Supplemental Document 1 – Gene Data Collection, Sequence Alignment &
Phylogenetic Analyses
Methods of DNA extraction followed Starrett & Hedin (2007). PCR
amplification conditions for the CO1 and 28S gene regions followed Starrett &
Hedin (2007), although we also used the 28S primers ZX1 and ZR2 to amplify 28S
for some specimens (see Bond & Hedin 2006).
EF1G PCR reactions were conducted in two rounds using primers and
reaction conditions from Ayoub et al. (2007). For the first round, primers
EF1gF78 and EF1gR1258 were used. One microliter of this PCR product was used
in a nested PCR using primers EF1gF218 and EF1gR1090. An anonymous nuclear
gene was discovered as a PCR amplicon using primers designed to amplify
mygalmorph spidroin proteins, but this amplicon has no similarity to spidroin
sequences (Starrett and Hayashi, unpublished). Internal primers were redesigned
(AtUk-F CAGGATTTCTTGGGAATGTGAGC, AtUk-R
GCTGCCCTATGTAGGCGTCC) and the gene region was amplified in 25 uL
reactions that consisted of 1 μL genomic DNA, 0.1 mM each primer, 0.5 mM each
dNTP (Fisher), 67 mM Tris, 3 mM MgCl2, and 16.6 mM (NH4)2SO4. The reaction
was carried out for 40 cycles of 94° C for 30 seconds, 59° C for 40 seconds, and
72° C for one minute.
PCR products were purified using either PEG or with Montage PCR filter
units (Millipore), and sequenced in both directions at the SDSU Microchemical
Core Facility or at the UCR IIGB Genomics Core Instrument Facility. Sequencher
4.5 (Gene Codes) was used to edit and assemble sequence contigs. The lengthvariable 28S data were aligned manually in MacClade 4.0 (Maddison &
Maddison 2003). We compared this to an algorithmic alignment, where we used
the Geneious Pro 4.5 MUSCLE plug-in (Drummond et al. 2011) to re-align
multiple length-variable regions, using the “refine existing alignment” tool
starting from an initial manual alignment.
Phylogenetic analyses were conducted on individual data partitions in order
to explicitly assess genealogical congruence across loci with regards to
geographic groupings. Identical sequences from the same sampling location
were merged prior to phylogenetic analysis; exceptions included 28S sequences
not merged because of ambiguous sites or length differences (due to amplicon
size differences) but that were otherwise identical. Sequence evolution models
were chosen using jModelTest 0.1.1 (Posada 2008); model likelihoods were
calculated under three substitution schemes (JC, HKY, GTR) on a fixed BIONJ
tree, allowing for unequal base frequencies and among-site rate variation. From
these likelihood scores model selection was based on the Akaike Information
Criterion (AIC).
Bayesian analyses were conducted using MrBayes v3.1 (Huelsenbeck &
Ronquist 2001; Ronquist & Huelsenbeck 2003). The CO1 data were analyzed
using a partitioned strategy (see Ronquist & Huelsenbeck 2003; Nylander et al.
2004; Brandley et al. 2005), where a separate model was applied to each CO1
codon position. Because of few variable first and second position sites, individual
nuclear datasets were not partitioned. For partitioned CO1 analyses, estimated
parameters (revmat, statefreq, gamma shape, pinvar) for each partition were
“unlinked”. Default cold and heated chain parameters were used in all Bayesian
analyses. Two independent searches were run for multiple millions of
generations, and we considered the sampling of the posterior distribution to be
adequate when the average standard deviation of split frequencies dropped
below 0.01 (Ronquist et al. 2005). The first 20-40% of tree topologies were
discarded as burn-in, and from this post burn-in tree set we generated a majority
rule consensus tree with mean branch-length estimates.
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