DOI: 10.5061/dryad.ht76hdrmn
title: Dataset from: The origin and fate of fungal mitochondrial horizontal gene transferred sequences in orchids (Orchidaceae)

description: The transfer of DNA among distantly related organisms is relatively common
 in bacteria but less prevalent in eukaryotes. Among fungi and plants, few
 of these events have been reported. Two segments of fungal mitochondrial
 DNA have been discovered in the mitogenome of orchids. Here, we build on
 their work to understand the timing of those transfer events, which
 orchids retain the fungal DNA, and the fate of the foreign DNA during
 orchid evolution. We update the content of the large DNA fragment and
 establish that it was transferred to the most recent common ancestor of a
 highly diverse clade of epidendroid orchids that lived ~28–43 Mya. Also,
 we present hypotheses of the origin of the small transferred fragment. Our
 findings deepen the knowledge of these interesting DNA transfers among
 organelles and we formulate a probable mechanism for these horizontal gene
 transfer events.
description: We sampled 61 taxa from across Orchidaceae of
 which two were taken from available data on GenBank (mitochondrial
 sequences of <em>Erycina pusilla:</em> KJ501971, KJ501972,
 KJ501991, KJ501994, and <em>Gastrodia elata</em>: MF070088 and
 MF070090). The HGT regions of <em>Apostasia shenzhenica</em>
 and <em>Triphora wagneri</em> were taken from Sinn &
 Barrett (2020).  DNA extractions,
 sequencing, and data assembly were performed as in Valencia-D. et al.
 (2021). In short, total DNA was extracted following a modified Doyle and
 Doyle (1987) procedure (Neubig et al., 2014). Sequencing of total DNA
 without enrichment was performed using Illumina HiSeq or NovaSeq
 technologies, generating paired-end read sequences of 100, 150, or 250 bp
 length. The data was processed using Geneious Prime 2020.3 (Kearse et al.,
 2012).   To capture the HGT region,
 the sequences found in other orchids by Sinn and Barrett (2020) we used.
 Geneious mapper and Bowtie2 (Langmead & Salzberg, 2012) were used
 with low sensitive parameters to capture reads that were at least 75%
 similar to the references (Geneious mapper with maximum mismatch per read
 25%, gaps of 5% as a maximum per read and maximum gap size of 5 nt, other
 parameters were left at the default value; Bowtie mapper settings:
 alignment type: local, Lowest Sensitivity/Very Fast). Then, the reads
 captured in the reference assemblies were de novo assembled (mapper:
 Geneious, maximum mismatch per read 5%, gaps of 5% as a maximum per read
 and maximum gap size of 2 nt). To account for possible spurious scaffolds
 (i.e., non-mitochondrial or low-quality), contigs with depth below 5× or
 over 200× were excluded as well as those with pairwise identity below 95%
 and those shorter than 500 nt in length. All contigs were inspected to
 identify possible erroneous assemblies of the reads and to ensure the
 contiguity. The consensus sequences of these contigs were annotated to
 confirm the presence of the FMTs.  Eleven native mitochondrial genes were recovered
 from orchids, i.e., <em>atp6, ccmFC </em>and <em>FN,
 cob, mttB, nad2 </em>and <em>4, rps1, 2, 3</em>, and
 <em>4</em>, including the introns. We sampled fungal mitogenomes from 32 species in
 the subphylum Ustilaginomycotina. The mitogenomes of ten species were
 downloaded from GenBank and additional mitochondrial sequences for
 twenty-two taxa were obtained from the whole-genome shotgun contigs
 repository. Annotations of the sequences were made through the MITOS web
 server (Bernt et al., 2013) and then inspected in Geneious using
 <em>Ustilago maydis</em> (DQ157700) as a reference. 
 Three main datasets were generated with the
 following data: (1) native orchid mitochondrial data (eleven genes), (2)
 small-FMT data from orchids and the putative xenologous tRNAs from fungi,
 and (3) large-FMT data from orchids and the putative xenologues from the
 fungi (and excluding the endonuclease gene). Alignments were performed in
 Geneious Prime. The datasets were analyzed as follows: (1) native orchid mitochondrial data: genes with
 introns were aligned individually with MAFFT (Katoh & Standley,
 2013), and genes without introns were aligned by translation. Then the
 genes were concatenated in one matrix. Phylogenetic trees were made using
 Maximum likelihood and Bayesian Inference methods. (2) small-FMT data: the whole region between the
 tRNA(Thr) to tRNA(Lys) genes was included for the orchid samples. The
 fungal tRNAs were annotated in each genome and extracted. Orchid and
 fungal samples that did not have the three tRNA genes were excluded from
 the analyses. Alignments with and without <em>Dendrobium</em>
 and <em>Triphora</em> were performed with the MAFFT plugin on
 Geneious. Phylogenetic trees were made using Maximum likelihood
 methods.   (3) large-FMT data:
 orchids and fungal sequences were aligned separately and then, the data
 were combined and realigned. Orchid data were aligned using MAFFT. Fungal
 genes were aligned gene by gene with MAFFT (for tRNA genes) or by
 translation (for protein-coding genes). For the combined analyses, fungal
 locus alignments were concatenated in the position and direction in which
 they appear on the large-FMT. Alignments with and without fungal data were
 made, and for the latter, with and without <em>Triphora</em>.
 Phylogenetic trees were made using Maximum likelihood methods. The dataset
 of fungal and orchids data including Triphora was also analyzed using
 Bayesian Inference methods.   The
 adjacent regions to the large-FMT were also inspected. Alignments of
 homologous regions on the 5 prime and the 3 prime flanks are included in
 these files. Maximum Likelihood
 analyses of the datasets were performed with IQTree2 (Nguyen et al., 2015)
 using ModelFinder (Kalyaanamoorthy et al., 2017) to identify the best
 model in each case. Branch supports were calculated using 100
 nonparametric bootstrap replicates.  We evaluated the divergence times for the native
 mitochondrial genes and the large-FMT plus fungal xenologous genes
 matrices using BEAST 2.6.3. (Bouckaert et al., 2019) implemented on CIPRES
 Science Gateway (Miller, Pfeiffer, & Schwartz, 2010). We used the
 substitution rates obtained for each dataset selected as most appropriate
 in ModelFinder according to the Bayesian Information Criterion (Table 4).
 An uncorrelated relaxed clock model was used with a log-normal
 distribution (Drummond et al., 2006). The tree was produced using a
 birth-death model (Gernhard, 2008) under a topology with constrained root
 or ingroup. The native mitochondrial genes analysis was rooted with
 Apostasioideae. For the analysis of the third dataset (large-FMT plus the
 corresponding putative xenologues from the fungi combined),
 <em>Malassezia</em> was designated as the root, following
 Kijpornyongpan et al. (2018).  A
 log-normal distribution was applied to set the priors. For the native
 mt-orchid analysis the calibration date used was the age of the branching
 point of the subfamily Apostasioideae with the rest of the orchids,
 estimated by Givnish et al. (2015) at 83.6 Mya. To account for the
 uncertainty in the estimation the standard deviation (s) was set at 0.07
 to obtain a 95% confidence interval of 74.3–93.6 Mya. We performed four
 replicate BEAST analyses with 10 million MCMC iterations and sampled once
 every 1000 generations. For the third dataset, a calibration point was set
 at the root of all Ustilaginomycotina with a mean of 270 Mya (s=0.05),
 following the estimations of Kijpornyongpan et al. (2018). Three
 replicates were run in BEAST with 200 million generations and sampled
 every 5000 generations. The log files of the MCMC runs were examined using
 Tracer 1.7.1 (Rambaut et al., 2018) and the burn-in trees were removed
 where they reached stationarity in the resultant likelihood of trees
 observed. The log files and the resulting trees from the runs were
 combined using LogCombiner v2.6.3 (Drummond & Rambaut, 2007).
 Maximum clade credibility trees were calculated using TreeAnnotator v2.6.3
 (Drummond & Rambaut, 2007) and visualized in FigTree v1.4.4
 (https://github.com/rambaut/figtree/releases, retrieved on Dec 6,
 2019).