Methods to detect selection in populations with applications to the human.

Area of Science:

• Population genetics
• Molecular evolution
• Statistical genomics

Background:

• Statistical tests for natural selection at the DNA level have been developed over the past 13 years.
• Current methods rely on the neutral theory of molecular evolution as a null hypothesis.
• Departures from neutral expectations may indicate natural selection or linked selection.

Purpose of the Study:

• To review the current state of statistical tests for natural selection at the DNA level.
• To describe available tests and their underlying assumptions.
• To discuss challenges in interpreting results, particularly in non-equilibrium populations.

Main Methods:

• Review of existing statistical tests for natural selection.
• Application of neutral evolution theory as a null hypothesis.
• Analysis of population genetic data, including human mitochondrial DNA.

Main Results:

• Various statistical tests for DNA-level selection are available.
• Interpreting departures from neutrality is complicated by factors like mutation-drift disequilibrium and population subdivision.
• Distinguishing selection from demographic hypotheses in human mitochondrial DNA remains difficult.

Conclusions:

• The development of statistical tests for natural selection has progressed significantly.
• Non-equilibrium population dynamics and structure complicate the detection of selection.
• Further population genetic data and improved null models are needed to better define alternatives to selection.