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deltaBS

A high-throughput screen for functionally important genetic variation

Comparing the genomes of bacteria associated with different niches or phenotypes can reveal the genetic mechanisms driving key differences in lifestyle and virulence. However, bacteria mutate frequently and there are often a large number of mutations that differentiate individual strains. Some of these mutations will have large impacts on phenotype, while others will have little to no measurable impact.

 

deltaBS provides a way to scan through the protein-coding genes of bacteria for mutations that are rarely observed in nature, and are therefore likely to be selected against under most circumstances. This is an effective method for identifying gene degradation associated with niche adaptation.

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deltaBS uses profile hidden Markov models that take a diverse collection of sequences of the same gene from different organisms and capture patterns of sequence variation that occur commonly in nature. These models are used to score the protein-coding genes of different strains of bacteria to produce bitscores, which indicate how well each protein conforms to modelled sequence constraints on that gene. Differences between these bitscores (delta-bitscores) can then be used to identify genes that may be undergoing functional adaptation or degradation.

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For more advice on whether this approach is suitable for your data, email me

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