Statistical Tests for Detecting Positive Selection by Utilizing High-Frequency Variants

Author:

Zeng Kai12,Fu Yun-Xin34,Shi Suhua1,Wu Chung-I2

Affiliation:

1. State Key Laboratory of Biocontrol and Key Laboratory of Gene Engineering of the Ministry of Education, Sun Yat-sen University, Guangzhou 510275, China

2. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637

3. Human Genetics Center, School of Public Health, University of Texas, Houston, Texas 77030 and

4. Laboratory for Conservation and Utilization of Bioresources, Yunnan University, Kunming 650091, China

Abstract

Abstract By comparing the low-, intermediate-, and high-frequency parts of the frequency spectrum, we gain information on the evolutionary forces that influence the pattern of polymorphism in population samples. We emphasize the high-frequency variants on which positive selection and negative (background) selection exhibit different effects. We propose a new estimator of θ (the product of effective population size and neutral mutation rate), θL, which is sensitive to the changes in high-frequency variants. The new θL allows us to revise Fay and Wu's H-test by normalization. To complement the existing statistics (the H-test and Tajima's D-test), we propose a new test, E, which relies on the difference between θL and Watterson's θW. We show that this test is most powerful in detecting the recovery phase after the loss of genetic diversity, which includes the postselective sweep phase. The sensitivities of these tests to (or robustness against) background selection and demographic changes are also considered. Overall, D and H in combination can be most effective in detecting positive selection while being insensitive to other perturbations. We thus propose a joint test, referred to as the DH test. Simulations indicate that DH is indeed sensitive primarily to directional selection and no other driving forces.

Publisher

Oxford University Press (OUP)

Subject

Genetics

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