Abstract
There is a desire for increasing use of statistical methods in analysing the growing amounts of bio-sequences. We present statistical methods that are useful when a protein alignment can be divided into two groups based on known features or traits. The approach is based on stratification of the data, and to show the applicability of the methods we present analysis of genomic data from proteobacteria orders. A dataset of 25 periplasmic/extracellular bacterial enzyme endonuclease I proteins was compiled to identify genotypic characteristics that separate the cold adapted proteins from ortholog sequences with a higher optimal growth temperature. Our results reveal that the cold adapted protein has a significantly more positively charged exterior. Life in a cold climate seems to be enabled by many minor structural modifications rather than a particular amino acid substitution. Redistribution of charge might be one of the most important signatures for cold adaptation.
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Thorvaldsen, S., Ytterstad, E., Flå, T. (2007). Inferring Weak Adaptations and Selection Biases in Proteins from Composition and Substitution Matrices. In: Măndoiu, I., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2007. Lecture Notes in Computer Science(), vol 4463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72031-7_35
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DOI: https://doi.org/10.1007/978-3-540-72031-7_35
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