44 
PROCEEDINGS OF THE CALIFORNIA ACADEMY OF SCIENCES 
Series 4, Volume 65, 28 Sept. 2018, No. 2 
2013) to serve as outgroups, for a total of 34 accessions herein studied. DNA was extracted from 
field-dried materials using a CTAB protocol (Doyle and Doyle 1987). ddRAD libraries were pre¬ 
pared in-house using a custom protocol (Tripp et al. 2017) that was originally adapted from Parch- 
man et al. 2012. Details are available in Tripp et al. (2017), and noted briefly here. Extracted DNA 
was first subjected to double digestion using EcoRl and Msel. Illumina sequencing oligos that 
included custom designed, variable length barcodes affixed to the EcoRl cutsite were ligated onto 
digested fragments. Ten cycles of PCR were conducted to amplify restriction products, and this 
reaction was repeated once to ameliorate stochastic differences in PCR amplification. Agarose gels 
were used to assess DNA concentrations and sizes throughout the library prep protocol. Products 
of the two PCR reactions were pooled and then submitted to the University of Colorado’s Biofron¬ 
tiers Next-Gen Sequencing Facility for quality control and size selection. Fragments that ranged 
between 200 and 500 bp in length were size selected using BluePippin. Libraries from these 
34 samples were pooled with libraries prepared by others and for other projects, and the final 
pooled libraries containing 96 multiplexed samples were submitted for 1x75 sequencing on an Illu¬ 
mina NextSeq v2 High Output Sequencer at Biofrontiers. All wet lab work was conducted in 
E. Tripp’s molecular lab at the University of Colorado-Boulder. 
Bioinformatics and Phylogenomic Analyses. — Raw data were downloaded and QC was 
assessed using FastQC (Andrews 2017), both before and after the trimming and discarding of over¬ 
represented sequences. Illumina adapters were removed from reads using cutadapt v. 1.4.2 (Martin 
2011), implementing “-m 35” as the minimum required sequence length (35 bp) to retain a read. 
Reads were then demultiplexed using fastq-multx v.1.03, which is distributed as part of the ea-utils 
package (Aronesty 2011). We used the R function ggscatter() to visualize whether age of herbari¬ 
um specimens impacted resulting numbers of raw reads, with the following argument: method = 
“pearson.” Trimming of low quality bases, filtering, and de novo locus assembly steps were con¬ 
ducted using PyRAD v.3.0.66 (Eaton 2014). The following parameters were implemented: 
minimum coverage for retaining a cluster (Mindepth) = 5; maximum number of sites in a given 
locus with phread qualities < 20 (NQual) = 6; within-sample [step 3] and across-sample [step 6] 
clustering threshold (Wclust) = 0.85; and minimum number of samples required to retain a locus 
(MinCov) = 4. Additionally, Paralogous loci were excluded from further consideration by remov¬ 
ing loci that contained more than two alleles with a given sample. A total of three samples was 
removed from the dataset and not considered further for analysis because of too few loci, resulting 
in a final taxon set consisting of 27 accessions of Louteridium plus four outgroups (Table 1). The 
resulting output phylip file was used in maximum likelihood (ML) phylogenetic inference imple¬ 
mented in RaxML v.8.2.9 (Stamatakis 2014). We used a GTR + G model of sequence evolution and 
conducted 100 rapid bootstrap replicates to assess branch support. A 50% majority rule consensus 
tree was calculated for each bootstrap tree, and branch support was summarized on the resultant 
most likely tree derived from the ML search. We considered branches to be supported if bootstrap 
values were > 70%, with values nearer 70% taken to reflect low or weak support. Petalidium was 
used to root the final ML tree. All bioinformatic and phylogenomic work was conducted using the 
University of Colorado’s SUMMIT supercomputer. The final RADseq phylogenomic dataset is 
available in GenBank under the Sequence Read Archive Study #SRP 159283. 
PHYLOGENY 
Intergeneric Relationships. — Louteridium has traditionally been treated as a unigeneric 
tribe, Louterideae, of either Acanthoideae (e.g., Lindau 1895) or Ruellioideae (e.g., Bremekamp 
1965). Molecular phylogenetic data for nearly all currently recognized genera of Ruellieae (Tripp 
