DOI: 10.5061/dryad.1jwstqk11
title: Data from: Genetic signatures of lineage fusion closely resemble population decline

description: Accurate interpretation of the genetic signatures of past demographic
 events is crucial for reconstructing evolutionary history. Lineage fusion
 (complete merging, resulting in a single panmictic population) is a
 special case of secondary contact that is seldom considered. Here, the
 circumstances under which lineage fusion can be distinguished from
 population size constancy, growth, bottleneck, and decline were
 investigated. Multi-locus haplotype data were simulated under models of
 lineage fusion with different divergence versus sampling lag times (D:L
 ratios). These pseudo-observed datasets also differed in their allocation
 of a fixed amount of sequencing resources (number of sampled alleles,
 haplotype length, number of loci). Distinguishability of lineage fusion
 versus each of 10 untrue non-fusion scenarios was quantified based on six
 summary statistics (neutrality tests). Some datasets were also analyzed
 using extended Bayesian skyline plots. Results showed that signatures of
 lineage fusion very closely resemble those of decline—high
 distinguishability was generally limited to the most favorable scenario
 (D:L = 9), using the most sensitive summary statistics (FS and ZnS),
 coupled with the optimal sequencing resource allocation (maximizing number
 of loci). Also, extended Bayesian skyline plots often erroneously inferred
 population decline. Awareness of the potential for lineage fusion to carry
 the hallmarks of population decline is critical.
description: All pseudo-observed datasets (PODs) were simulated in DIY-ABC
 v2.1.0 (Cornuet et al., 2014) using the HKY model of nucleotide sequence
 evolution (Hasegawa et al., 1985) with proportion of invariant sites = 10%
 and gamma = 2.0, and a mutation rate (<em>µ</em>) of
 1×10<sup>-7</sup> substitutions per site per generation.
 Summary statistic distributions were estimated via 1,000 simulations using
 the “Coalescent Simulations (n-loci | 1-pop)” feature in DnaSP V6.12.03
 (Rozas et al., 2017). Simulations were seeded using values for θ per gene
 (Watterson, 1975), number of sampled individuals, DNA sequence haplotype
 length, and number of diploid autosomal loci from the associated POD. A
 subset of PODs were analyzed using Extended Bayesian Skyline Plots (EBSPs;
 Heled & Drummond, 2008), implemented in BEAST V2.7.3 (Bouckaert et
 al., 2014), using the true model nucleotide sequence evolution and
 mutation rate that generated the PODs, clock model = strict, operator
 weights = auto-optimized, with other priors as default. Searches were
 conducted using 2.5×10<sup>8</sup> Markov Chain Monte Carlo
 generations, sampling parameters every 5,000<sup>th</sup>
 step, discarding 10% as burn-in.
description: # Genetic signatures of lineage fusion closely resemble population decline
 All pseudo-observed datasets (PODs) were simulated in DIY-ABC v2.1.0
 (Cornuet et al., 2014) using the HKY model of nucleotide sequence
 evolution (Hasegawa et al., 1985) with proportion of invariant sites = 10%
 and gamma = 2.0, and a mutation rate () of 110-7 substitutions per site
 per generation. Summary statistic distributions were estimated via 1,000
 simulations using the Coalescent Simulations (n-loci | 1-pop) feature in
 DnaSP V6.12.03 (Rozas et al., 2017). Simulations were seeded using values
 for per gene (Watterson, 1975), number of sampled individuals, DNA
 sequence haplotype length, and number of diploid autosomal loci from the
 associated POD. A subset of PODs were analyzed using Extended Bayesian
 Skyline Plots (EBSPs; Heled & Drummond, 2008), implemented in BEAST
 V2.7.3 (Bouckaert et al., 2014), using the true model nucleotide sequence
 evolution and mutation rate that generated the PODs, clock model = strict,
 operator weights = auto-optimized, with other priors as default. Searches
 were conducted using 2.5108 Markov Chain Monte Carlo generations, sampling
 parameters every 5,000th step, discarding 10% as burn-in. ## Description
 of the data and file structure Folder: Simulated_PODs.zip Simulated
 pseudo-observed datasets (PODs) composed of aligned multi-locus DNA
 haplotypes, generated using DIY-ABC v2.1.0 (Cornuet et al., 2014). PODs
 were simulated under four alternative lineage fusion scenarios that
 differed in their pre-fusion divergence time vs. post-fusion sampling lag
 time (D:L ratios = 1, 3, 5 or 9), each represented by a different folder.
 See that main for full details on simulation parameter settings.
 Hierarchically nested subfolders then partition PODs according number of
 sampled alleles (n#), followed by haplotype alignment length in base pairs
 (#bp) and number of independent diploid autosomal loci (#loc). PODs are
 provided in .alleles format, which are compatible with DnaSP V6.12.03
 (Rozas et al., 2017). Note that there are five replicate PODs for datasets
 containing 40 sampled alleles (n40) coupled with 50 loci (50loc), as this
 expanded set was used for demographic hypothesis testing (e.g., Extended
 Bayesian Skyline Plot [EBSP] analyses; Heled & Drummond, 2008). In
 these cases, file names also include a suffix indicating replicate number
 (001, 002... 005.alleles). References: Cornuet J-M, Pudlo P, Veyssier J,
 Dehne-Garcia A, Gautier M, Leblois R, Marin J-M, Estoup A (2014) DIYABC
 v2.0: A software to make approximate Bayesian computation inferences about
 population history using single nucleotide polymorphism, DNA sequence and
 microsatellite data. Bioinformatics, 30, 11871189. Heled, J., &
 Drummond, A. J. (2008). Bayesian inference of population size history from
 multiple loci. BMC Evolutionary Biology, 8, 289. Rozas, J., Ferrer-Mata,
 A., Sanchez-DelBarrio, J. C., Guirao-Rico, S., Librado, P., Ramos-Onsins,
 S. E., & Sanchez-Gracia, A. (2017). DnaSP 6: DNA sequence polymorphism
 analysis of large data sets. Molecular Biology and Evolution, 34,
 32993302. Excel spreadsheet: Summary_statistic_CIs Spreadsheet with all
 estimated summary statistic 90% confidence intervals (CIs).
 Pseudo-observed datasets (PODs) were simulated under four alternative
 lineage fusion scenarios that differed in their pre-fusion divergence time
 vs. post-fusion sampling lag time (D:L ratios). Data associated with each
 these are contained within a separate worksheet: DL1, DL3, DL5 and DL9.
 Within a worksheet, each POD and demographic scenario are labeled with the
 following elements: DL ratio (DL#), number of sampled alleles (n#),
 haplotype alignment length in base pairs (#bp), number of independent
 diploid autosomal loci (#loc), and demographic scenario under which
 summary statistic distributions were estimated via the Coalescent
 Simulations (n-loci | 1-pop) feature in DnaSP V6.12.03 (Rozas et al.,
 2017), seeded using basic characteristics of a given POD. These scenarios
 are abbreviated as follows: size constancy (Const), growth (Grow, with
 suffix 2, 3 or 4 indicating intensity of 2, 3, or 4 of the base Ne),
 bottleneck (Bott, with suffix 2, 3 or 4 indicating intensity of 0.5, 0.33,
 or 0.25 base Ne), decline (Decn, with suffix 2, 3 or 4 indicating
 intensity of 0.5, 0.33, or 0.25 base Ne), or lineage fusion (Fuse, the
 "true" scenario). Within a worksheet, the estimated 90% CI for
 each of six summary statistics (see Table S1 associated with the main text
 for explanation of notation) is reported as the lower 5% and upper 95%
 bound. The proportion (Prop.) of the lineage fusion (Fuse) scenario's
 90% CI that is unique (Unq), compared to a given non-fusion
 scenario's 90% CI, was calculated in two steps: first at the lower
 tail (Lower Unq), and then at the upper tail (Upper Unq). Two these two
 proportions were then summed to generate the total (Tot) proportion of the
 lineage fusion scenario's 90% CI that is unique. References: Rozas,
 J., Ferrer-Mata, A., Sanchez-DelBarrio, J. C., Guirao-Rico, S., Librado,
 P., Ramos-Onsins, S. E., & Sanchez-Gracia, A. (2017). DnaSP 6: DNA
 sequence polymorphism analysis of large data sets. Molecular Biology and
 Evolution, 34, 32993302. Folder: EBSP_analyses.zip This folder contains
 files used to run Extended Bayesian Skyline Plot (EBSP) analyses (Heled
 & Drummond, 2008). Pseudo-observed datasets (PODs) were simulated
 under four alternative lineage fusion scenarios that differed in their
 pre-fusion divergence time vs. post-fusion sampling lag time (D:L ratios =
 1, 3, 5 or 9). All PODs analyzed via EBSPs were composed of 40 sampled
 alleles (n40), 400 base pair haplotype alignments (400bp), and 50
 independent diploid autosomal loci (50loc). Subfolder names (e.g.,
 "DL1_n40_400bp_50loc") reflect these genetic dataset
 characteristics. Five replicate PODs per D:L scenario were simulated, and
 .xml files for each (suffix 001, 002... 005.xml) were prepared using
 BEAUTI, and then run with BEAST V2.7.3 (Bouckaert et al., 2014). See that
 main text for details on EBSP run settings and interpretation of output.
 References: Bouckaert, R., Heled, J., Khnert, D., Vaughan, T., Wu, C. -H.,
 Xie, D., Drummond, A. J. (2014). BEAST 2: a software platform for Bayesian
 evolutionary analysis. PLoS Computational Biology, 10, e1003537. Heled,
 J., & Drummond, A. J. (2008). Bayesian inference of population size
 history from multiple loci. BMC Evolutionary Biology, 8, 289. ##
 Sharing/Access information Data was derived from the following sources:
 DNA sequences were simulated using the software DIY-ABC v2.1.0 (Cornuet et
 al., 2014).