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Detecting selection using time-series data of allele frequencies with multiple independent reference Loci.

Nishino J - G3 (Bethesda) (2013)

Bottom Line: Recently, in 2013 Feder et al. proposed the frequency increment test (FIT), which evaluates natural selection at a single diallelic locus by the use of time-series data of allele frequencies.Here, we expand upon the FIT by introducing a test that explicitly allows for changes in population size by using information from independent reference loci.Various demographic models suggest that our proposed test is unbiased irrespective of fluctuations in population size when sampling noise can be ignored and that it has greater power to detect selection than the FIT if sufficient reference loci are used.

View Article: PubMed Central - PubMed

Affiliation: Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization of Information and Systems, Mishima, Shizuoka 411-8540, Japan.

ABSTRACT
Recently, in 2013 Feder et al. proposed the frequency increment test (FIT), which evaluates natural selection at a single diallelic locus by the use of time-series data of allele frequencies. This test is unbiased under conditions of constant population size and no sampling noise. Here, we expand upon the FIT by introducing a test that explicitly allows for changes in population size by using information from independent reference loci. Various demographic models suggest that our proposed test is unbiased irrespective of fluctuations in population size when sampling noise can be ignored and that it has greater power to detect selection than the FIT if sufficient reference loci are used.

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Demographic models used in this study. Model 1: constant-size model (N(t) = 104); Model 2: slow-growth (grows exponentially from N(0) = 104 to N(T) = 105); Model 3: moderate-bottleneck model (); Model 4: rapid-growth model (); Model 5: severe-bottleneck model ().
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fig1: Demographic models used in this study. Model 1: constant-size model (N(t) = 104); Model 2: slow-growth (grows exponentially from N(0) = 104 to N(T) = 105); Model 3: moderate-bottleneck model (); Model 4: rapid-growth model (); Model 5: severe-bottleneck model ().

Mentions: Let us consider a population evolving according to the Wright–Fisher model with fluctuating population size. The population size fluctuates as a function of generation time, t, and is denoted by N(t). To investigate the actual type I errors and the powers of Feder et al.’s (2013) FIT and the FITR introduced in this study, we conducted computer simulations under the five demographic models shown in Figure 1. The two alleles at a diallelic locus of interest are denoted by A0 and a0, respectively. At generation times , the frequencies of a0 are denoted by . Here, t0 = 0 and tL = T are the first and the last sampling times, respectively, and the number of sampled times is L + 1. The fitnesses of genotypes A0A0, A0a0, and a0a0 are assumed to be 1, , and , respectively (i.e., no dominance is assumed). The population size, N(t), is independent of the frequency of a0. As described in the next section, the FITR also uses neutral reference loci.


Detecting selection using time-series data of allele frequencies with multiple independent reference Loci.

Nishino J - G3 (Bethesda) (2013)

Demographic models used in this study. Model 1: constant-size model (N(t) = 104); Model 2: slow-growth (grows exponentially from N(0) = 104 to N(T) = 105); Model 3: moderate-bottleneck model (); Model 4: rapid-growth model (); Model 5: severe-bottleneck model ().
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3852378&req=5

fig1: Demographic models used in this study. Model 1: constant-size model (N(t) = 104); Model 2: slow-growth (grows exponentially from N(0) = 104 to N(T) = 105); Model 3: moderate-bottleneck model (); Model 4: rapid-growth model (); Model 5: severe-bottleneck model ().
Mentions: Let us consider a population evolving according to the Wright–Fisher model with fluctuating population size. The population size fluctuates as a function of generation time, t, and is denoted by N(t). To investigate the actual type I errors and the powers of Feder et al.’s (2013) FIT and the FITR introduced in this study, we conducted computer simulations under the five demographic models shown in Figure 1. The two alleles at a diallelic locus of interest are denoted by A0 and a0, respectively. At generation times , the frequencies of a0 are denoted by . Here, t0 = 0 and tL = T are the first and the last sampling times, respectively, and the number of sampled times is L + 1. The fitnesses of genotypes A0A0, A0a0, and a0a0 are assumed to be 1, , and , respectively (i.e., no dominance is assumed). The population size, N(t), is independent of the frequency of a0. As described in the next section, the FITR also uses neutral reference loci.

Bottom Line: Recently, in 2013 Feder et al. proposed the frequency increment test (FIT), which evaluates natural selection at a single diallelic locus by the use of time-series data of allele frequencies.Here, we expand upon the FIT by introducing a test that explicitly allows for changes in population size by using information from independent reference loci.Various demographic models suggest that our proposed test is unbiased irrespective of fluctuations in population size when sampling noise can be ignored and that it has greater power to detect selection than the FIT if sufficient reference loci are used.

View Article: PubMed Central - PubMed

Affiliation: Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Research Organization of Information and Systems, Mishima, Shizuoka 411-8540, Japan.

ABSTRACT
Recently, in 2013 Feder et al. proposed the frequency increment test (FIT), which evaluates natural selection at a single diallelic locus by the use of time-series data of allele frequencies. This test is unbiased under conditions of constant population size and no sampling noise. Here, we expand upon the FIT by introducing a test that explicitly allows for changes in population size by using information from independent reference loci. Various demographic models suggest that our proposed test is unbiased irrespective of fluctuations in population size when sampling noise can be ignored and that it has greater power to detect selection than the FIT if sufficient reference loci are used.

Show MeSH
Related in: MedlinePlus