Abstract
Methods for identifying essential genes currently depend predominantly on biochemical experiments. However, there is demand for improved computational methods for determining gene essentiality. In this study, we used the Hurst exponent, a characteristic parameter to describe long-range correlation in DNA, and analyzed its distribution in 33 bacterial genomes. In most genomes (31 out of 33) the significance levels of the Hurst exponents of the essential genes were significantly higher than for the corresponding full-gene-set, whereas the significance levels of the Hurst exponents of the nonessential genes remained unchanged or increased only slightly. All of the Hurst exponents of essential genes followed a normal distribution, with one exception. We therefore propose that the distribution feature of Hurst exponents of essential genes can be used as a classification index for essential gene prediction in bacteria. For computer-aided design in the field of synthetic biology, this feature can build a restraint for pre- or post-design checking of bacterial essential genes. Moreover, considering the relationship between gene essentiality and evolution, the Hurst exponents could be used as a descriptive parameter related to evolutionary level, or be added to the annotation of each gene.
Highlights
Essential genes are those genes of an organism that are critical for its survival, and their content are highly determined by the circumstances in which the organism lives [1]
Of the four hypothetical distributions, that is, normal, uniform, Poisson, and exponential distribution, our results showed that only a normal distribution was satisfied at various levels
There are more than 5000 bacterial genomes currently available in the NCBI sequence database, far more than the number of objects provided in the DEG database
Summary
Essential genes are those genes of an organism that are critical for its survival, and their content are highly determined by the circumstances in which the organism lives [1]. Essential genes are characterized by lethal mutant phenotypes that block survival or reproduction. Identifying essential genes is important for understanding the minimal requirements for cellular survival, and this information may have practical applications in the fields of medicine and bioengineering [2]. This information may provide insight into the complex mechanisms of cell function and evolution. Single-gene-specific mutagenesis, saturation transposon mutagenesis, and antisense RNA inhibition are employed as traditional approaches [3]. These methods are costly, PLOS ONE | DOI:10.1371/journal.pone.0129716. These methods are costly, PLOS ONE | DOI:10.1371/journal.pone.0129716 June 12, 2015
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