84
D. Enard
sequencing data may not accurately represent the true frequency in the sample if
sequencing depth is too low. Sequencing depth is more convenient to handle than
ascertainment bias. Indeed, sequencing depth unlike ascertainment bias can be
readily measured and is therefore much easier to take into account. The process
of imputation further makes it possible to infer alleles in regions of the genome
with insufficient sequencing depth (Li et al. 2009).
– The confounding factors of selection. Confident detection of positive selection
is always challenging due to the multiple confounding factors that create the
same signatures in diversity as positive selection. The choice of a specific test of
selection thus depends on which confounding factors are acceptable and which
are not in a particular study context.
Demographic history represents the most important confounding factor of
selection. Indeed both decreases and increases in population size can create
local signatures that are undistinguishable from the signatures left by a local
event of positive selection. Increases in population size or population expansions
affect both the SFS and haplotype structure. Population expansion creates
an increased influx of new, low-frequency mutations. The main effect of a
population expansion is therefore to skew the SFS toward rare alleles, just
like hitchhiking. Decreases in population size or bottlenecks can also severely
confound tests of selection. Bottlenecks can either result in an excess of rare
alleles, due to all lineages coalescing during the bottleneck, or lead to an excess
of intermediate-frequency alleles, if only a few lineages make it through the
bottleneck into the larger ancestral population. Either of these effects can occur
depending on the specific parameter (e.g., timing and severity) of the bottleneck.
Thus, there could be depletion in genetic variation or an excess of rare alleles that
can be mistaken with selection. Specific haplotypes can reach high frequency
quickly during a bottleneck, which can also mimic selection.
References
Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth
GT, McVean GA (2012) An integrated map of genetic variation from 1,092 human genomes.
Nature 491(7422):56–65
Achaz G (2009) Frequency spectrum neutrality tests: one for all and all for one. Genetics
183(1):249–258
Akey JM (2009) Constructing genomic maps of positive selection in humans: where do we go from
here? Genome Res 19(5):711–722
Andres AM, Hubisz MJ, Indap A, Torgerson DG, Degenhardt JD, Boyko AR, Gutenkunst RN,
White TJ, Green ED, Bustamante CD et al (2009) Targets of balancing selection in the human
genome. Mol Biol Evol 26(12):2755–2764
Bergland AO, Behrman EL, O’Brien KR, Schmidt PS, Petrov DA (2014) Genomic evidence of
rapid and stable adaptive oscillations over seasonal time scales in Drosophila. PLoS Genet
10(11):e1004775
Bersaglieri T, Sabeti PC, Patterson N, Vanderploeg T, Schaffner SF, Drake JA, Rhodes M, Reich
DE, Hirschhorn JN (2004) Genetic signatures of strong recent positive selection at the lactase
gene. Am J Hum Genet 74(6):1111–1120
D. Enard
sequencing data may not accurately represent the true frequency in the sample if
sequencing depth is too low. Sequencing depth is more convenient to handle than
ascertainment bias. Indeed, sequencing depth unlike ascertainment bias can be
readily measured and is therefore much easier to take into account. The process
of imputation further makes it possible to infer alleles in regions of the genome
with insufficient sequencing depth (Li et al. 2009).
– The confounding factors of selection. Confident detection of positive selection
is always challenging due to the multiple confounding factors that create the
same signatures in diversity as positive selection. The choice of a specific test of
selection thus depends on which confounding factors are acceptable and which
are not in a particular study context.
Demographic history represents the most important confounding factor of
selection. Indeed both decreases and increases in population size can create
local signatures that are undistinguishable from the signatures left by a local
event of positive selection. Increases in population size or population expansions
affect both the SFS and haplotype structure. Population expansion creates
an increased influx of new, low-frequency mutations. The main effect of a
population expansion is therefore to skew the SFS toward rare alleles, just
like hitchhiking. Decreases in population size or bottlenecks can also severely
confound tests of selection. Bottlenecks can either result in an excess of rare
alleles, due to all lineages coalescing during the bottleneck, or lead to an excess
of intermediate-frequency alleles, if only a few lineages make it through the
bottleneck into the larger ancestral population. Either of these effects can occur
depending on the specific parameter (e.g., timing and severity) of the bottleneck.
Thus, there could be depletion in genetic variation or an excess of rare alleles that
can be mistaken with selection. Specific haplotypes can reach high frequency
quickly during a bottleneck, which can also mimic selection.
References
Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth
GT, McVean GA (2012) An integrated map of genetic variation from 1,092 human genomes.
Nature 491(7422):56–65
Achaz G (2009) Frequency spectrum neutrality tests: one for all and all for one. Genetics
183(1):249–258
Akey JM (2009) Constructing genomic maps of positive selection in humans: where do we go from
here? Genome Res 19(5):711–722
Andres AM, Hubisz MJ, Indap A, Torgerson DG, Degenhardt JD, Boyko AR, Gutenkunst RN,
White TJ, Green ED, Bustamante CD et al (2009) Targets of balancing selection in the human
genome. Mol Biol Evol 26(12):2755–2764
Bergland AO, Behrman EL, O’Brien KR, Schmidt PS, Petrov DA (2014) Genomic evidence of
rapid and stable adaptive oscillations over seasonal time scales in Drosophila. PLoS Genet
10(11):e1004775
Bersaglieri T, Sabeti PC, Patterson N, Vanderploeg T, Schaffner SF, Drake JA, Rhodes M, Reich
DE, Hirschhorn JN (2004) Genetic signatures of strong recent positive selection at the lactase
gene. Am J Hum Genet 74(6):1111–1120