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News & Blogs » Protein News » A New genome Algorithm Can Pinpoint Mutations Favored by Natural Selection
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A New genome Algorithm Can Pinpoint Mutations Favored by Natural Selection

natural selection, mutations, human genome, algorithmsIn a new study published in Nature Methods, scientists have developed a new algorithm that allows for the prediction of mutations favored by natural selection in large regions of the human genome. What does this new study mean for treatment options for genetic disorders?

Researchers needed to study the sequenced genome of a population size of 1000 individuals, so they turned to computational techniques to help perform this project. Researchers created an algorithm entitled iSAFE, which is able to analyze a certain region of the genome and determine which mutation is favored by which selection. Previous studies have been able to detect which regions of the human genome are evolving under which selection pressure, but have not been able to shed light on the specific mutation that responds to that particular selective pressure. This algorithm however, does not need to know the function of the genomic region it is analyzing nor does it require any demographic information since it works by reading population genetic signals imprinted on the genomes of the sampled individuals to identify the mutation. During nature selection, neighboring mutations can essentially “hitchhike” with a mutation that is under positive selection causing a loss in genetic diversity near that mutation. iSAFE is able to exploit the signals of neighboring mutations in order to pinpoint the location of the favored mutation. The algorithm is shedding light on the possibility of understand genetic disorders and possibly pinpoint underlying causes of those disorders; hopefully, paving the way to potential therapeutic targets.

Identifying the favored mutation in a positive selective sweep (February 2018)

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