DOI: 10.5061/dryad.nzs7h4518
title: A comparison of phylogenomic inference pipelines for low-coverage whole-genome sequencing in Formica ants

description: A rapid proliferation in the availability of whole genome sequences (WGS),
 often with relatively low read depth, offers an unprecedented opportunity
 for phylogenomic advances using publicly available data, but there are
 several key challenges in applying these data. Using low-coverage WGS data
 for Formica ants, we conducted detailed comparisons on two different
 analytical pipelines (reference-based vs. de novo genome assembly), four
 types of datasets (5kbp-window, ultra-conserved element [UCE], single-copy
 ortholog [BUSCO] and mitogenome), and a series of analytical procedures
 (e.g., concatenation vs. coalescent analyses) to identify which are robust
 to typical WGS data. The results show that at shallow scale of
 phylogenetic relationships of closely related species 5kbp-windows from
 the reference-based pipeline and UCEs from the de novo assemblies are more
 advantageous than the BUSCOs in recovering informative markers for
 phylogenetic inference. Compared to concatenation analyses, coalescent
 analyses often resulted in disparate deeper relationships in the
 phylogeny. This study uncovers obvious mito-nuclear discordance, and
 demonstrates genome-wide gene conflicts in phylogenetic signals, both
 pointing to possible incomplete lineage sorting and/or hybridization
 during the early, rapid radiation of Formica ants. Divergence dating
 analyses show that different types of data often resulted in inconsistent
 time estimates, with older ages estimated for deep nodes using the
 mitogenomic and 5kbp-window datasets. A taxon sampling covering the
 diversity of a lineage is essential to accurately estimate its divergence
 time. The strengths and weaknesses of different analytical pipelines and
 strategies are discussed. Findings from this study provide valuable
 insights for large-scale phylogenomic projects using WGS data.
description: # A comparison of phylogenomic inference pipelines for low-coverage
 whole-genome sequencing in Formica ants ## Description of the data and
 file structure * `36Assembled.Genomes.zip`: contains genome assemblies for
 36 Formica taxa (named as "[taxon name].fa]"). *
 `FinalDatasets.rename.zip`: contains all the final concateated matrices
 (named as "[dataset].phy.rename" or
 "[dataset].fas.rename") and its corresponding partition files
 (named as "[dataset].partition"). * `FinalTrees.rename.zip`:
 contains the trees in newick format from all phylogenetic analyses. The ML
 results from the concatenated datasets were named as
 "[dataset].MFM.10ML.[best run number]UFboot.suptree.rename.tre";
 the ASTRAL results from the species tree analyses were named as
 "Astral.[dataset][bootstrap cutoff]_100boots.rename.tre". *
 `Partitioned_likelihood_5kwinodws-12datasets_AMAS_results.zip`: provide
 statistics of 5kbp-windows and ΔGLS from partitioned likelihood analyses
 (named as
 "Partitioned_likelihood_analyses_5kwindow_results.xlsx"), as
 well as the AMAS statistics for 12 different datasets (named as
 "[dataset].AMAS.csv"). *
 `RF_distances-Ave_Bootstrap_6datasets.zip`: provide normalized RF
 distances of the gene trees to the T1 topology (named as
 "[dataset]avg_bootstrap.csv") and the average bootstrap supports
 of gene trees (named as "normalized_rf_distances[dataset].csv")
 for 6 different datasets. * `DatingDivergence.zip`: provide divergence
 dating results from BEAST and MCMCtree analyses on different datasets. The
 BEAST results were named as "MaxCre.Mean.[number of
 runs].BEAST.[dataset].tre"; the MCMCtree results were named as:
 "MCMCtree.[dataset].APL.run1.tre".