Methods for estimating gene frequencies and detecting selection in bacterial populations

Recent breakthroughs in molecular technology, most significantly the polyme rase chain reaction (PCR) and in situ hybridization, have allowed the detec tion of genetic variation in bacterial communities without prior cultivatio n. These methods often produce data in the form of the presence or absence of alleles or genotypes, however, rather than counts of alleles. Using rela tive allele frequencies from presence-absence data as estimates of populati on allele frequencies tends to underestimate tl-le frequencies of common al leles and overestimate those of rare ones, potentially biasing the results of a test of neutrality in favor of balancing selection. In this study, a m aximum-likelihood estimator (MLE) of bacterial allele frequencies designed for use with presence-absence data is derived using an explicit stochastic model of the host infection (or bacterial sampling) process. The performanc e of the MLE is evaluated using computer simulation and a method is present ed for evaluating the fit of estimated allele frequencies to die neutral in finite alleles model (IAM). The methods are applied to estimate allele freq uencies at two outer surface protein loci (ospA and ospC) of the Lyme disea se spirochete, Borrelia burgdorferi, infecting local populations of deer ti cks (Ixodes scapularis) and to test the fit to a neutral IAM.