Do You Use Dna Or Rna To Calculate Fst

This calculator provides a simple way to perform an Fst calculation, a fundamental measure of population differentiation. Enter the allele frequencies for a single biallelic locus in two populations to see how genetically distinct they are. This tool is essential for anyone studying population genetics.

Formula Used: Fst = (Ht – Hs) / Ht. This Fst calculation compares the expected heterozygosity of a total population (Ht) to the average expected heterozygosity of its subpopulations (Hs). A higher value indicates greater differentiation.

Interpretation of Fst Values

Fst Value	Level of Genetic Differentiation
0.00 – 0.05	Little genetic differentiation
0.05 – 0.15	Moderate genetic differentiation
0.15 – 0.25	Great genetic differentiation
> 0.25	Very great genetic differentiation

What is the Fst Calculation? DNA vs. RNA in Genetics

The Fst calculation is a crucial method in population genetics used to measure the genetic differentiation between two or more populations. It quantifies the proportion of total genetic variance at a specific locus that is due to differences in allele frequencies between those populations. The resulting value, the Fixation Index (Fst), ranges from 0 to 1. An Fst of 0 implies that the populations are panmictic (interbreeding freely) and have identical allele frequencies, while an Fst of 1 indicates that the populations are completely separate and fixed for different alleles. When you ask, “do you use dna or rna to calculate fst?”, the fundamental answer is DNA. Genetic variation, the basis for an Fst calculation, originates from differences in the DNA sequence. While RNA is a transcript of DNA, and we can sequence it (as cDNA), the underlying inherited differences are stored in the organism’s DNA. Therefore, population genetics studies, including any Fst calculation, analyze genetic markers found in DNA.

Fst Calculation Formula and Mathematical Explanation

The most common formula for the Fst calculation, developed by Sewall Wright, is based on heterozygosity. It is expressed as:

Fst = (Ht - Hs) / Ht

The process involves these steps:

1. Calculate Expected Heterozygosity within each Subpopulation: For a biallelic locus with allele frequencies p and q, heterozygosity is 2pq. This is done for each subpopulation (e.g., H1 = 2 * p1 * q1, H2 = 2 * p2 * q2).
2. Calculate the Average Subpopulation Heterozygosity (Hs): This is the weighted average of the heterozygosities calculated in the previous step. For two equally sized populations, Hs = (H1 + H2) / 2.
3. Calculate Total Population Heterozygosity (Ht): First, find the average allele frequencies across the total population (e.g., p_total = (p1 + p2) / 2 and q_total = 1 – p_total). Then, calculate Ht as Ht = 2 * p_total * q_total.
4. Perform the final Fst calculation: Substitute Hs and Ht into the main formula. This Fst calculation gives the final value.

Variables in the Fst Calculation

Variable	Meaning	Unit	Typical Range
p1, p2	Frequency of one allele in Population 1 and 2	Frequency (proportion)	0.0 – 1.0
q1, q2	Frequency of the other allele (1-p)	Frequency (proportion)	0.0 – 1.0
Hs	Average expected heterozygosity within subpopulations	Proportion	0.0 – 0.5
Ht	Expected heterozygosity in the total metapopulation	Proportion	0.0 – 0.5
Fst	Fixation Index	Index Value	0.0 – 1.0

Practical Examples of Fst Calculation

Understanding the Fst calculation is easier with practical examples.

Example 1: Moderate Differentiation

Imagine two populations of bighorn sheep separated by a newly built highway. A researcher studies a specific genetic marker.

• Population 1 (East of highway): Allele ‘A’ frequency (p1) = 0.7
• Population 2 (West of highway): Allele ‘A’ frequency (p2) = 0.4

Using the Fst calculator:

• Hs = ((2*0.7*0.3) + (2*0.4*0.6)) / 2 = (0.42 + 0.48) / 2 = 0.45
• Ht = 2 * ((0.7+0.4)/2) * ((0.3+0.6)/2) = 2 * 0.55 * 0.45 = 0.495
• Fst calculation result: (0.495 – 0.45) / 0.495 = 0.091

This Fst of ~0.091 indicates moderate genetic differentiation, suggesting the highway is beginning to limit gene flow between the populations.

Example 2: Low Differentiation

Consider two populations of oak trees in a continuous forest.

• Population 1 (North side): Allele ‘A’ frequency (p1) = 0.55
• Population 2 (South side): Allele ‘A’ frequency (p2) = 0.50

Using the Fst calculator:

• Hs = ((2*0.55*0.45) + (2*0.50*0.50)) / 2 = (0.495 + 0.50) / 2 = 0.4975
• Ht = 2 * ((0.55+0.50)/2) * ((0.45+0.50)/2) = 2 * 0.525 * 0.475 = 0.49875
• Fst calculation result: (0.49875 – 0.4975) / 0.49875 = 0.0025

This very low Fst value indicates almost no genetic differentiation, meaning the two populations are interbreeding freely.

How to Use This Fst Calculator

This tool simplifies the Fst calculation. Follow these steps:

1. Enter Allele Frequencies: Input the frequency of a single allele (e.g., the dominant or reference allele) for a specific gene locus in Population 1 and Population 2. The value must be between 0 and 1.
2. Review Real-Time Results: The calculator instantly performs the Fst calculation. The primary result is the Fst value itself, displayed prominently.
3. Analyze Intermediate Values: Observe Hs and Ht. Seeing how these values differ provides insight into the source of the population structure.
4. Interpret the Fst Value: Use the provided table to understand what your Fst value means, from little to very great differentiation. A proper analysis depends on understanding concepts like genetic drift.

Key Factors That Affect Fst Calculation Results

Several evolutionary forces can influence the outcome of an Fst calculation:

• Gene Flow: High rates of migration and interbreeding between populations will lower Fst values, as it homogenizes allele frequencies.
• Genetic Drift: In small, isolated populations, random chance can cause allele frequencies to change unpredictably, leading to higher Fst values when compared to other populations. Our Hardy-Weinberg calculator can help explore baseline expectations.
• Mutation: While a slow process, the introduction of new alleles through mutation can, over long periods, contribute to differences between populations and increase Fst.
• Selection: If an environment favors a specific allele in one population but not another (divergent selection), it can rapidly increase Fst. Conversely, if selection favors the same alleles in all populations, it can keep Fst low.
• Population Size: Small populations are more susceptible to genetic drift, which tends to increase Fst values over time compared to large populations.
• Time Since Divergence: The longer two populations have been isolated, the more time they have had for drift and mutation to cause their allele frequencies to diverge, resulting in a higher Fst calculation.

Frequently Asked Questions about Fst Calculation

1. Why do you use DNA and not RNA to calculate Fst?

You use DNA because Fst measures differences in heritable genetic variation. This variation is stored in the DNA sequences passed from one generation to the next. RNA is a temporary copy used for protein synthesis and does not represent the stable, heritable genetic code of an individual or population required for a meaningful Fst calculation.

2. What is considered a “high” Fst value?

This is context-dependent. For human populations, an Fst over 0.15 is often considered high. For species known to have very isolated populations, like certain mountaintop insects, an Fst of 0.15 might be considered low. Generally, values above 0.25 indicate very great genetic differentiation. This is a key part of population genetics analysis.

3. Can an Fst calculation be negative?

Theoretically, no, as Ht is designed to be greater than or equal to Hs. However, due to sampling error in real-world data, a calculation might yield a small negative number. This is typically interpreted as an Fst of zero, meaning no differentiation.

4. What does a multi-locus Fst calculation mean?

It means averaging Fst values across many different gene loci throughout the genome. This provides a much more robust and reliable estimate of overall population differentiation than a single-locus Fst calculation, which could be an outlier.

5. How does sample size affect the Fst calculation?

Small sample sizes can lead to inaccurate estimates of the true allele frequencies in a population. This sampling error can cause the calculated Fst to be higher or lower than the actual value. Larger sample sizes provide more confidence in the results.

6. What are Wright’s F-statistics?

Fst is part of a larger set of measures called F-statistics. Others include Fis (measuring inbreeding within an individual relative to their subpopulation) and Fit (measuring inbreeding in an individual relative to the total population). The Fst calculation specifically addresses the structuring among subpopulations.

7. Can I use this calculator for more than two alleles?

This specific Fst calculator is designed for a simple, biallelic system (two alleles). Calculating Fst for multi-allelic loci requires more complex formulas that account for multiple heterozygote combinations.

8. What is the difference between Fst and Gst?

Gst is an equivalent measure of population differentiation. Fst is often used more broadly, while Gst was specifically defined by Nei for multi-allelic loci, but they measure the same concept of among-population variance.