examined the complexity of RBF and RP (co-)orthologs by bioinformatic assignment in 14 different plant species and expression profiling in the model crop Solanum lycopersicum. Assigning (co-)orthologs to each RBF revealed that at least 25% of all predicted RBFs are encoded by more than one gene. At first we realized that the occurrence of multiple RBF co-orthologs is not globally correlated to the existence of multiple RP co-orthologs. The transcript abundance of genes coding for predicted RBFs and RPs in leaves and anthers of S. lycopersicum was determined by next generation sequencing (NGS). In combination with existing expression profiles, we can conclude that co-orthologs of RBFs by large account for a preferential function in different tissue or at distinct developmental stages. This notion is supported by the differential expression of selected RBFs during male gametophyte development. In addition, co-regulated clusters of RBF and RP coding genes have been observed. The relevance of these results is discussed.

No MeSH data available.