Commentary To Pool , or Not to Pool ?

IN this issue of Genetics, Futschik and Schlötterer (2010) present one of the first and the most systematic explorations of the relative merits of pooling vs. individual sequencing for several genetics applications. They argue that pooling individuals is often more effective both for SNP discovery and for the estimation of allele frequencies (and thus for population genomic analyses) and as a result can be more cost effective because less sequencing effort is required to obtain the same precision of estimates. While the authors’ results are strictly correct for the models that they examine, application of the innovative and powerful statistical framework that they have developed may be used to show that, for a wide range of applications, pooling is in fact less desirable than individual sequencing. Given the prevalence and importance of current and future whole-genome sequencing projects, it is worthwhile to carefully consider these results. The authors begin by considering SNP detection and comparing pooling experiments to individual sequencing. Building upon the work of Eberle and Kruglyak (2000), they derive both type I and type II errors under both schemes. The authors find, as expected, that the relative efficiency of pooling depends upon not only expected coverage, but also upon the minimum number of reads required for allele calling. The trade-off in power is clear: pooling is less efficient when coverage is small, whereas individual sequencing becomes less efficient with higher expected coverage. However, regardless of the assumed model of sequencing errors, SNP calling from pools is shown to be accompanied by a tremendously high probability of sequencing errors, unless the minimum coverage depth required to make a call is quite high. And herein lies the major drawback of the pooling approach. The authors propose two possible corrections to address this unacceptably high error rate: (1) naturally, if an unbiased estimate of sequencing error is known, this estimate could be used as a correction in subsequent analysis; and (2) in the likely absence of this knowledge, the authors propose a minimum required allele frequency for inclusion of a site in SNP-based analyses. Based on the assumption that sequencing errors will be rare if this minimum frequency is sufficiently large, this approach resigns itself to the loss of a tremendous amount of information—notable particularly given the importance of low-frequency alleles in population genetics analyses ranging from the detection of patterns of hitchhiking (Maynard-Smith and Haigh 1974), to the quantification of positive (Przeworski 2002) and purifying selection (Charlesworth et al. 1993), to the estimation of demographic parameters (e.g., Thornton and Andolfatto 2006). Perhaps more importantly, the precise application modeled by the authors, ‘‘SNP detection,’’ might subtly differ from the application that many readers may consider performing themselves. The application of the Futschik and Schlötterer model has the goal of discovering markers, which can subsequently be assayed in future experiments. This application is, of course, an important one, particularly in systems that have not yet seen much genomic analysis. Conversely, it is an experiment of essentially no utility in systems such as the human or fly, where SNP discovery has been extensively performed. Importantly, the key idea behind this experiment is that discovered SNPs are ‘‘exchangeable.’’ The user cares only about the total number of markers discovered and is untroubled by the fact that, if the experiment were repeated many times, the precise SNPs discovered would change with each experiment. In the context of human genetics, for example, the more common experiment is often called ‘‘medical resequencing’’ and follows a general structure: N individuals who have some common disorder are sequenced, as are K individuals free of the disorder. The experiment determines whether these N individuals also share certain ‘‘kinds’’ of mutations (stop codons, replacement sites, etc.) disproportionately. In this experiment, the precise individuals sequenced and the precise variants discovered matter, and because of that, one comes to a very different conclusion about the relative merits of pooling. Futschik and Schlötterer’s Corresponding author: Department of Human Genetics, Emory University School of Medicine, 343 Whitehead Bldg., 615 Michael St., Atlanta, GA 30322. E-mail: [email protected]