Dataset Information

The random nature of genome architecture: predicting open reading frame distributions.

ABSTRACT:

Background

A better understanding of the size and abundance of open reading frames (ORFS) in whole genomes may shed light on the factors that control genome complexity. Here we examine the statistical distributions of open reading frames (i.e. distribution of start and stop codons) in the fully sequenced genomes of 297 prokaryotes, and 14 eukaryotes.

Methodology/principal findings

By fitting mixture models to data from whole genome sequences we show that the size-frequency distributions for ORFS are strikingly similar across prokaryotic and eukaryotic genomes. Moreover, we show that i) a large fraction (60-80%) of ORF size-frequency distributions can be predicted a priori with a stochastic assembly model based on GC content, and that (ii) size-frequency distributions of the remaining "non-random" ORFs are well-fitted by log-normal or gamma distributions, and similar to the size distributions of annotated proteins.

Conclusions/significance

Our findings suggest stochastic processes have played a primary role in the evolution of genome complexity, and that common processes govern the conservation and loss of functional genomics units in both prokaryotes and eukaryotes.

SUBMITTER: McCoy MW

PROVIDER: S-EPMC2714469 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

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Publications

The random nature of genome architecture: predicting open reading frame distributions.

McCoy Michael W MW Allen Andrew P AP Gillooly James F JF

PloS one 20090730 7

<h4>Background</h4>A better understanding of the size and abundance of open reading frames (ORFS) in whole genomes may shed light on the factors that control genome complexity. Here we examine the statistical distributions of open reading frames (i.e. distribution of start and stop codons) in the fully sequenced genomes of 297 prokaryotes, and 14 eukaryotes.<h4>Methodology/principal findings</h4>By fitting mixture models to data from whole genome sequences we show that the size-frequency distrib ...[more]

PMID: 19649247

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Project description:Translation of an mRNA in eukaryotes starts at AUG in most cases. Near-cognate codons (NCCs) such as UUG, ACG and AUU are also used as start sites at low levels in S. cerevisiae. Initiation from NCCs or AUGs in the 5’-untranslated regions (UTRs) of mRNAs can lead to translation of upstream open reading frames (uORFs) that might regulate expression of the main ORF (mORF). Although there is some circumstantial evidence that the translation of uORFs can be affected by environmental conditions, little is known about how it is affected by changes in growth temperature. Using reporter assays, we found that changes in growth temperature can affect translation from NCC start sites in yeast cells, suggesting the possibility that gene expression could be regulated by temperature by altering use of different uORF start codons. Using ribosome profiling, we provide evidence that growth temperature regulates the efficiency of translation of nearly 200 uORFs in S. cerevisiae. Of these uORFs, most that start with an AUG codon have increased translational efficiency at 37 ˚C relative to 30 ˚C and decreased efficiency at 20 ˚C. For translationally regulated uORFs starting with NCCs, we did not observe a general trend for the direction of regulation as a function of temperature, suggesting mRNA-specific features can determine the mode of temperature-dependent regulation. Consistent with this conclusion, the position of the uORFs in the 5’-leader relative to the 5’-cap and the start codon of the main ORF correlates with the direction of temperature-dependent regulation of uORF translation. We have identified several novel cases in which changes in uORF translation are inversely correlated with changes in the translational efficiency of the downstream main ORF. Our data suggest that translation of these mRNAs is subject to temperature-dependent, uORF-mediated regulation. Overall, our data suggest that alterations in the translation of specific uORFs by temperature can regulate gene expression in S. cerevisiae.

Dataset Information

The random nature of genome architecture: predicting open reading frame distributions.

Background

Methodology/principal findings

Conclusions/significance

Publications

The random nature of genome architecture: predicting open reading frame distributions.

Similar Datasets

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