DOI: 10.5061/dryad.2547d7wsz
title: Joining forces in Ochnaceae phylogenomics: A tale of two targeted sequencing probe kits

description: Premise: Both universal and family-specific targeted sequencing probe kits
 are becoming widely used for the reconstruction of phylogenetic
 relationships in angiosperms. Within the pantropical Ochnaceae, we show
 that with careful data filtering, universal kits are equally as capable in
 resolving intergeneric relationships as custom probe kits. Furthermore, we
 show the strength in combining data from both kits to mitigate bias and
 provide a more robust result to resolve evolutionary relationships.
 Methods: We sampled 23 Ochnaceae genera and used targeted sequencing with
 two probe kits, the universal Angiosperms353 kit, and a family-specific
 kit. We used maximum likelihood inference with a concatenated matrix of
 loci and multispecies-coalescence approaches to infer relationships in the
 family. We explored phylogenetic informativeness and the impact of missing
 data on resolution and tree support. Results: For the Angiosperms353 data
 set, the concatenation approach provided results more congruent with those
 of the Ochnaceae-specific data set. Filtering missing data was most
 impactful on the Angiosperms353 data set, with a relaxed threshold being
 the optimum scenario. The Ochnaceae-specific data set resolved consistent
 topologies using both inference methods, and no major improvements were
 obtained after data filtering. The merging of data obtained with the two
 kits resulted in a well-supported phylogenetic tree. Conclusions: The
 Angiosperms353 data set improved upon data filtering, and missing data
 played an important role in phylogenetic reconstruction. The
 Angiosperms353 data set resolved the phylogenetic backbone of Ochnaceae as
 equally well as the family-specific data set. All analyses indicated that
 both Sauvagesia L. and Campylospermum Tiegh. as currently circumscribed
 are polyphyletic and require revised delimitation.
description: <strong>Contig assembly and multiple sequence alignment:
 </strong>The following bioinformatic methods were conducted for both
 data sets. FastQC v. 0.11.7 (Andrews, 2010) was used to assess the quality
 of Illumina raw reads from the bait-enriched samples. The raw sequencing
 reads were then trimmed with  Trimmomatic  v.0.36 (Bolger et al., 2014)
 using the settings LEADING:20 TRAILING:20 SLIDINGWINDOW:4:20 MINLEN:36 to
 remove adapter sequences and portions of low quality. The HybPiper
 pipeline v.3 (Johnson et al., 2016) was used with default settings to
 process the quality-checked reads and recover the coding sequences for
 each locus.  Outgroup sequences from the OneKP project (Wickett et al.,
 2014) were added to each data set. Paired reads of samples enriched with
 the Angiosperms353 baits and the Ochnaceae baits were mapped to targets
 using BLASTx option (Altschul et al., 1990) and their respective amino
 acid target file. The sequences obtained from the BLASTx option were used
 for subsequent analysis because it was found to recover longer sequences.
 Mapped reads were then assembled into contigs with  SPAdes  v3.13.1
 (Bankevich et al., 2012), and the retrieve_sequences.py script from the
 HybPiper suite was used with the .aa flag to produce outputs of a single
 sequence per gene, which is selected using length, similarity, and
 coverage. HybPiper flags potential paralogs when multiple contigs are
 discovered mapping well to a single reference sequence. All loci flagged
 as potential paralogs were removed from downstream analyses. Subsequent
 analyses were performed using exon-only data. Sequence recovery for both
 data sets is listed in Appendix S2. The percentage of gene recovery was
 calculated using the sum of the captured length per genes per individual
 divided by the sum of the mean length of all loci. MAFFT v. 7.305b (Katoh
 et al., 2002) was used to align individual genes using the –auto flag.
 AMAS (Borowiec, 2016) was used to produce summary statistics for each
 alignment, evaluating the amount of missing data and the number of
 parsimony informative sites (Appendices S3 and S4).
 <strong>Phylogenetic inference: </strong>Both
 assembled data sets were individually analyzed using the following
 approaches. An additional data set was generated by combining the genes
 from both probe kits. The two target files were tested for gene overlap
 using BLASTx. Duplicate genes (7 genes) were removed, and all other
 recovered genes from both data sets were combined resulting in 620
 individual loci. Where two species were available for a genus, the species
 with higher gene recovery from its respective probe kit was selected to
 represent the genus.
 <strong><em>Multispecies-coalescent (MSC)
 approach—</em></strong>The aligned exons were then used to
 infer individual maximum likelihood gene trees with IQTREE v.2.0 (Nguyen
 et al., 2015) with 1000 ultrafast bootstraps using the -bb option. Species
 trees were then inferred from the gene trees using ASTRAL-III v5.5.11
 (Zhang et al., 2018) with the -t 2 option providing full annotation
 outputs, including quartet support to allow visualization of the main
 topology, and first and second alternative as pie charts on the
 phylogenetic tree reconstruction.
 <strong><em>Concatenation
 approach—</em></strong>An additional analysis was performed by
 concatenating exon alignments using AMAS for all loci. A species tree was
 generated from the concatenated exon alignments using IQTREE v.2.0, and
 then two measures of genealogical concordance were also calculated for
 each data set; gene concordance factor (gCF) and site concordance factor
 (sCF) using the options -gcf and -scf in IQTREE v.2.0 (Nguyen et al.,
 2015). The gCF and sCF values represent the percentage of gene trees
 containing that branch, and the number of alignment sites supporting that
 branch, respectively.
description: Hybpiper plus all dependancies (see https://github.com/mossmatters/HybPiper for installation details) Trimmomatic-0.39 MAFFT ASTRAL2.0 IQTREE-2.1.1