A major question in understanding the variation in DNA sequences within and between species is how important are selective constraints in determining this variation. Differential survivorship and fertility of individuals carrying different gene forms is of interest both for an understanding of the evolution of genes and from the standpoint of health, since so many human diseases are influenced, if not directly caused, by genetic variants. Except for a few cases of very strong physiological effect, it is not possible to detect selective differences by direct observation, so it has become necessary to use statistical tests on observed DNA sequence variation in populations. These tests, however, depend on a large array of assumptions that are not met in real populations. This research project will use large-scale computer simulation of populations to ask under what conditions the statistical tests presently used can actually detect selection and under what conditions an apparent detection of natural selection is really a consequence of the fact that populations deviate in various ways from the underlying assumptions of the tests about population history and structure. The ultimate goal is to prescribe the most powerful test procedures that are not unduly sensitive to unmet assumptions. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM070543-02
Application #
6893381
Study Section
Genetics Study Section (GEN)
Program Officer
Eckstrand, Irene A
Project Start
2004-07-01
Project End
2008-01-31
Budget Start
2005-07-01
Budget End
2007-01-31
Support Year
2
Fiscal Year
2005
Total Cost
$100,860
Indirect Cost
Name
Harvard University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
082359691
City
Cambridge
State
MA
Country
United States
Zip Code
02138
Shpak, Max; Wakeley, John; Garrigan, Daniel et al. (2010) A structured coalescent process for seasonally fluctuating populations. Evolution 64:1395-409
Garrigan, Daniel; Lewontin, Richard; Wakeley, John (2010) Measuring the sensitivity of single-locus ""neutrality tests"" using a direct perturbation approach. Mol Biol Evol 27:73-89