01924nas a2200313   4500000000100000008004100001260001300042653002100055653002800076653001000104653002400114653002500138653002100163653002000184653002400204653001300228653001500241653002300256653002300279100001100302700001400313700001400327700001400341245007600355300001100431490000700442520114700449022001401596       2010                            d  c2010 Mar10aBase Composition10aChi-Square Distribution10aCodon10aComputer Simulation10aEvolution, Molecular10aGenes, Protozoan10aModels, Genetic10aModels, Statistical10aMutation10aPlasmodium10aSelection, Genetic10aSequence Alignment1 aYap VB1 aLindsay H1 aEasteal S1 aHuttley G00aEstimates of the effect of natural selection on protein-coding content.  a726-340 v273 a<p>Analysis of natural selection is key to understanding many core biological processes, including the emergence of competition, cooperation, and complexity, and has important applications in the targeted development of vaccines. Selection is hard to observe directly but can be inferred from molecular sequence variation. For protein-coding nucleotide sequences, the ratio of nonsynonymous to synonymous substitutions (omega) distinguishes neutrally evolving sequences (omega = 1) from those subjected to purifying (omega < 1) or positive Darwinian (omega > 1) selection. We show that current models used to estimate omega are substantially biased by naturally occurring sequence compositions. We present a novel model that weights substitutions by conditional nucleotide frequencies and which escapes these artifacts. Applying it to the genomes of pathogens causing malaria, leprosy, tuberculosis, and Lyme disease gave significant discrepancies in estimates with approximately 10-30% of genes affected. Our work has substantial implications for how vaccine targets are chosen and for studying the molecular basis of adaptive evolution.</p>  a1537-1719