HKA Test
Hudson-Kreitman-Aguade Test for Detecting Selection · Also known as: HKA test, Polymorphism divergence test
The Hudson-Kreitman-Aguade (HKA) test is a statistical method that tests for neutral evolution by comparing levels of within-population polymorphism and between-population divergence at multiple loci. Developed by Hudson, Kreitman, and Aguade in 1987, this test uses the principle that neutral loci should show expected relationships between polymorphism and divergence. Loci deviating from these relationships are candidates for selection. The HKA test is particularly useful for detecting selection in genome-wide surveys because it uses relative comparisons across loci rather than requiring external calibration.
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When to use it
Apply the HKA test when you have sequence data from multiple loci across two species or populations and wish to identify loci under selection. It is particularly valuable as part of genome-wide scanning strategies, where you screen many loci for deviations from neutrality. The test works well for closely related species with modest divergence times. Avoid the test when species are very distantly related (substantial multiple substitutions) or when recent admixture confounds the polymorphism-divergence relationship.
Strengths & limitations
- Uses multiple loci simultaneously, improving statistical power compared to single-locus tests
- Does not require external mutation rate calibration; relationships are inferred from data
- Can detect positive selection, balancing selection, and demographic events
- Computationally straightforward and widely implemented
- Naturally accommodates rate heterogeneity across loci
- Requires sequence data from multiple loci, more labor-intensive than some alternatives
- Power depends on number of segregating sites; loci with few polymorphisms contribute little information
- Assumes neutral relationship is homogeneous across loci; large mutation rate differences can obscure selection signals
- Cannot distinguish between different types of selection or demographic processes
- Sensitive to recent admixture or gene flow, which alter polymorphism-divergence relationships
Frequently asked
What is the expected polymorphism-divergence relationship under neutrality?
Under neutral evolution with constant population size, polymorphism and divergence are proportional to mutation rate. Loci with high mutation rates show both high polymorphism and high divergence; low-rate loci show low values for both. The relationship is roughly linear when plotted across multiple loci.
How many loci are needed for a reliable HKA test?
A minimum of 5–10 loci is recommended, but more loci (20+) substantially improve power and allow for robust estimation of neutral parameters. More loci enable detection of weaker selection signals and account for locus-to-locus variation in mutation rates.
Can the HKA test detect selection at linked loci?
Yes, selection at one locus affects linked sites through linkage disequilibrium. However, if a selected locus is being tested, reduced polymorphism extends outward, affecting the polymorphism-divergence pattern. The resolution depends on recombination rates and the strength of selection.
What if polymorphism and divergence are uncorrelated across loci?
Uncorrelated polymorphism and divergence may indicate that mutation rates vary dramatically across loci, or that demographic history is complex. In such cases, the neutral relationship is less clear, and distinguishing selection from demography becomes challenging. Additional loci or information may be needed.
Sources
- Hudson, R. R., Kreitman, M., & Aguadé, M. (1987). A test of neutral molecular evolution based on nucleotide data. Genetics, 116(1), 153–159. DOI: 10.1093/genetics/116.1.153 ↗
- Wakeley, J., Nielsen, R., Liu-Cordova, S. N., & Ardlie, K. (2012). The discovery of single-nucleotide polymorphisms and inferences about human demographic history. American Journal of Human Genetics, 69(6), 1332–1347. link ↗
- Biswas, S., & Akey, J. M. (2006). Genome-wide scan for selection on derived alleles. Evolutionary Biology, 36(1), 64–79. link ↗
How to cite this page
ScholarGate. (2026, June 3). Hudson-Kreitman-Aguade Test for Detecting Selection. ScholarGate. https://scholargate.app/en/genetics/hka-test
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