Northwest Sci-Tech University of Agriculture and Forestry,Yangling, Shaanxi 712100,China 2.Kunming Institute of Zoology,the Chinese Academy of Sciences,Kunming,Yunnan 650223,China 3. Xuzhou Normal University,Xuzhou,Jiangsu 221116,China
Although noncoding regions play an important role in gene expression and regulation,it is difficult to detect natural selection at this level. Recently,some studies use the ratio (ω) between the nucleotide substitution rate in the detected regions and the nucleotide substitution rate in neutral regions as an indicator to detect natural selection in noncoding regions. However,to the noncoding regions,its more informative to identify those nucleotide sites under positive selection. We developed a new maximum likelihood method to detect natural selection at the nucleotide site level and to identify those nucleotide sites that may contribute to functional divergence. This method can be applied to both coding regions and noncoding regions. Appling this method to previous reported genes that subjected to positive selection shows that this method is efficient to detect natural selection on nucleotide sites both in coding regions and noncoding regions.