Erratum

Advances and Limits of Using Population Genetics to Understand Local Adaptation: (Trends in Ecology & Evolution 29, 673–680; 2014)(S0169534714002237)(10.1016/j.tree.2014.10.004)

Peter L Tiffin, Jeffrey Ross-Ibarra

Research output: Contribution to journalComment/debate

1 Citation (Scopus)

Abstract

In our manuscript exploring the population genetics of local adaptation [1] we included a discussion about the potential uses of reduced representation data (e.g., RAD-seq, GBS). To provide a sense of the probability of using reduced representation data to identify targets of selection, we included a figure showing the probability of having a SNP included in a region of the genome in which diversity had been severely reduced due to a recent selective sweep. Unfortunately this figure is not correct; an error in the code inadvertently used centimorgans as morgans, causing the recombination rate to be off by a factor of 100. To correct this we have generated a new figure that corrects this error and presents a more realistic model (Figure 1). Our previous model assumed SNPs were distributed evenly across the genome and the presence of a single SNP near a sweep was sufficient for detection. Instead, here we explicitly model sequence ‘tags’ coming from RAD-seq or GBS, and we incorporate information about the variation in diversity expected among tags in neutral regions of the genome. The figure clearly shows that with dense marker coverage and strong selection, the probability of detecting reductions in diversity due to recent selective sweeps from new beneficial mutations can be relatively high. We emphasize, however, that the purpose of the figure is solely to develop an intuition of the likelihood of detecting a recent selective sweep. The many simplifying assumptions made in generating the figure (no recent demographic change, both sequence tags and recombination occur uniformly along the genome, selection is on a novel beneficial mutation with additive effect that has recently swept to fixation), as well as the specific mutation rates, sample size, sequence length, and recombination rates assumed will all affect the actual probability of a tag being included in a selective sweep. Moreover, this figure does not touch on many other relevant issues such as multiple testing, complex demography, background selection, or other modes of positive selection (e.g., from standing variation, balancing selection, or selection on polygenic traits).

Original languageEnglish (US)
Pages (from-to)801-802
Number of pages2
JournalTrends in Ecology and Evolution
Volume32
Issue number10
DOIs
StatePublished - Oct 1 2017

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local adaptation
population genetics
ecology
genome
mutation
recombination
touch (sensation)
additive effect
demography
demographic statistics
trend
fixation
testing
sampling
rate

PubMed: MeSH publication types

  • Journal Article
  • Published Erratum

Cite this

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title = "Erratum: Advances and Limits of Using Population Genetics to Understand Local Adaptation: (Trends in Ecology & Evolution 29, 673–680; 2014)(S0169534714002237)(10.1016/j.tree.2014.10.004)",
abstract = "In our manuscript exploring the population genetics of local adaptation [1] we included a discussion about the potential uses of reduced representation data (e.g., RAD-seq, GBS). To provide a sense of the probability of using reduced representation data to identify targets of selection, we included a figure showing the probability of having a SNP included in a region of the genome in which diversity had been severely reduced due to a recent selective sweep. Unfortunately this figure is not correct; an error in the code inadvertently used centimorgans as morgans, causing the recombination rate to be off by a factor of 100. To correct this we have generated a new figure that corrects this error and presents a more realistic model (Figure 1). Our previous model assumed SNPs were distributed evenly across the genome and the presence of a single SNP near a sweep was sufficient for detection. Instead, here we explicitly model sequence ‘tags’ coming from RAD-seq or GBS, and we incorporate information about the variation in diversity expected among tags in neutral regions of the genome. The figure clearly shows that with dense marker coverage and strong selection, the probability of detecting reductions in diversity due to recent selective sweeps from new beneficial mutations can be relatively high. We emphasize, however, that the purpose of the figure is solely to develop an intuition of the likelihood of detecting a recent selective sweep. The many simplifying assumptions made in generating the figure (no recent demographic change, both sequence tags and recombination occur uniformly along the genome, selection is on a novel beneficial mutation with additive effect that has recently swept to fixation), as well as the specific mutation rates, sample size, sequence length, and recombination rates assumed will all affect the actual probability of a tag being included in a selective sweep. Moreover, this figure does not touch on many other relevant issues such as multiple testing, complex demography, background selection, or other modes of positive selection (e.g., from standing variation, balancing selection, or selection on polygenic traits).",
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N2 - In our manuscript exploring the population genetics of local adaptation [1] we included a discussion about the potential uses of reduced representation data (e.g., RAD-seq, GBS). To provide a sense of the probability of using reduced representation data to identify targets of selection, we included a figure showing the probability of having a SNP included in a region of the genome in which diversity had been severely reduced due to a recent selective sweep. Unfortunately this figure is not correct; an error in the code inadvertently used centimorgans as morgans, causing the recombination rate to be off by a factor of 100. To correct this we have generated a new figure that corrects this error and presents a more realistic model (Figure 1). Our previous model assumed SNPs were distributed evenly across the genome and the presence of a single SNP near a sweep was sufficient for detection. Instead, here we explicitly model sequence ‘tags’ coming from RAD-seq or GBS, and we incorporate information about the variation in diversity expected among tags in neutral regions of the genome. The figure clearly shows that with dense marker coverage and strong selection, the probability of detecting reductions in diversity due to recent selective sweeps from new beneficial mutations can be relatively high. We emphasize, however, that the purpose of the figure is solely to develop an intuition of the likelihood of detecting a recent selective sweep. The many simplifying assumptions made in generating the figure (no recent demographic change, both sequence tags and recombination occur uniformly along the genome, selection is on a novel beneficial mutation with additive effect that has recently swept to fixation), as well as the specific mutation rates, sample size, sequence length, and recombination rates assumed will all affect the actual probability of a tag being included in a selective sweep. Moreover, this figure does not touch on many other relevant issues such as multiple testing, complex demography, background selection, or other modes of positive selection (e.g., from standing variation, balancing selection, or selection on polygenic traits).

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