#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Correction: Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data


Authors: Thibaut Paul Patrick Sellinger;  Diala Abu Awad;  Markus Moest;  Aurélien Tellier
Published in the journal: Correction: Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genet 17(4): e1009504. doi:10.1371/journal.pgen.1009504
Category: Correction
doi: https://doi.org/10.1371/journal.pgen.1009504

The mutation and recombination rates reported throughout the article are incorrect by a factor of 2. The captions of Figs 14, Table 2, and S1S19 Figs are incorrect. Additionally, the Y axes of Figs 5 and 6 and S20 Fig are shifted by a factor of 2. The authors provide corrected versions here. The correct rates were used for the simulations (S2 Appendix) and as such this error does not affect the conclusions of the study.

Fig. 1. Estimated demographic history with no selfing or seed banking.
Estimated demographic history with no selfing or seed banking.
Estimated demographic history using four simulated sequences of 30 Mb under a saw-tooth scenario with 10 replicates. Mutation and recombination rates (respectively μ and r) are set to 1.25 × 10−8 per generation per bp. Therefore ρθ=rμ=1. The simulated demographic history is represented in black. a) Demographic history estimated by eSMC (red). b) Demographic history estimated by MSMC (purple). c) Demographic history estimated by MSMC2 (blue). d) Demographic history estimated by PSMC’ (orange).
Fig. 2. Estimated demographic history with seed banking.
Estimated demographic history with seed banking.
Estimated demographic history using four simulated sequences of 10 Mb and ten replicates under a saw-tooth demographic scenario (black). The mutation and recombination rates are set to 1.25 × 10−8 per generation per bp. Therefore rμ=1. We simulate under four different germination rates β = 1 (red), 0.5 (blue), 0.2 (green) and 0.1 (purple), hence we respectively have ρθ=1, 0.5, 0.2 and 0.1. The demographic history is estimated using a) eSMC, b) MSMC, c) MSMC2 and d) PSMC’. β* represents the estimated germination rate by eSMC.
Fig. 3. Estimated demographic history with selfing.
Estimated demographic history with selfing.
Estimated demographic history using four simulated sequences of 10 Mb and ten replicates under a saw-tooth demographic scenario (black). The mutation and recombination rates are set to 1.25 × 10−8 per generation per bp, and simulations were run for four different self-fertilization rates (σ = 0 (red), 0.5 (blue), 0.8 (green) and 0.9 (purple)), and as rμ=1, this gives ρθ=1, 0.6667, 0.333 and 0.182 respectively. The demographic history is estimated using a) eSMC, b) MSMC, c) MSMC2 and d) PSMC’. σ* represents the self-fertilization rate estimated by eSMC.
Fig. 4. Estimated demographic history with selfing and seed banking.
Estimated demographic history with selfing and seed banking.
Demographic history estimated by eSMC for ten replicates using four simulated sequences of 10 Mb under a saw-tooth demographic scenario and four different combinations of germination (β) and self-fertilization (σ) rates but resulting in the same ρθ. Mutation and recombination rates are set to 1.25 × 10−8 per generation per bp, giving rμ=1. The four combinations are: a) σ = 0.4 and β = 0.25, b) σ = 0.75 and β = 0.6, c) σ = 0.85 and β = 1 and d) σ = 0 and β = 0.15. Hence, for each scenario ρθ=0.15. For each combination of β and σ, eSMC was launched with five different prior settings: ignoring seed-banks and self-fertilization (red), accounting for seed-banks and self-fertilization but without setting priors (blue), accounting for seed-banks and self-fertilization with a prior set only for the self-fertilization rate (green), only for the germination rate (orange) or for both (purple). σ* and β* respectively represent the estimated self-fertilization and germination rate.
Fig. 5. Estimated demographic history of Arabidopsis thalinana.
Estimated demographic history of <i>Arabidopsis thalinana</i>.
Demographic history of two European (Sweden (S, blue) and German (G, green)) populations of A. thaliana estimated using eSMC: a) accounting only for selfing (σ is a variable and β = 1) and b) accounting simultaneously for selfing and seed-banking (σ bounded between 0.5 and 0.99 and β bounded between 0.5 and 1). Mutation rate is set to 7 × 10−9 per generation per bp and recombination respectively set for chromosome 1 to 5 to 3.4 × 10−8, 3.6 × 10−8, 3.5 × 10−8, 3.8 × 10−8, 3.6 × 10−8) per generation per bp. σ* and β* respectively represent the estimated self-fertilization and germination rates.
Fig. 6. Estimated demographic history of Daphnia pulex.
Estimated demographic history of <i>Daphnia pulex</i>.
Demographic history estimated by eSMC on six individuals of D. pulex accounting for egg-banks (β is a variable and σ = 0). Different assumptions concerning the number of parthenogenetic cycles before the production of the dormant egg are made: Five cycles (pink), two cycles (red) and no parthenogenesis (dark red). A subset of demographic history estimated by PSMC’ are plotted in orange. Mutation and recombination rates are respectively set to 4.33 × 10−9 and 8×10−8np per generation per bp, where np is the number of reproductive cycles per year, parthenogenetic and sexual.
Tab. 1. Calculation times of eSMC on simulated data under the “saw-tooth” demographic scenario with mutation and recombination rate set to 1.25 × 10−8 per generation per bp.
Calculation times of eSMC on simulated data under the “saw-tooth” demographic scenario with mutation and recombination rate set to 1.25 × 10<sup>−8</sup> per generation per bp.
Results are in minutes given the sequence length and the number of haplotypes.

There are several errors in the Simulation results subsection of the Results as listed below.

In the Convergence property in the absence of seed-banks and self-fertilization subheading, there are errors in the first sentence of the fourth paragraph. The correct sentence is: We now assume ρθ=rμ=5, with the mutation and recombination rate respectively set to 1.25 × 10−8 and 6.25 × 10−8 per generation per nucleotide.

In the Convergence property with dormancy (seed- or egg-banks) subheading of the Simulation results subsection of the Results, there is an error in the first sentence of the first paragraph. The correct sentence is: Using eSMC on sequences simulated under the “saw-tooth” scenario in the presence of seed-banks (mutation and recombination rates are set to 1.25 × 10−8 per generation per bp, (Fig 2), we obtain an accurate estimation of the demography (χt) and of the germination rates (β). There is also an error in the last sentence of the first paragraph. The correct sentence is: Therefore when the molecular mutation and recombination are set to 2.5 × 10−9 per generation per bp, better fits are obtained (S12 Fig).

In the Convergence property with dormancy (seed- or egg-banks) subheading, there are several errors in the second paragraph. The correct paragraph is: For simpler demographic scenarios (constant population size, bottleneck, expansion and decrease, see S13 Fig) and μ = r = 1.25 × 10−8 per generation per bp, the germination rate and the demographic histories estimated by eSMC are accurate for most of the demographic scenarios considered, except in the case of a bottleneck scenario (as expected from previous results). In presence of strong seed-banks (β = 0.2 or 0.1) there are biases in estimations of the far past. Once again, this tendency disappears when the molecular mutation and recombination rates per site are lowered so as not to violate the infinite site model (μ and r = 2.5 × 10−9 per generation per bp, see S14 Fig).

In the Convergence property with self-fertilization subheading, there is an error in the first sentence of the first paragraph. The correct sentence is: Under the “saw-tooth” scenario with different rates of self-fertilization σ, with mutation and recombination rates set to 1.25 × 10−8 per generation per bp (rμ=1), for four different self-fertilization rates σ = 0 (no self-fertilization), 0.5 (50% selfing), 0.8 (80% selfing) and 0.9 (90% selfing), we estimate the self-fertilization rate respectively at 0.19, 0.5, 0.77 and 0.87 (Fig 3). There are also errors in the fifth sentence of the first paragraph. The correct sentence is: When the mutation rate is set to 1.25 × 10−8 per generation per bp and the recombination rate to 6.25 × 10−8 per generation per nucleotide (rμ=5), the self-fertilization rate is overestimated for small values of σ (S15 Fig), but well estimated for higher values of σ.

In the Convergence property with both dormancy and self-fertilization subheading, there is an error in the first sentence of the first paragraph. The correct sentence is: Here we test different combinations of seed/egg-banks and self-fertilization rates that result in the same ratio ρθ=0.15, with rμ=1 (setting μ = r = 1.25 × 10−8 per generation per bp). There is also an error in the eleventh sentence of the first paragraph. The correct sentence is: We also test how recombination can influence the output of these models, notably by taking a higher recombination rate (8.335 × 10−8 per site per generation), more representative of the high recombination to mutation ratio observed in some species (notably D. pulex and A. thaliana [4, 45]).

There is a minor error in S2 Appendix. The command lines for S8, 10, and 11 Fig are incorrect. Please view the correct S2 Appendix below.

Supporting information

S2 Appendix [pdf]
Command lines.

S1 Fig [red]
Estimated demographic history in absence of selfing or seed banking using sequences of 10 Mb.

S2 Fig [red]
Estimated demographic history in absence of selfing or seed banking using sequences of 10 Mb when all method have same discretization of the population size as eSMC).

S3 Fig [red]
Estimated demographic history in absence of selfing or seed banking using sequences of 1 Mb.

S4 Fig [tif]
Estimated demographic history using eSMC in four simple demographic scenarios.

S5 Fig [tif]
Estimated demographic history using PSMC’ in four simple demographic scenarios.

S6 Fig [tif]
Estimated demographic history using MSMC in four simple demographic scenarios.

S7 Fig [tif]
Estimated demographic history using MSMC2 in four simple demographic scenarios.

S8 Fig [red]
Estimated demographic history under .

S9 Fig [red]
Estimated demographic history under .

S10 Fig [red]
Estimated demographic history under with initial value .

S11 Fig [red]
Estimated demographic history under with initial value .

S12 Fig [black]
Estimated demographic history with seed banking and μ = 2.5 × 10.

S13 Fig [red]
Estimated demographic history in four simple demographic scenarios with seed banking.

S14 Fig [red]
Estimated demographic history in four simple demographic scenarios with seed banking where = 2.5 × 10.

S15 Fig [black]
Estimated demographic history with selfing under .

S16 Fig [red]
Estimated demographic history in four simple demographic scenarios with selfing.

S17 Fig [b]
Possible selfing and seed banking value where .

S18 Fig [b]
Estimated demographic history with selfing and seed banking where .

S19 Fig [b]
Possible selfing and seed banking value where .

S20 Fig [blue]
Estimated demographic history of where selfing and seed banking is ignored.


Zdroje

1. Sellinger TPP, Abu Awad D, Moest M, Tellier A (2020) Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genet 16(4): e1008698. doi: 10.1371/journal.pgen.1008698 32251472


Článek vyšel v časopise

PLOS Genetics


2021 Číslo 4
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Důležitost adherence při depresivním onemocnění
nový kurz
Autoři: MUDr. Eliška Bartečková, Ph.D.

Koncepce osteologické péče pro gynekology a praktické lékaře
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková, Ph.D.

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Multidisciplinární zkušenosti u pacientů s diabetem
Autoři: Prof. MUDr. Martin Haluzík, DrSc., prof. MUDr. Vojtěch Melenovský, CSc., prof. MUDr. Vladimír Tesař, DrSc.

Všechny kurzy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#