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The Multivariate Correlation Between Translating MRNA And Proteins And Its Biological Relevance

Posted on:2018-03-30Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y Z CuiFull Text:PDF
GTID:1310330536983696Subject:Cell biology
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As a well-known phenomenon in the central dogma of molecular biology,total mRNAs poorly correlate to proteins in their abundances as reported.Recent findings have concluded that such an abundance correlation falls into the range of R2 = 0.01-0.50,no matter using the mRNA or the translating mRNAs(ribosome nascent-chain complex-bound mRNAs,RNC-mRNAs)to fit the protein.This represents an unresolved question in the central dogma for years.In this study,we analysed the abundances of mRNA,RNC-mRNA and protein in a genomewide scale.We analyzed the protein relative abudance comparing the human lung cancer A549 and H1299 cells with the human bronchial epithelium derived H292 cells,respectively.In parallel,we reanalyzed the absolute quantitation of hepatocellular carcinoma Hep3 B,MHCC97-H and HCCLM3 cells,respectively.We found that a strong correlation between RNC-mRNAs and proteins both in their relative or absolute abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor.The R2 reached over 0.96 in the comparison between lung cancer cells and greater than 0.85 in all three hepatocellular carcinoma cells,respectively.This correlation highlighted that the mRNA length significantly contributes to the translational modulation,especially to the translational initiation,favored by its correlation with the mRNA translation ratio(TR)as observed.We found that TR was highly phenotype specific,which was substantiated by both pathway analysis and biased TRs of the splice variants of the 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.
Keywords/Search Tags:RNC-mRNA, Multivariate linear model, Proteome, Next generation sequencing
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