Abstract
A common problem in molecular comparative geno- mics is the identification of genes that are under positive, adaptive selection [1]. Such genes are likely to be crucial for speciation, species differentiation, and func- tional specialization. However, discerning the difference between positive selection and relaxation of func- tional constraint can be difficult using current methods. Both processes generally increase the rate of ami- no acid change relative to synonymous changes within coding regions, and unless the amino acid rate is over- whelmingly high across an entire gene, the signature of positive selection can be obscured [2]. Some methodologies do not explicitly determine the difference be- tween a relaxation of functional constraint and positive selection, leaving researchers to determine via other means whether the trajectory of a gene has been specialization or creation of a new function, or removal from the genome via a process of degeneration.
Highlights
Most current methods evaluate the possibility of positive selection based on the exchangeabilities of amino acids
Discerning the difference between positive selection and relaxation of functional constraint can be difficult using current methods. Both processes generally increase the rate of amino acid change relative to synonymous changes within coding regions, and unless the amino acid rate is overwhelmingly high across an entire gene, the signature of positive selection can be obscured [2]
Zinc finger proteins are a group of protein families classified based upon their conserved sequence motif, and they are capable of binding DNA, RNA, protein and/or lipid substrates following their coordination with one or more zinc atoms [15,16,17]
Summary
Most current methods evaluate the possibility of positive selection based on the exchangeabilities of amino acids. The rationale is that if an observed amino acid substitution has a low probability in terms of their amino acids’ physio-chemical properties, it is more probable that the substitution may be driven by selection events. Charge, and amino acid structural properties (via Karlin and Ghandour [3]) and genetic and structural similarity (from Feng et al, [4]) are common methods. Based on evolutionary distance measures from a 1,572 amino acid change data set in 71 closely related proteins, PAM stands for “percent-accepted matrix” [5]. It set the path for most matrices to come
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