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Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific.

Wang T, Cui Y, Jin J, Guo J, Wang G, Yin X, He QY, Zhang G - Nucleic Acids Res. (2013)

Bottom Line: This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed.We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs.These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Institute of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China. tongwang@jnu.edu.cn

ABSTRACT
As a well-known phenomenon, total mRNAs poorly correlate to proteins in their abundances as reported. Recent findings calculated with bivariate models suggested even poorer such correlation, whereas focusing on the translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) subset. In this study, we analysed the relative abundances of mRNAs, RNC-mRNAs and proteins on genome-wide scale, comparing human lung cancer A549 and H1299 cells with normal human bronchial epithelial (HBE) cells, respectively. As discovered, a strong correlation between RNC-mRNAs and proteins in their relative abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor. The R(2) reached 0.94 and 0.97 in A549 versus HBE and H1299 versus HBE comparisons, respectively. This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed. We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs. These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

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Gene identification in translatome and transcriptome sequencing, in comparison with SILAC-based mass spectrometry. (A and B) Number of genes and proteins identified with RNA-seq (lighter circles) and MS (dark circle), respectively, in A549 cells (A) and HBE cells (B). (C and D) RNC-mRNA abundance distribution in A549 cells (C) and HBE cells (D). Genes were step-wise classified, based on abundances of quantified RNC-mRNA. Each bar indicates gene number of detection in its respective category. In each category, the percentage of the number of MS quantifiable protein to the number of genes that are detected by RNC-mRNA sequencing is shown with a dot. (E) Validation of gene detection in RNC-mRNA, extracted from A549 and HBE cells, respectively. Six randomly selected genes were subjected to RT-PCR assays and indicated by HGNC gene names.
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gkt178-F2: Gene identification in translatome and transcriptome sequencing, in comparison with SILAC-based mass spectrometry. (A and B) Number of genes and proteins identified with RNA-seq (lighter circles) and MS (dark circle), respectively, in A549 cells (A) and HBE cells (B). (C and D) RNC-mRNA abundance distribution in A549 cells (C) and HBE cells (D). Genes were step-wise classified, based on abundances of quantified RNC-mRNA. Each bar indicates gene number of detection in its respective category. In each category, the percentage of the number of MS quantifiable protein to the number of genes that are detected by RNC-mRNA sequencing is shown with a dot. (E) Validation of gene detection in RNC-mRNA, extracted from A549 and HBE cells, respectively. Six randomly selected genes were subjected to RT-PCR assays and indicated by HGNC gene names.

Mentions: Genes detected by mRNA and RNC-mRNA sequencing in both cell lines showed a remarkable overlap, indicating that the majority of transcribed mRNAs were translated (Figure 2A and B, Supplementary Table S3). Regarding RNC-mRNA data set, a total of 11 686 genes in A549 cells (Figure 2A) and 11 911 genes in HBE cells (Figure 2B) were mapped with ≥10 reads, which is considered as the threshold of quantifiable genes in RNA-seq data (34). In the SILAC experiments (A549 versus HBE cells), a total of 4803 proteins were identified, among which 3045 proteins were identified with at least two unique peptides, and 2934 proteins contained quantifiable information (Ratio H/L Normalized) (Figure 2A and B). The detailed protein list is included in the Supplementary Table S4. We observed that all of the MS-quantified proteins were also detected in RNC-mRNAs in A549 cells (Figure 2A). Similar detection pattern was also observed in experiments performed with HBE cells, although minor proportion of outliers was noted (Figure 2B).Figure 2.


Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific.

Wang T, Cui Y, Jin J, Guo J, Wang G, Yin X, He QY, Zhang G - Nucleic Acids Res. (2013)

Gene identification in translatome and transcriptome sequencing, in comparison with SILAC-based mass spectrometry. (A and B) Number of genes and proteins identified with RNA-seq (lighter circles) and MS (dark circle), respectively, in A549 cells (A) and HBE cells (B). (C and D) RNC-mRNA abundance distribution in A549 cells (C) and HBE cells (D). Genes were step-wise classified, based on abundances of quantified RNC-mRNA. Each bar indicates gene number of detection in its respective category. In each category, the percentage of the number of MS quantifiable protein to the number of genes that are detected by RNC-mRNA sequencing is shown with a dot. (E) Validation of gene detection in RNC-mRNA, extracted from A549 and HBE cells, respectively. Six randomly selected genes were subjected to RT-PCR assays and indicated by HGNC gene names.
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gkt178-F2: Gene identification in translatome and transcriptome sequencing, in comparison with SILAC-based mass spectrometry. (A and B) Number of genes and proteins identified with RNA-seq (lighter circles) and MS (dark circle), respectively, in A549 cells (A) and HBE cells (B). (C and D) RNC-mRNA abundance distribution in A549 cells (C) and HBE cells (D). Genes were step-wise classified, based on abundances of quantified RNC-mRNA. Each bar indicates gene number of detection in its respective category. In each category, the percentage of the number of MS quantifiable protein to the number of genes that are detected by RNC-mRNA sequencing is shown with a dot. (E) Validation of gene detection in RNC-mRNA, extracted from A549 and HBE cells, respectively. Six randomly selected genes were subjected to RT-PCR assays and indicated by HGNC gene names.
Mentions: Genes detected by mRNA and RNC-mRNA sequencing in both cell lines showed a remarkable overlap, indicating that the majority of transcribed mRNAs were translated (Figure 2A and B, Supplementary Table S3). Regarding RNC-mRNA data set, a total of 11 686 genes in A549 cells (Figure 2A) and 11 911 genes in HBE cells (Figure 2B) were mapped with ≥10 reads, which is considered as the threshold of quantifiable genes in RNA-seq data (34). In the SILAC experiments (A549 versus HBE cells), a total of 4803 proteins were identified, among which 3045 proteins were identified with at least two unique peptides, and 2934 proteins contained quantifiable information (Ratio H/L Normalized) (Figure 2A and B). The detailed protein list is included in the Supplementary Table S4. We observed that all of the MS-quantified proteins were also detected in RNC-mRNAs in A549 cells (Figure 2A). Similar detection pattern was also observed in experiments performed with HBE cells, although minor proportion of outliers was noted (Figure 2B).Figure 2.

Bottom Line: This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed.We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs.These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Institute of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China. tongwang@jnu.edu.cn

ABSTRACT
As a well-known phenomenon, total mRNAs poorly correlate to proteins in their abundances as reported. Recent findings calculated with bivariate models suggested even poorer such correlation, whereas focusing on the translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) subset. In this study, we analysed the relative abundances of mRNAs, RNC-mRNAs and proteins on genome-wide scale, comparing human lung cancer A549 and H1299 cells with normal human bronchial epithelial (HBE) cells, respectively. As discovered, a strong correlation between RNC-mRNAs and proteins in their relative abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor. The R(2) reached 0.94 and 0.97 in A549 versus HBE and H1299 versus HBE comparisons, respectively. This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed. We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs. These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

Show MeSH
Related in: MedlinePlus