Abstract
To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences. Sequentially more genes exhibited extreme (low or high) expression values from TR to RA, and then to TA; that is, cellular coordination of multiple transcriptome regulatory mechanisms leads to sequentially enhanced gene expression selectivity as the genetic information flow from the genome to the proteome. Second, contribution of the stabilization-by-translation regulatory mechanism to the cellular coordination process was assessed. The data enabled an estimation of mRNA stability, revealing a moderate but significant positive correlation between mRNA stability and translation activity. Third, the proportion of mRNA occupied by un-translated regions (UTR) exhibited a negative relationship with the level of this correlation, and was thus a major determinant of the mode of regulation of the mRNA. High-UTR-proportion mRNAs tend to defy the stabilization-by-translation regulatory mechanism, staying out of the polysome but remaining stable; mRNAs with little UTRs largely followed this regulation. In summary, we quantitatively delineated the relationship among multiple transcriptome regulation parameters, i.e., cellular coordination of corresponding regulatory mechanisms.
Highlights
Transcriptome analysis techniques have been coupled to conventional experimental protocols to measure other gene expression parameters
We attempted to explain the discrepancy among gene expression parameters, which seemed mysterious to most scientists, from the perspectives of biochemical pathway/network control and cellular operations
We provide a quantitative analysis of the impact of translation activity on transcriptome regulation, by showing a moderate but significant positive correlation between the mRNA translation index and the RA-transcription rate (TR) index
Summary
Transcriptome analysis techniques have been coupled to conventional experimental protocols to measure other gene expression parameters. Multi-parameter approaches are being used to study the discrepancy and glean out fundamental gene expression regulation principles Such studies will potentially lead to more efficient gene expression analysis strategies that generate more informative data. All techniques are in place for genome-wide integration of transcription rate (i.e., GRO-seq), mRNA abundance (RNA-seq) and mRNA translation activity (i.e., polysome profiling). This will generate an integrative view of the transcriptome and its dynamic regulation, i.e., how the multiple transcriptome regulatory mechanisms are coordinated. We generated a multi-parameter snapshot of the transcriptome by simultaneous genome-wide measurement of transcription rate (TR), mRNA abundance (RA) and translation activity (TA); we estimated mRNA stability/degradation by the RA to TR ratio. Analysis of the data in conjunction with mRNA UTRs revealed further insights into, and the roles of UTRs in, cellular coordination of these transcriptome regulatory mechanisms
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