Data for: PickMe: sample selection for species tree reconstruction using coalescent weighted quartets

Description

Notes

Methods

We obtained targeted sequence data for 763 putatively single-copy nuclear loci for samples of 59 North American milkweed species, three African outgroup species, \textit{Asclepias physocarpa}, \textit{A. fruticosa}, and \textit{A. fornicata}, and one additional outgroup, \textit{Pergularia daemia} using the target enrichment baits of Weitemier et al. (2014) (Supplemental Material~\protect\ref{app:milkweed}). Data for 32 of these samples and orthologs from the genome sequence of \textit{Asclepias syriaca} \citep{weitemier2019draft} were included in the analyses of \cite{BOUTTE2019106534}, and nuclear sequence data for the additional 30 samples were generated using the DNA sequencing and assembly methods described therein. \cite{BOUTTE2019106534} had excluded the 30 newly analyzed samples based on an ad hoc minimum gene recovery criterion of 600 genes (79\%) with the goal of high gene occupancy for all samples for species tree analyses. For the analyses conducted here, we masked assembled sequences with Ns for very low read depth ($\le 2$ reads) and at heterozygous sites (i.e., intra-individual SNPs). For each gene, we aligned masked sequences using Mafft version 7.245 with default parameters \citep{katoh2013mafft}, and removed sequences with less than 50\% of the total alignment length \citep[i.e. Type II missing data;][]{hosner2016avoiding} to reduce gene tree error following \cite{sayyari2017fragmentary} and \cite{mirarab2019species}.

For further analysis, we selected a subset of 703 genes, which had been identified by \cite{BOUTTE2019106534} as producing the best-resolved milkweed phylogenies based on bootstrap support across the gene trees. For the complete data set of 63 species, we first estimated the 703 gene trees using Neighbor-Joining on uncorrected distances (the proportion of observed differences in the aligned sequences) as implemented in the ape package \citep{paradis2018ape} in R v. 3.5.1 \citep{R}. Using these estimated gene trees, we identified the samples to be included in species tree analyses using \emph{PickMe}. To determine whether the gene tree inference method affected the sample selection results, we also used the GTR+Gamma model in RAxML v. 8.2.12;  \citep{stamatakis2014raxml} to estimate the initial gene trees. For the set of samples identified as reliable by \emph{PickMe}, we realigned the sequences and then removed small alignments ($< 100$ bp) following \cite{BOUTTE2019106534}. We then used IQ-Tree v. 1.5.4 \citep{nguyen2014iqtree,chernomor2016terrace} to select the best model of molecular evolution for the retained alignments and inferred the gene tree for each locus using the same parameters as \cite{BOUTTE2019106534}. Using ASTRAL-II v. 4.10.12 \citep{mirarab2015astral}  with default parameters, we inferred a species tree and calculated local posterior probability support \citep{sayyari2016fast}. We calculated gene concordance factors using the method of \cite{Minh2020new}, implemented in IQ-Tree v. 2.1.2 \citep{nguyen2014iqtree,chernomor2016terrace}. For comparison, we repeated the gene and species tree analyses done for the subset of \textit{PickMe} reliable samples for the full data set using identical methods.