Transcriptome Sequences Resolve Deep Relationships of the Grape Family

Abstract

Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

Full text

Transcriptome Sequences Resolve Deep Relationships of
the Grape Family
Jun Wen1*, Zhiqiang Xiong2, Ze-Long Nie3, Likai Mao2, Yabing Zhu2, Xian-Zhao Kan4, Stefanie M. Ickert-
Bond5, Jean Gerrath6, Elizabeth A. Zimmer1, Xiao-Dong Fang2*
1 Department of Botany, National Museum of Natural History, MRC166, Smithsonian Institution, Washington, D.C., United States of America, 2 BGI-Shenzhen,
Shenzhen, China, 3 Key Laboratory of Biodiversity and Biogeography, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, China,
4 College of Life Sciences, Anhui Normal University, Wuhu, Anhui, China, 5 UA Museum of the North Herbarium and Department of Biology and Wildlife,
University of Alaska Fairbanks, Fairbanks, Alaska, United States of America, 6 Department of Biology, University of Northern Iowa, Cedar Falls, Iowa, United
States of America
Abstract
Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus
impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein
coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417
orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its
phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships,
showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous.
The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.
Citation: Wen J, Xiong Z, Nie Z-L, Mao L, Zhu Y, et al. (2013) Transcriptome Sequences Resolve Deep Relationships of the Grape Family. PLoS ONE
8(9): e74394. doi:10.1371/journal.pone.0074394
Editor: Hector Candela, Universidad Miguel Hernández de Elche, Spain
Received February 2, 2013; Accepted August 1, 2013; Published September 17, 2013
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by
anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: This study was funded by grants from the Office of the Smithsonian Undersecretary of Science, the US National Science Foundation (grant DEB
0743474 to S.R. Manchester and J. Wen, and grant DEB 0743499 to J. Gerrath), the Small Grants Program of the National Museum of Natural History of
the Smithsonian Institution to JW, and trust funds generated by EAZ. The funders had no role in study design, data collection and analysis, decision to
publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: wenj@si.edu (JW); fangxd@genomics.org.cn (XDF)
Introduction
The grape family (Vitaceae) has been widely recognized for
its economic importance as the source of table grapes, wine,
and raisins. The family consists of 14 genera and ~ 900
species [1]. Many species of the family are dominant lianas in
lowland tropical forests, while species in Parthenocissus
Planchon, Ampelopsis Michx. and Vitis L. are primarily from the
temperate zone. Previous phylogenetic analyses support five
major clades within Vitaceae: (i) the Vitis – Ampelocissus–
clade (180 spp.), (ii) the Ampelopsis – Rhoicissus clade (43
spp.), (iii) the Parthenocissus -Yua clade (15 spp.), (iv) the core
Cissus clade (300 spp.), and (v) the Cayratia – Tetrastigma –
Cyphostemma – clade (350 spp.) [2,3]. Parthenocissus and
Yua are supported as closely related to Vitis (3, 4). However, in
spite of several recent efforts [2,3,5,6,7,8] that effectively
resolved the relationships within each of the main clades, the
deep relationships of the family remained poorly resolved.
Recently, it has been demonstrated for a number of plant and
animal lineages that uncertainty of deep relationships among
taxonomic groups hinders progress in understanding their
evolution including their temporal and spatial origins as well as
their morphological changes over time [9,10]. In particular,
biogeographic reconstructions, especially at the family level,
are a major challenge for plant biologists [2,3,11–16], even
though methods have been developed to account for
phylogenetic uncertainty in biogeographic inferences [17–19].
Transcriptome sequences, generated using high throughput
techniques, have been shown to provide a rich set of
characters to produce phylogenies in eukaryotes and are more
efficient and cost-effective than traditional PCR-based and
EST-based methods (20). Recent studies have demonstrated
the utility of transcriptome data for resolving the relationships of
mosquitoes [20], mollusks [9,21], and the large tetrapod group
consisting of turtles, birds and crocodiles [22]. For example,
even though mollusks have an excellent fossil record, deep
relationships of the phyllum have been uncertain when
molecular phylogenies used a few genes. With a transcriptome
approach, the major clades were resolved with highly
significant statistical support. Given its potential, we decided to
take a phylogenomics approach to resolve the deep
relationships of the Vitaceae. This represents the first study in
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plants to use RNA-Seq data to reconstruct phylogenies in
flowering plants. Several previous studies employed RNA-Seq
data to explore the evolution of paleopolyploidy (e.g. [23-25];
also see 26). The 1KP collaborative project has also generated
large-scale gene sequence information for many different
species of plants (http://www.onekp.com/).
Results and Discussion
Backbone relationships of the grape family
Transcriptome (RNA-Seq) data were obtained from 14
species of the grape family and one species of its sister family
Leeaceae (Table S1, Figure S1), and augmented with publicly
available whole genome data of the domesticated grape Vitis
vinifera [27]. Each of the five major lineages of the grape family
[3] was represented in the data. We obtained about twenty
million 90 bp paired-end DNA sequence reads from non-
normalized cDNA libraries for each of the 15 species using an
Illumina HiSeq 2000, assembled the sequence reads de novo
and retained all contigs ≥ 150 bp for further analysis (Table
S2). This strategy identified 417 orthologous genes suitable for
concatenation and phylogenetic inference (Table S3, also see
Figure S2), totaling 770,922 nucleotide and 256,974 amino
acid positions. After filtering out any gene where each taxon
contained no more than 50% of the data as missing, a 229
gene data set resulted, totaling 334,317 nucleotide and
111,439 amino acid positions.
Initial maximum likelihood analysis of the nucleotide
sequences of the 417 gene matrix using PhyML [28] produced
robust support for relationships of the grape family (Figure 1; all
nodes with 100% bootstrap support values). However, to
minimize the impact of missing data, we subsequently
employed the 229 gene data set to explore various
phylogenetic inference methods. Maximum likelihood estimates
(ML [28,29]) and Bayesian inference (BI) with a phylogenetic
mixture model [30] of the 229 gene data set also supported the
topology shown in Figure 1. The maximum parsimony (MP)
analyses [31], however, placed the Cissus clade at the base,
even though the unrooted relationships within Vitaceae were
identical with all three different analytical strategies (Figure 2).
When we examined the data set closely, we noted that Cissus
is the most divergent taxon within Vitaceae. The parsimony
method has been known to be problematic under conditions of
greatly unequal branch lengths, referred to as the long-branch
attraction phenomenon [32]. Our analyses using maximum
likelihood with both PhyML (28) and RAxML [29], and Bayesian
inference [30] all yielded an identical topology of Vitaceae
(Figure 1) that showed all nodes with 100% bootstrap support
and posterior probabilities of 1.00, suggesting that all taxa of
Vitaceae were represented by sufficient data to be reliably
placed.
Thus, using the model-based analytical methods, we
produced a transcriptome phylogeny (Figure 1) that supports
the Ampelopsis – Rhoicissus clade as the basally diverged
clade in Vitaceae. Vitis, Ampelocissus, Pterisanthes, and
Nothocissus form a clade, which is sister to Parthenocissus.
The taxa Cissus, Cayratia, Cyphostemma and Tetrastigma
form a separate clade, with the latter three genera forming a
subclade sister to core Cissus. These four genera possess two
morphological synapomorphies: 4-merous flowers and very
well-developed thick floral discs. This backbone relationship of
Vitaceae is similar to the results of Ren et al. [3] using three
chloroplast markers, but support values were relatively low for
several major clades in that earlier study. It is of interest to
mention that the deep clades, such as the Parthenocissus-
Vitis-Ampelocissus-Nothocissus-Pterisanthus (PVANP) clade,
as well as the clade of PVANP and Cayratia, Tetrastigma,
Cyphostemma and Cissus, lack detectable morphological
synapomorphies. Morphological convergence is the most likely
reason for such a pattern at the deep level. All relationships at
the shallower level are consistent with the results of the
previous analyses of various clades of Vitaceae [4,6-8].
The biogeographic origin of the grape family has never been
explored with analytical methods. With the phylogeny of
Vitaceae unavailable at that time, in their seminal paper, Raven
and Axelrod [33] considered Vitaceae as a relatively ancient
family and proposed that it might have originated in the
Laurasian region and subsequently reached the Southern
Hemisphere subsequently. The first diverged clade, i.e., the
Ampelopsis-Rhoicissus clade, consists of ca. 43 species
disjunctly distributed over six continents (Asia, Europe, North
America, South America, Africa, and Australia), and represents
a rare example in angiosperms with such a widely disjunct
distribution in both the Northern and the Southern Hemisphere.
The Ampelopsis - Rhoicissus clade is composed of two distinct
Laurasian lineages, each disjunct between the Old and the
New World, and one Southern Hemisphere group with a
Gondwana-like intercontinental disjunction: (Africa (Australia,
and South America)). The biogeographic analyses of the 28
species sampled by Nie et al. [34] suggested that the
Ampelopsis – Rhoicissus clade had an early diversification in
the Northern Hemisphere and subsequently migrated into the
Southern Hemisphere and diversified there. Our results also
support the hypothesis that the primarily North Temperate
grape genus Vitis forms a clade with the pantropical
Ampelocissus, and the tropical Asian Pterisanthes and
Nothocissus (Figure 1). This large clade of four genera
consisting of the close relatives of grapes is sister to
Parthenocissus, a North Temperate genus disjunct in eastern
Asia and eastern North America. Even though a biogeographic
analysis of the family is beyond the scope of the current paper,
the establishment of the backbone phylogeny (Figure 1) will
ultimately facilitate our inference of the family at the global
scale and help elucidate the diversification processes involving
both the temperate and tropical floristic elements. In particular,
the placement of the Ampelopsis-Rhoicissus clade as the first
diverged clade, the Northern Hemisphere taxa forming a grade,
and the Southern Hemisphere taxa (e.g., Rhoicissus) nested
within the Northern Hemisphere grade (also see [34]) are
consistent with the Northern Hemisphere origin of the family. A
detailed biogeographic analysis with a broad taxon sampling
scheme will be attempted in the near future.
Given the strong support for the Vitaceae backbone
phylogeny, we further tested its topological stability by
producing new data sets via randomly reducing the gene
number in multiples of 10, starting from the 229 gene tree. To
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automatically obtain bootstrap support scores on the nodes of
large numbers of trees, we used the following strategy. For
each specified gene number N, we obtained a random set of N
genes from the 229 orthologous genes. Then we built an ML
tree based on this set and compared the topology of the tree
with that of the standard tree (Figure 2). If the topologies were
the same, the set and tree were kept, or else they were
discarded, and new sets and trees would be created and
followed by comparison of the new topology to the 229 gene
data set. The process was repeated until a tree with standard
topology was obtained. For each N, the program built 30 trees
based on 30 random sets of N genes. N was set to 10, 20, 30..
220. The average numbers of repeats for each N were
tabulated and plotted (Figure 3). With just 30 genes, all nodes
had bootstrap support (BS) of more than 95% using the
likelihood approach in PhyML; with 40 genes, all nodes had BS
of at least 99% (Figure 2; Table S4). We also examined the
average bootstrap support and the resampled nucleotide
positions in the phylogenetic analyses to show the topological
stability (Figure S3). Our results thus indicate that RNA-Seq
[35], even with non-normalized transcriptomes, offers access to
protein coding sequences very easily and quickly and
represents a data-rich, accurate, and cost-effective source of
orthologous sequences for phylogenetic inference.
Our data sets also showed that only 48 of the 229 gene trees
had exactly the topology found in Figure 1, and in fact, the
gene trees were quite diverse in topology. Nevertheless, the
concatenated gene tree had all clades strongly supported. This
result is reminiscent of the study of Rokas et al. [36], who
demonstrated that concatenation of a sufficient number of
randomly selected genes overwhelms conflicting signals
present in different genes.
Figure 1. Maximum likelihood tree of Vitaceae using nucleotide sequences of 229 genes from the 15 transcriptomes of
Vitaceae. The same topology was recovered from the 417 gene data set. Bootstrap support for all nodes was 100%, and posterior
probabilities in the Bayesian inference for all nodes were 1.00.
doi: 10.1371/journal.pone.0074394.g001
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Utility of transcriptome data for phylogenetic inference
A practical disadvantage of using the transcriptome
approach is that it requires high quality RNA from fresh
material, while silica gel dried plant tissue samples and
herbarium specimens will rarely yield good RNA. In fact,
Hittinger et al. [20] have shown that large phylogenetic data
matrices can be assembled accurately from even short (50 bp
average) transcript sequences, so even non-optimal plant
material, for example, that was preserved in “RNAlater” may
eventually be used for transcriptome data generation. Our data
demonstrate that the transcriptomes can yield resolution for
previously difficult to resolve radiations, especially at the family
level in plants, in the time frame since the mid-Cretaceous
(Figure 4). This may be true, even though these are coding
sequences, since their third positions and the 5’ and 3’
untranslated regions do evolve relatively rapidly [37].
Transcriptome data can effectively lead to identification of truly
single copy transcripts and offer the conserved sequences
necessary to generate primer pairs that can be used to amplify
and sequence rapidly evolving intron regions for studies at and
below the species level, generally without cloning steps [38].
The amplifications may then be standard ones followed by
Sanger sequencing, or may be ones employed in the next-
generation sequencing approaches generally referred to as
targeted sequence capture [39,40]. Nevertheless, as the RNA-
Seq approach is still relatively costly, extensive taxon sampling
is not presently feasible. Our sampling in the grape family
emphasized the backbone relationships and represents an
example of what we can accomplish using transcriptomes and
a first step toward resolving the deep phylogenetic
relationships of Vitaceae.
Transcriptomic phylogenetic analyses do face some
challenges due to the complications associated with
pseudogenes and paralogous comparisons [38,41]. Because
Figure 2. Unrooted tree of 15 species of Vitaceae based on nucleotide sequences of 229 genes. The node numbers
correspond to those in Table S4.
doi: 10.1371/journal.pone.0074394.g002
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many plant lineages may have experienced reticulate evolution
and allopolyploidy [42], it is also challenging to tease apart the
plant diversification history given the hundreds of genes
available. Our grape data set shows that transcriptome data
can be an important source for phylogenetic inference.
However, we may have been highly fortunate that the grape
family was not seriously impacted by reticulate evolution in its
early history (see Figure S4, based on the Ks value distribution
Figure 3. Average bootstrap support and the gene number in the phylogenetic analyses based on data from Table S4.
doi: 10.1371/journal.pone.0074394.g003
Figure 4. Divergence time estimation of Vitaceae clades using the program mcmctree in PAML and 4-fold degenerate
sites. The red dots correspond to calibration points.
doi: 10.1371/journal.pone.0074394.g004
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of paralogs of species across the grape family), which allowed
us to recover the highly robust topology (Figure 1).
With respect to data analyses, species tree approaches [43]
may need to be explored more thoroughly and other
partitioning strategies may be applied [44]. Testing and
selecting genes with strong phylogenetic signals will be an
important next step with our data set (see [45]). New analytical
strategies will be needed to handle these large data sets, and
to deal with realistic assumptions about the complications of
molecular evolution as well as differences in nucleotide
substitution rates. A number of common computer programs
such as MrBayes [46], BEAST [47] and even PhyloBayes [44]
cannot accommodate large data sets like ours with over
300,000 aligned nucleotide positions at present. Clearly, the
systematic biology community needs to invest in the
bioinformatics front more aggressively, as large data sets now
are being generated at a rapid rate. Our study also
demonstrates that the non-parametric parsimony method [31]
may be misleading when handling genomic datasets with
hundreds of thousands of characters when the sequence
evolution is highly unequal across taxa in the study group.
Furthermore, our case study on the grape family is within the
time frame of 100 million years of evolution (Figure 4). If we
move deeper into the time scale of the tree of life, we expect
additional complications concerning homology of gene
sequences. Nevertheless, plant biologists have experienced
enormous difficulties in resolving deep relationships among
taxa in the time frame of the last 100 million years, and our
data demonstrate the power of transcriptome data over this
evolutionary time scale.
Materials and Methods
Ethics Statement
No specific permits were required for the collection of
samples as they were all grown in the greenhouse, which
complied with all relevant regulations. None of the samples
represents endangered or protected species.
RNA extraction and transcriptome sequencing
Total RNA was isolated from finely ground mixed tissue
samples of stems, leaves, tendrils and sometimes flowers of
plants growing in the Botany Department greenhouse of the
Smithsonian Institution. Voucher information for the species
used is given in Table S1. We used the Sigma Spectrum™
Plant Total RNA Kit for the extractions. The transcriptome
library construction and sequencing were performed at BGI and
followed the protocols in Peng et al. [48].
De novo assembly and transcript annotation
After we obtained raw sequencing data, we first filtered out
reads of low quality, including cases of weak signal, large
number of N’ s and PCR duplication. The reads with more than
40 bases of low quality, i.e., 71 or lower Illumina scores or with
more than 20% of N (unknown) bases were all filtered out.
Three software packages, Trinity [49], Velvet-Oases [50] and
SOAPdenovo-Trans (http://soap.genomics.org.cn/
SOAPdenovo-Trans.html) were evaluated for the initial
assembly. The genes from the grape whole genome annotation
were used as calibration to check the performance of the
programs. We also used a gene set of conservative proteins in
eukaryotes to evaluate the assemblies. After comparing the
assemblies to check for completeness, redundancy, and the
coverage of some essential or housekeeping genes in the
grape genome, we selected the software SOAPdenovo-Trans
as our assembler for its overall best performance.
After the de novo assembly of each sample with
SOAPdenovo-Trans, we filtered out highly similar transcripts
that may represent alternatively spliced transcripts. We then
aligned the remaining transcripts to the reference grape
genome in the Swiss-Prot database using BLAST [51] with the
parameters “-e 1e-5 -F F -a 5”. The transcripts that could be
aligned to reference sequences were selected and scanned to
define coding regions (CDS). Length distribution of the coding
regions extracted from the 14 transcriptomes and one
reference genome (Vitis vinifera) of Vitaceae is shown in Figure
S1.
Gene orthologs
Self-to-self BLASTP [51] was conducted for all protein
sequences with an E-value of 1E-5. We assigned a connection
(edge) between two nodes (genes) if the aligned length was
longer than 1/3 for both genes. An H-score that ranged from 0
to 100 was used to weight the edges. For genes G1 and G2, H-
score is defined as Score (G1, G2) *100 / max(Score(G1, G1),
Score(G2, G2)), where Score(A, B) is BLAST raw score of
genes A and B.
To define gene families, we used average distance for a
hierarchical clustering algorithm implemented in Hcluster_sg
(part of TreeFam) [52]. It required the minimum edge weight
(H-score) to be larger than 5 and the minimum edge density
(total number of edges / theoretical number of edges) to be
larger than 1/3. One-to-one single-copy orthologous gene
families were then selected. The length distribution of 417
ortholog gene sequences (data including 6672 sequences, the
total of 417 genes x 16 samples) is shown in Figure S2. The
grape transcriptome sequence data have been deposited in
GenBank (submission ID: Grape Transcriptome; submission
content: Transcriptome analysis of 16 grapes; Submission:
Grape Transcriptome; Created SUBMISSION: ACC =
SRA081731 subid = 14992).
Phylogenetic reconstruction
MUSCLE [53] was used to obtain multi-sequence alignments
for each orthologous gene family. All alignments were
concatenated for phylogenetic analyses using the optimality
criteria of maximum parsimony (MP), maximum likelihood (ML),
and Bayesian inference (BI), as implemented in PAUP 4.0b10
[31], PhyML 7.2.6 [28] and RAxML [29] and BayesPhylogenies
[30], respectively. For the MP analyses, we used heuristic
searches with tree-bisection-reconnection (TBR) branch
swapping, MULTREES option on, and 1000 random additions.
All characters were unordered and equally weighted, and gaps
were treated as missing data in the analyses. For the ML
analysis, the ML tree was calculated assuming a GTR + CAT
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model of sequence evolution. Robustness of inference was
assessed by running 1000 fast bootstrap replicates. For the
Bayesian analysis, we employed a joint model that
accommodates both rate-heterotachy and pattern-
heterogeneity as implemented in the program
BayesPhylogenies [30]. We performed two runs of 2 million
generations, sampling every 1000 generations, using 4 chains
with the default heating scheme. After discarding the first
200,000 trees in the chain as a ‘‘burn-in’’ period, we sampled
1000 trees to ensure that successive trees in our sample were
independent.
Divergence time estimation
We used the program mcmctree in PAML [54] and 4-fold
degenerate sites to estimate divergence time. The fossil record
of Vitaceae is rich, and seed fossils can be differentiated at the
generic level [55,56]. The oldest confirmed vitaceous seed
fossil is unambiguously assigned to Ampelocissus s.l. (A.
parvisemina) and dates back to the late Paleocene in North
Dakota of North America [56]. Furthermore, Ampelocissus has
been shown not to be monophyletic, but clearly forms a clade
with Vitis, Pterisanthes, and Nothocissus [2,3]. The stem of the
Vitis-Ampelocissus-Pterisanthes-Nothocissus clade was thus
fixed at 58.5 ± 5.0 million yeas ago (Ma). For the root age of
the family Vitaceae, Nie et al. [4,34] and Zecca et al. [57] fixed
the split between Vitaceae and its sister lineage, Leea, as 85 ±
4.0 Ma based on the estimated age of 78-92 Ma by Wikström
et al. [58]. However, Magallón and Castillo [59] reported a pre-
Tertiary origin at 90.65 to 90.82 Ma for Vitaceae. The estimated
ages from Magallón and Castillo [48] and Wikström et al. [58]
are close, but the latter was criticized for using nonparametric
rate smoothing and for calibrating the tree using only a single
calibration point [50]. We herein use the estimate from
Magallón and Castillo [59] and set the normal prior distribution
of 90.7±1.0 Ma for the stem age of the family.
Supporting Information
Figure S1. Length distribution of the coding regions extracted
from the 14 transcriptomes and one reference genome (Vitis
vinifera) of Vitaceae. Sample numbers are shown in Table S1.
(TIF)
Figure S2. Length distribution of 417 ortholog gene
sequences (data include 6672 sequences, the total of 417
genes x 16 samples).
(TIF)
Figure S3. Average bootstrap support and the resampled
nucleotide positions in the phylogenetic analyses to show the
topological stability.
(TIF)
Figure S4. Ks value distributions for paralogs of Vitaceae
species and the outgroup.
(TIF)
Table S1. Vitaceae species sampled for the grape
transcriptome analyses. Voucher specimens are deposited at
the US National Herbarium (US).
(DOCX)
Table S2. Statistical information of the transcriptomes of 15
species of Vitaceae and Leeaceae.
(DOCX)
Table S3. The 1:1:1 orthlog genes selected for phylogenetic
analysis of the grape family.
(DOCX)
Table S4. Topological stability as estimated by bootstrap
support of nodes with the maximum likelihood method by
randomly reducing the gene number by 10, starting from the
229 gene data set.
(DOCX)
Acknowledgements
We thank Mike Barker and Sarah Mathews for advice and
discussions and Tim Utteridge for the photo of Pterisanthes.
Author Contributions
Conceived and designed the experiments: JW EAZ XDF.
Performed the experiments: JW ZQX ZLN LKM XZK YBZ.
Analyzed the data: ZQX ZLN LKM JW. Wrote the manuscript:
JW ZQX ZLN LKM JG XDF SMI EAZ.
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