Oxford University Press
DNA barcodes from four loci provide poor resolution of taxonomic groups in the genus
Crataegus
10.1093/aobpla/plv045
contrib:
CONT
Mehdi Zarrei
Nadia Talent
Maria Kuzmina
Jeanette Lee
Jensen Lund
Paul R. Shipley
Saša Stefanović
Timothy A. Dickinson
AFF
[1 The Centre for Applied Genomics, The Hospital for Sick Children]
AFF
[2 Green Plant Herbarium, Department of Natural History]
AFF
[3 50 Stone Road East, Guelph, ON]
AFF
[4 109 Lakeshore Ave., Edgewood, BC]
AFF
[5 Department of Chemistry, I.K. Barber School of Arts and Sciences]
AFF
[6 Department of Ecology and Evolutionary Biology]
AFF
[7 Department of Biology]
<EMAIL_ADDRESS>[]
[Associate Editor: Kermit Ritland]
[2015-4-29]
[Copyright 2015: ]
[Licence This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits
unrestricted reuse, distribution, and reproduction in any medium, provided the original
work is properly cited.]
[Canada Foundation for Innovation http://dx.doi.org/10.13039/501100000196Ontario Research
FundOntario Genomics Institute http://dx.doi.org/10.13039/5011000000922008-OGI-ICI-03Natural
Sciences and Engineering Research Council of Canada Strategic Research Project grantUniversity
of Western Ontario'sROM Reproductions, Acquisitions, and Research FundDepartment of
Natural HistoryUniversity of Toronto http://dx.doi.org/10.13039/501100003579]
[]
[]
Abstract
The leaves and fruits of some of the approximately 230 species of hawthorn (
Crataegus) yield natural health products with significant therapeutic effects on symptoms of
cardiovascular disease. DNA barcoding could be a valuable tool for authenticating
these products, but only a small fraction of the 93 taxa that we examined were distinguished,
even though all major clades and eight out of ten taxonomic sections of the genus
were included. DNA barcoding as currently practised thus has limited utility in
Crataegus. Hybridization, lineage sorting due to incomplete concerted evolution in ITS2, and
limited variation in plastid loci are implicated.
Abstract
DNA barcodes can facilitate identification of organisms especially when morphological
characters are limited or unobservable. To what extent this potential is realized
in specific groups of plants remains to be determined. Libraries of barcode sequences
from well-studied authoritatively identified plants represented by herbarium voucher
specimens are needed in order for DNA barcodes to serve their intended purpose, where
this is possible, and to understand the reasons behind their failure to do so, when
this occurs. We evaluated four loci, widely regarded as universal DNA barcodes for
plants, for their utility in hawthorn species identification. Three plastid regions,
matK,
rbcLa and
psbA
-trnH, and the internal transcribed spacer 2 (ITS2) of nuclear ribosomal DNA discriminate
only some of the species of
Crataegus that can be recognized on the basis of their morphology etc. This is, in part, because
in Rosaceae tribe Maleae most individual plastid loci yield relatively little taxonomic
resolution and, in part, because the effects of allopolyploidization have not been
eliminated by concerted evolution of the ITS regions. Although individual plastid
markers provided generally poor resolution of taxonomic groups in
Crataegus, a few species were notable exceptions. In contrast, analyses of concatenated sequences
of the 3 plastid barcode loci plus 11 additional plastid loci gave a well-resolved
maternal phylogeny. In the ITS2 tree, different individuals of some species formed
groups with taxonomically unrelated species. This is a sign of lineage sorting due
to incomplete concerted evolution in ITS2. Incongruence between the ITS2 and plastid
trees is best explained by hybridization between different lineages within the genus.
In aggregate, limited between-species variation in plastid loci, hybridization and
a lack of concerted evolution in ITS2 all combine to limit the utility of standard
barcoding markers in
Crataegus. These results have implications for authentication of hawthorn materials in natural
health products.
Introduction
The main aim of DNA barcoding is to identify an unknown organism by comparing a DNA
sequence from the unknown with records in a database of identified sequences, based
on some measure of genetic similarity (
Hebert et al. 2003a
;
Chase et al. 2005
;
Ross et al. 2008
;
Seberg and Petersen 2009
;
Hollingsworth et al. 2011
;
Dong et al. 2012
) or combination of diagnostic sequence characters (
Reid et al. 2011
;
Weitschek et al. 2013
). The Barcode of Life Data Systems (BOLD) database (
Ratnasingham and Hebert 2007
) plays an important role as a centralized and curated depository for DNA barcode
sequences that is effective in archiving and making accessible detailed voucher information
for each organism from which the sequence was obtained. The Consortium for the Barcode
of Life (CBOL) Plant Barcoding Group
(2009)
identified two plastid protein-coding loci,
matK and
rbcL, as the barcode regions for generating a library of identified sequences for plants.
Additional discrimination on species-level taxonomy was proved by using supplementary
markers: plastid
psbA-
trnH intergenic spacer and internal transcribed spacer 2 (ITS2) from nuclear ribosomal
DNA (
Kress et al. 2009
;
Chen et al. 2010
). The usefulness and challenges of using different plant DNA barcodes were summarized
by
Hollingsworth et al. (2011)
. It remains to be seen to what extent these markers can assist identification in
closely related plant taxa that are difficult to identify because, for example, there
is a limited number of characters, not all of which are necessarily present at the
phenological stage of a given specimen.
Hawthorns (
Crataegus, Rosaceae tribe Maleae) are frequent and often locally abundant throughout the North
Temperate Zone in high light intensity habitats where the moisture regime permits
the establishment of woody vegetation. Within the Rosaceae subfamily Amygdaloideae
the genus is relatively large (
Dickinson et al. 2007
), with 50–100 Old World species (
Christensen 1992
), and 150–200 New World ones (
Phipps 2015
). Species identification depends on a suite of characters; some of which can only
be recorded at the time of flowering, while others must be observed in fruiting material.
In addition, identification has been further complicated by the much larger number
of species that have been described in
Crataegus, for which comprehensive synonymies have only recently become available (
Christensen 1992
;
Phipps 2015
).
Hawthorn fruits are edible and a few species are cultivated for their fruits in East
Asia (
C. pinnatifida), Europe (
C. azarolus,
C. germanica) and in the New World (
C. mexicana,
C. opaca). Hawthorns are also used in traditional medicine in all of these places, and there
is a sizable market for natural health products (NHPs) made from hawthorn leaves,
flowers and fruits (
Edwards et al. 2012
). Hawthorn chemistry is fairly well known, but most species studied are Eurasian
ones (Table 1 in
Edwards et al. 2012
;
Yang and Liu 2012
). Studies of the effects of hawthorn preparations in treating hyperlipidaemia and
cardiovascular conditions have been the subject of meta-analyses that suggest there
are significant health benefits to be obtained from these preparations (
Guo et al. 2008
). To date, however, virtually all published studies of the therapeutic components
and the therapeutic effects of hawthorn preparations have used Eurasian
Crataegus species (
Yang and Liu 2012
). Similarly, hawthorn NHPs sold in Europe and North America predominantly employ
raw materials from only a limited number of Eurasian species.
In the southern interior of British Columbia, hawthorns are particularly abundant
as a consequence of their weediness, and of agricultural activity and land-use changes
(
Phipps and O'Kennon 2002
;
Dickinson et al. 2008
). The diversity of described hawthorn species is higher here than anywhere else in
western North America, comprising widespread species like red-fruited
C. chrysocarpa (
C. sect.
Coccineae) and
C. macracantha (
C. sect.
Macracanthae), as well as black-fruited ones (
C. douglasii,
C. suksdorfii in
C. sect.
Douglasia) and their hybrids in
Crataegus series
Douglasianae and
Purpureofructus (
Zarrei et al. 2014
) and the naturalized Eurasian red-fruited hawthorn,
C. monogyna. Native hawthorn species are common throughout the southern half of British Columbia
(south of 56° North latitude). In addition to using their wood for hammers, tool handles
and digging sticks (
Turner 2014b
), coastal and interior First Nations in British Columbia used the fruits of native
hawthorns for food, often smashed so as to break up the pyrenes (and the seeds inside;
Turner 2014b
). First Nation names for both black- and red-fruited hawthorns are documented for
the southern half of British Columbia and the adjacent USA, the latter species (
C. chrysocarpa) mainly in the southern and interior portion of this range (
Turner 2014a
,
b
). In fact, hawthorn species across North America are named by First Nations people,
and ethnobotanical uses of hawthorn species are documented for food and for treatments
of various conditions, including gastrointestinal, dermatological and heart ailments
(
Arnason et al. 1981
;
Edwards et al. 2012
).
Together with widespread use of hawthorn NHPs that are manufactured almost exclusively
from a small number of Eurasian species, the diversity and abundance of hawthorns
in British Columbia has led to recognition of a potential economic opportunity for
locally sourced NHPs. For example, the Naturally Grown Herb and Spice Producers Cooperative
(HerbPro;
http://herbpronaturals.ca/HerbPro/
) has established an agroforestry demonstration farm with hawthorn as the main orchard
alley cropping tree. HerbPro has developed a fresh/frozen puree of
C. chrysocarpa fruit and
C. monogyna leaf and has had farm-gate sales since 2008. Anecdotal evidence has shown that the
puree has positive health benefits for those with cardiovascular disease and hypertension.
The raw ingredients for NHPs manufactured and marketed in Canada must be identified
and the species listed on product labelling. Collaboration between HerbPro and the
academic authors has focussed on evaluating the chemistry and taxonomy of western
North American hawthorns, developing identification tools that can be used in the
field, and investigating the extent to which DNA barcodes can be used to confirm identifications
and authenticate raw ingredients in post-harvest processing (e.g. dried and/or powdered
forms of fruit, leaf and flower). Our collaboration also includes limited trials of
hawthorn preparations in an animal model of human metabolic syndrome (F. Borthwick
et al., unpubl. data—presented in part as
Dickinson et al. 2014
).
Hawthorn preparations, as employed in the animal trials described above and as used
in NHP formulations, comprise not only biopolymers (nucleic acids, proteins) but also
complex mixtures of much lower molecular weight secondary metabolites. Characterization
of these secondary metabolites (the metabolome) by means of analytical instrumentation
such as mass spectrometer or nuclear magnetic resonance (NMR) spectrometer (metabolomics;
Oliver et al. 1998
) provides another means by which to describe hawthorn species. Since the therapeutic
effects of hawthorn preparations appear to be mediated by the metabolome (notably,
phenolic compounds;
Edwards et al. 2012
;
Yang and Liu 2012
), it is valid to ask to what extent the variation in the metabolomes of
Crataegus species parallels the variation in DNA sequences. Given that the DNA sequence variation
reflects genealogical relationships (we infer the latter from the former), we wish
to see whether or not metabolomics resemblances reflect phylogenetic relationships.
To the extent that the molecular data are sufficient (sequence variation in ITS and
two chloroplast loci) in a study of
Stachys (Lamiaceae;
Salmaki et al. 2013
), we know that phytochemical variation (
Tundis et al. 2014
) is not necessarily congruent with phylogeny. Non-metric multidimensional scaling
of data for several classes of secondary metabolites (mono-, sesqui- and diterpenes,
iridoids, phenylethanoid glycosides, flavonoids) contrasts species of
Stachys and those of
Sideritis, while species of the genus
Betonica are located in a subset of the chemospace occupied by the
Stachys species (
Tundis et al. 2014
). In the nuclear and plastid phylogenies, however,
Betonica is one of the outgroups for
Stachys, and the species of
Sideritis are nested among those of
Stachys (
Salmaki et al. 2013
).
Here we examine the utility of the proposed plant DNA barcode loci, comparing the
information they provide for hawthorns with that obtained using additional loci and
molecular phylogenetic methods. In doing so, we seek to (i) sample the species diversity
of hawthorns extensively in order to generate a vouchered library of DNA sequences
deposited in BOLD (see
Supporting Information—Table S1
; dx.doi.org/10.5883/DS-NAMCRAT;
Ratnasingham and Hebert 2007
) and GenBank (
Benson et al. 2011
) from
Crataegus specimens that have already been identified by expert taxonomists; (ii) assess the
utility of the universal plant DNA barcoding markers in species identification, particularly
in discrimination of medicinally important taxa; (iii) compare the preceding results
with those of phylogenetic analyses of the cpDNA barcoding loci augmented by 11 additional
cpDNA loci chosen for the variability they exhibit in
Crataegus and other Maleae (
Lo and Donoghue 2012
) and (iv) examine whether polyploidization, apomixis and possibly incomplete concerted
evolution of ITS limit the usefulness of DNA barcoding in plant groups where these
factors may be frequent (
Hollingsworth et al. 2011
;
Zarrei et al. 2012
,
2014
). (v) We provide a preliminary NMR metabolomics dataset with which we examine the
relationship between similarities in the therapeutically significant phenolic composition
of leaf tissue with that of phylogenetic relationships seen in the cpDNA sequence
data.
Methods
Plant materials
We sampled DNA barcode loci for 355
Crataegus specimens in the Royal Ontario Museum Green Plant Herbarium (TRT;
Supporting Information—Table S1
; BOLD doi:10.5883/DS-NAMCRAT), selected as follows. A total of 275 samples of primarily
North American species came from hawthorn trees in Ontario, the southeastern USA,
Colorado, Utah, Wyoming and the Pacific Northwest for which we had leaf tissue dried
on silica gel, as well as voucher specimens (
Talent and Dickinson 2005
;
Lo et al. 2007
,
2009
;
Dickinson et al. 2008
;
Coughlan 2012
;
Zarrei et al. 2012
,
2014
;
Coughlan et al. 2014
). For these individuals up to 10 accessions per species (or cytotype) were sampled
[see
Supporting Information—
Table S1
]
. This material also included vouchered samples collected at the arboreta and botanical
gardens acknowledged in our earlier papers, together with samples of Eurasian species
provided to us by K. I. Christensen, A. A. Dönmez and T. Romankova
[see
Supporting Information—Table S1
]. A further 80 TRT herbarium specimens of North American species from the J.B. Phipps
Hawthorn Research Collection
[see
Supporting Information—Table S1
] were sampled as part of the Canadian Centre for DNA Barcoding project, ‘DNA Barcode
Flora of Canada’. Of the samples, 38
[
Supporting Information—Table S1]
, together with samples from 6 additional individuals, were used for more intensive
study of cpDNA sequence variation in mainly Pacific Northwest
Crataegus
[Supporting Information—Table S2]
(cf.
Zarrei et al. 2014
). Finally, a further eight accessions were part of samples used to explore the utility
of the two low-copy nuclear markers described below (AT1 and PEPC;
Supporting Information—Tables S3 and S4
). DNA for some of these individuals was obtained from seeds. These 369
Crataegus samples represent all of the clades found by
Lo et al. (2007
,
2009
), as well as all four sections native to North America and four of six sections native
to Eurasia (i.e. not including any of the four species in sections
Cuneatae and
Henryanae). Our sample also comprises four named nothosections, as well as 35 series, two named
nothoseries and 83 species (plus five varieties, one hybrid and four named nothospecies;
Supporting Information—Tables S1 and S2
). Although just over one-third of our 369 accessions belong to
C. section
Douglasia, the taxonomic breadth of our sample is sufficient to let us relate the infrageneric
classification
[
Supporting Information—Table S1]
to the phylogenetic structure found by
Lo et al. (2007)
in a similarly wide sampling of the genus. Most of the samples studied come from
individuals whose ploidy level and breeding system have been documented either by
means of chromosome counts and embryological studies (
Dickinson et al. 1996
), or by means of flow cytometry of leaf and seed tissues (
Talent and Dickinson 2005
,
2007a
;
Supporting Information—Tables S1 and S2
).
Based on the results of
Campbell et al. (2007)
,
Potter et al. (2007)
and
Lo et al. (2007)
, sequences from
Amelanchier,
Cotoneaster,
Malus,
Pyrus and
Sorbus were chosen for outgroup rooting of all but one of the trees produced in this study
[see
Supporting Information—Tables S1–S4
]. The tree built from sequences of the plastid barcode loci
[see
Supporting Information—
Fig. S1
]
was rooted using the sequences from
Crataegus brachyacantha, following the results of
Lo et al. (2007)
, and based on the similarity of the submarginal venation seen in leaves of this species
(unique in
Crataegus; Fig. 1 in
Dickinson et al. 2008
) to that of
Hesperomeles (
Kelly 2008
), a genus shown by
Li et al. (2012)
to be sister to
Crataegus.
Molecular methods
Four DNA barcodes (
rbcL,
matK,
psbA
-trnH and ITS2;
Chase et al. 2007
;
CBOL Plant Working Group 2009
;
Hollingsworth et al. 2011
) were generated directly from genomic DNA for the 355
Crataegus accessions in the NAMCRAT dataset. DNA was extracted and amplified from leaf tissue
using Canadian Centre for DNA Barcoding (CCDB) protocols (
Ivanova et al. 2011
;
Kuzmina and Ivanova 2011a
,
b)
. With ITS2, additional primers (
White et al. 1990
;
Stanford et al. 2000
;
Chen et al. 2010
) were needed for successful amplification in some cases. The barcoding sample overlapped
partially with that for which additional plastid loci were sequenced (below), and
for which cloned ITS2 sequences were studied (
Zarrei et al. 2014
). The successfully amplified amplicons were then sequenced on the 3730xl DNA Analyser
(Applied Biosystems) with both forward and reverse primers to assure accuracy.
To increase the discriminatory power of the plastid markers especially in view of
the potential consequences of long generation times associated with woodiness in
Crataegus (
Smith and Donoghue 2008
), an additional 11 plastid markers (
Lo and Donoghue 2012
) were sequenced for a subsample of individuals
[see
Supporting Information—Table S2
], using the DNA extraction protocols described in
Zarrei et al. (2014)
. They are as follows:
trnG-
trnS (
Hamilton 1999
),
rpl2-
trnH (
Vaillancourt and Jackson 2000
),
rpl20-
rps12 (
Hamilton 1999
),
trnL-
trnF (
Taberlet et al. 1991
),
atpB-
rbcL (
Campbell et al. 2007
),
rps16 intron (
Campbell et al. 2007
),
rpl16 intron (
Campbell et al. 2007
),
trnC-
yfc6,
accD (forward, 5′-AGAATGGGTACCTCGA-3′; reverse, 5′-GTGTGGTGATCAAGTAGTTA-3′, designed
here),
rpoC1 (
Burgess et al. 2011
) and
atpF-
atpH (
Burgess et al. 2011
). For this component of the project, the plastid barcode loci were amplified and
sequenced using the following primers:
matK (forward, 5′-ACCCCATTCATCTGGAAATCTTGGTTC-3′; reverse, 5′-CGTACAGTACTTTTGTGTTTACGAG-3′,
designed here),
rbcLa (forward,
Levin et al. 2003
; reverse,
Kress and Erickson 2007
) and
psbA
-trnH (forward,
Tate and Simpson 2003
; reverse,
Sang et al. 1997
). The plastid amplicons were directly sequenced using the PCR primers. Post-PCR steps
for all markers were followed as in
Zarrei et al. (2014
). Cycle sequencing reactions were performed using the BigDye
® Terminator v3.1 kit (Applied Biosystems, Inc., Foster City, CA, USA). Cleaned cycle
sequencing products were sequenced on an ABI 3730 (Applied Biosystems) DNA Analyser
at the Royal Ontario Museum (Toronto, Canada). Sequences were proofed and edited using
Geneious Pro. v.5.6 (
Drummond et al. 2012
) and assembled using Geneious Pro. v.5.6 or BioEdit v.<IP_ADDRESS> (
Hall 1999
).
We also investigated two low-copy nuclear markers, i.e. the partial Phosphoenolpyruvate
Carboxylase (PEPC) gene and the Pentatricopeptide region (PPR) homologue to the AT1G09680
gene in Arabidopsis (AT1), in smaller samples representing mainly
Crataegus section
Douglasia
[see
Supporting Information—
Tables S3 and S4
]
. Details of the methods used are given in
Supporting Information—
File S1
.
Chemistry sample preparation
Leaves from 14 hawthorn samples representing four species (Table
1
) were lyophilized for 24 h and then ground to a fine powder using a food mill. The
milled plant material was passed through a 520 µm sieve (30 mesh) to remove any insufficiently
milled particles. Two hundred and fifty milligrams of filtered material were extracted
sequentially with three aliquots of deuterated methanol (methanol-d4) containing 5
mM 4,4-dimethyl-4-silapentane-1-sulfonic acid (DSS; 1.0, 0.5, 0.5 mL), centrifuged,
and the supernatants collected and combined. This extract was filtered through a 0.45
µm polyfluorotetraethylene syringe filter prior to transfer into an NMR tube for analysis.
Table 1.
Sources of the
Crataegus leaf samples lyophilized and extracted for the metabolomics assays (Fig.
2). All WKHGC samples were collected from hawthorn individuals grown from bare root
stock planted in 2005, 2006 and 2007 as orchard alley cropping trees at the Naturally
Grown Herb and Spice Producers Cooperative (HerbPro) agroforestry demonstration farm
in Edgewood BC. Ploidy levels in parentheses are those known for the taxon in question;
all four
C. suksdorfii shown to be diploid by flow cytometry.
| Taxon |
Sample |
Locality |
Voucher |
|
C. monogyna Jacq. (2
x)
|
|
|
WKHGC491 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC493 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC620 |
Edgewood BC (49.805, −118.156) |
|
|
C. okanaganensis J.B. Phipps and O'Kennon (4
x)
|
|
|
WKHGC490 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC495 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC619 |
Edgewood BC (49.805, −118.156) |
|
|
C. douglasii Lindl. (4
x)
|
|
|
WKHGC492 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC617 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC488 |
Edgewood BC (49.805, −118.156) |
|
|
WKHGC494 |
Edgewood BC (49.805, −118.156) |
|
|
C. suksdorfii (Sarg.) Kruschke—2
x
|
|
|
JC042 |
OR, Jackson Co. (42.4307, −123.094) |
TRT00020321 |
|
JC060 |
OR, Linn Co. (44.5626, −123.152) |
TRT00020146 |
|
JC139 |
OR, Columbia Co. (46.1106, −122.984) |
TRT00020243 |
|
2013-01 |
OR, Josephine Co. (42.278, −123.647) Deer Creek Center |
TRT00028421 |
Nuclear magnetic resonance spectra acquisition
A Varian MercuryPlus 400 MHz NMR instrument was used to acquire the metabolomic data
(Varian, Inc., Palo Alto, CA, USA). One-dimensional proton spectra NMR experiments
were acquired at 25 °C over a spectral width of 4201.7 Hz with an observe pulse of
11.80 µs (90°) using a PRESAT water suppression sequence including a PURGE cycle.
The acquisition time was 3.899 s, resulting in a dataset of 16 000 points. A total
of 128 transients were acquired for each spectrum. Spectra were processed using MestReNova
version 9.0.1 (Mestrelab Research S.L., Santiago de Compostela, Spain) and were manually
phased and baseline corrected using a Whittaker Smoother base point detection with
spline fitting. The spectra were then referenced, binned to chemical shift widths
of 0.005 ppm and normalized to the DSS reference peak. A transposed data matrix of
chemical shifts and the intensity values of the superimposed spectra was exported
as a comma separated value file (*.CSV) and imported to Microsoft Excel for formatting
prior to import into multivariate statistical analysis software. Statistical analysis
was performed on the region of the spectrum where the majority of the signals are
due to plant phenolic compounds (6.0–8.0 ppm), resulting in a data matrix of 44 samples
with 400 observables (intensities in each chemical shift bin). The data were then
imported into the multivariate statistical analysis software, Solo version 7.3.1 (Eigenvector
Research, Inc., Wenatchee, WA, USA).
Data analyses
Barcoding markers
The DNA sequences were edited and uploaded into the BOLD system (
Ratnasingham and Hebert 2007
). Following the guidelines proposed by the
CBOL Plant Working Group (2009)
and
Hollingsworth et al. (2011)
, the suitability of DNA barcoding for hawthorns was assessed against three main criteria:
(i) universality and marker amplification success, (ii) sequence quality and coverage
and (iii) discriminatory power among species. The data were analysed in two steps.
Each marker was first analysed individually. Because plastid markers in Maleae appear
to be inherited maternally (
Corriveau and Coleman 1988
;
Ishikawa et al. 1992
;
Raspé 2001
) and because they are found on a single chromosome as a linkage group (
Doyle 1992
), all three plastid markers were concatenated into a single matrix. Due to the paralogy
issues associated with the ITS2 marker in
Crataegus (discussed in
Zarrei et al. 2014
), the ITS2 data were not combined with those from the plastid markers in the final
analyses.
To assess the universality of markers, we report the per cent sequencing success for
each locus (Table
2
). The assessment of the sequence quality was performed via the CCBC automated informatics
pipeline following the guidelines of the
CBOL (2009)
. Character-based analysis [maximum parsimony (MP) and Bayesian inference] has also
proved to be a useful tool for species identification (
Lowenstein et al. 2009
;
Kelly et al. 2010
). However, since
Hebert et al. (2003a
,
b)
proposed the use of genetic distance as a standard method for analyses of barcode
data, the majority of barcoding studies have followed this distance-based approach
(reviewed in
Taylor and Harris 2012
). Neighbour-Joining (NJ) trees (
Saitou and Nei 1987
) were built using both the tools made available by BOLD (Jalview 2,
Waterhouse et al. 2009
; Kimura 2 parameter, after alignment by MUSCLE,
Edgar 2004
) and PAUP* v. 4b10 (
Swofford 2003
).
Table 2.
Barcoding information for the four markers investigated here for 355 samples representing
93
Crataegus taxa
[see
Supporting Information—
Table S1
]
.
1Percentage of individuals successfully sequenced.
2Outgroups excluded; calculated using MEGA v. 6.0 (
Tamura et al. 2013
).
| Marker |
matK
|
rbcLa
|
psbA-
trnH
|
ITS2 |
| Aligned sequence length (bp) |
783 |
552 |
429 |
671 |
| Unaligned length (mean); excluding end gaps |
321 (705.7 ± 99.3) 783 |
485 (551.3 ± 5.3) 552 |
183 (274.9 ± 22.0) 429 |
112 (312 ± 92.5) 587 |
| Pairwise % identity |
99.3 |
99.8 |
87.6 |
79.8 |
| Number of taxa successfully amplified and sequences |
82 |
93 |
81 |
65 |
| Number of samples successfully amplified and sequenced |
255 |
340 |
290 |
192 |
| % sequencing success
1
|
71.8 |
95.8 |
81.7 |
54.1 |
| Overall mean sequence divergence
2
|
0.001 |
0.002 |
0.128 |
0.135 |
Our evaluation of the success of the different barcode loci corresponds to the tree-based
methods described by
Ross et al. (2008)
. These authors used simulations to conclude that other approaches to using genetic
distance data to evaluate barcoding success (BLAST, comparisons of the distances between
unknowns and candidate reference taxa) will fail when not all candidate species are
represented unambiguously in the set of reference taxa. Thus we know that because
of the relatively limited sequence variation seen within the Maleae with individual
chloroplast loci (
Evans et al. 2000
;
Campbell et al. 2007
;
Potter et al. 2007
) the correspondence between a barcode sequence and a taxon may be ambiguous. The
abundance of ITS2 paralogs found by
Zarrei et al. (2014)
will have the same effect.
Additional plastid markers
All plastid sequences were submitted to GenBank (
Benson et al. 2011
), and the accession numbers are available in
Supporting Information—Table S2
. The sequences were aligned with CLUSTAL X (
Thompson et al. 1997
) or Geneious alignment option of Geneious Pro v.5.6 (
Drummond et al. 2012
). This initial alignment was adjusted manually in BioEdit v.<IP_ADDRESS> or Geneious Pro
v.5.6 to minimize steps in the most parsimonious trees (e.g.
Koch et al. 2010
). Because all 14 plastid markers (including the three barcode markers) used in this
study are linked, the concatenated sequence matrix was analysed. However, separate
parsimony analyses were conducted for each marker to investigate the possible incongruence
(discussed in
Bull et al. 1993
) among datasets. Two different phylogenetic analyses were run for the concatenated
regions: (i) MP analyses using PAUP* v. 4b10 (
Swofford 2003
) and (ii) Bayesian analyses (BIs;
Yang and Rannala 1997
) using MrBayes v. 3.2.0 (
Ronquist and Huelsenbeck 2003
;
Ronquist et al. 2010
). The details of each analysis are the same as in
Zarrei et al. (2014)
. Indels were coded as separate presence/absence characters using SeqState version
1.4.1 (
Müller 2005
) with modified complex coding option originally described by
Simmons and Ochoterena (2000)
and appended to the end of matrices.
In the parsimony analysis, the character state changes were equally weighted and character
changes were interpreted under ACCTRAN optimization (
Agnarsson and Miller 2008
). A two-stage strategy of Fitch parsimony (
Fitch 1971
) search was undertaken following
Zarrei et al. (2014
). The phylogenetic reliability was assessed using non-parametric bootstrapping. The
bootstrap support (BS) was estimated using 1000 bootstrap pseudoreplicates with simple
taxon addition and TBR swapping but permitting only 10 trees per replicate to be held.
The consistency index (CI), rescaled consistency index (RC) and
Farris's (1989)
retention index (RI) were calculated to measure the amount of homoplasy in the dataset.
The best-fit model for each region in the plastid concatenated matrix is provided
in
Supporting Information—Table S5
. These models were selected by Akaike information criterion (AIC;
Akaike 1974
), as implemented in MrModeltest v. 2.3 (
Nylander 2004
).
For the BIs, two simultaneous runs with four chains each were run for 20 million generations.
In each run, every 2000th tree was sampled. The completion of the BI was determined
when the average standard deviation of split frequencies ≤0.05 (
Ronquist and Huelsenbeck 2003
) for the combined two runs was assumed and the complete convergence between the Bayesian
Markov chain Monte Carlo runs was reached. Convergence of an independent search was
further explored by plotting likelihood scores vs generations using the program Tracer
v1.5 (
Rambaut and Drummond 2007
). The burn-in phase for each run—the first 25 % of sampled trees—was discarded during
computing the phylogram consensus tree based on the average branch lengths (50 % majority
rule) of the remaining trees (15 000 trees) using
sumt command implemented in MrBayes. Support for Bayesian topologies was estimated using
node posterior probabilities (PPs) from the posterior distribution of topologies.
Metabolomic data
Classes were defined for each sample according to its species identification. Before
multivariate analysis, mean centring and Pareto scaling, where each variable is divided
by the square of its standard deviation, were applied to the dataset (
van den Berg et al. 2006
). Following this, a hierarchical cluster analysis (HCA) was performed. The HCA dendrogram
was generated using Ward's minimum variance method with Mahalanobis distance and generalized
least squares weighting to
α = 0.001.
Results
Barcoding markers
Across all four regions investigated, a total of 1077 assembled DNA sequences were
obtained from 355 samples (mean = 3.03 regions sequenced per sample; BOLD dx.doi.org/10.5883/DS-NAMCRAT,
Table
2
;
Supporting Information—Table S1
). The overall average sample sequencing success was 75.8 %, ranging from 54.1 % for
ITS2 to 95.8 % for
rbcLa (Table
2
). Internal transcribed spacer 2 had the lowest species sequencing success (69.9 %),
compared with 100 % for
rbcLa (Table
2
). The sequences were retrieved for all the markers using both the forward and reverse
primers. The variation in both the sequence length (because of insertions or deletions)
and additive polymorphic sites (APS) was detected in the sequences of ITS2 due to
the presence of multiple copies of ITS2 in the genome of each individual (see Discussion
for more detail). No APS were detected in the traces obtained from the plastid markers.
However, displacement of electropherograms was observed in
psbA
-trnH tracers due to the presence of homopolymer runs (
Devey et al. 2009
;
Fazekas et al. 2010
). Sequencing with the reverse primer resolved this problem. Pairwise percentage sequence
identity varied from a low of 79.8 % (ITS2; estimated using Geneious Pro. v.5.6,
Drummond et al. 2012
; Table
2
), to a high of 99.8 % (
rbcLa; Table
2
). The lowest sequence identity among the plastid barcode markers investigated here
was 87.6 % for the
psbA
-trnH spacer (Table
2
).
Resolution of the barcode loci
Despite earlier success using barcode sequence data to confirm the parentage of two
hybrids (
Christensen et al. 2014
), only a very limited number of
Crataegus species are diagnosable using individual plastid barcode loci (Table
3
; cf.
Fineschi et al. 2005
). In addition to the six taxa (five species and one hybrid) for which at least one
locus provided a diagnostic position (Table
3
), single-nucleotide polymorphisms also diagnose two interesting groupings including
the autotriploid
C. gaylussacia with its probable progenitor, diploid
C. suksdorfii (
matK, Table
3
;
Zarrei et al. 2014
). The other grouping of interest is that of
C. ×
canescens together with (i)
C. sect.
Crataegus and its hybrids with
C. punctata (
Christensen et al. 2014
), (ii)
C. brachyacantha, and
C. spathulata (
rbcLa, Table
3
) and (iii)
C. germanica (
C. sect.
Mespilus), and all of the
C. ser.
Cerrones taxa in the sample (
psbA
-trnH, Table
3
). On the basis of their molecular phylogeny of
Crataegus,
Lo et al. (2007
) suggested that
C. ×
canescens (originally described as
Mespilus canescens J.B. Phipps) was likely a hybrid involving
C. germanica,
C. brachyacantha and an unknown third taxon.
Table 3.
Single-nucleotide changes in the three chloroplast markers investigated in
Crataegus for 355 samples representing 93 distinct taxa
[see
Supporting Information—
Table S1
]
. With these loci the accessions belonging to six taxa formed distinct single-taxon
clusters in the corresponding NJ tree calculated by BOLD; these clusters result from
the polymorphisms shown (position in the consensus sequence). In bold, polymorphisms
and positions scored as diagnostic by BOLD (
n ≥ 3). Ploidy levels shown are based on data from earlier studies (
Talent and Dickinson 2005
;
Coughlan et al. 2014
;
Zarrei et al. 2014
). In addition to
C. ×
canescens (
Lo et al. 2007
),
C. spathulata (
Lo et al. 2007
) and
C. nigra (
Zarrei et al. 2014
) are suspected of being (paleo-) hybrids.
| Marker |
matK
|
rbcLa
|
psbA-
trnH
|
|
C. ×
canescens (allotriploid;
n = 6)
|
|
T → C (5) with
N = 21 diploid
C. sect.
Crataegus and 4
C. ×
ninae-celottiae
|
G → C (287) with
N = 10 diploid
C. germanica and 17
C. ser.
Cerrones
|
|
A→G (57) |
|
C → G (121)
|
|
A→G (391) |
|
C. brachyacantha (diploid;
n = 9)
|
|
A→G (57) |
|
|
G → C (244)
|
|
G → A (357)
|
|
A →G (391) |
|
C. spathulata (diploid;
n = 3)
|
T → A (238)
|
A→G (57) |
G→A (91) |
|
A → G (621)
|
A→G (391) |
|
C. gaylussacia (autotriploid;
n = 6)
|
C→T (288) with
N = 7 diploid
C. suksdorfii
|
C → T (417)
|
|
|
C. nigra (diploid;
n = 3)
|
G→T (277) |
A → C (120)
|
|
|
C. pinnatifida (diploids, triploids, tetraploids and hexaploids known;
n = 3)
|
T→G (75) with
N=3 of seven
C. macracantha
|
|
G→T (197) |
|
G → A (354) with
N = 2
C. hupehensis
|
|
|
Combining the sequences of the three plastid barcode loci into a single alignment
yielded an NJ tree
[see
Supporting Information—
Fig. S1
]
in which some more and better-resolved clusters appeared, but few of these comprised
only a single species, or even only closely related species (e.g. belonging to the
same taxonomic series
[see
Supporting Information—
Fig. S1
]
). Also, topological relationships between groups expected from earlier analyses of
more informative loci (
Lo et al. 2007
,
2009
;
Zarrei et al. 2014
) were not recovered in the NJ tree based only on
rbcLa,
matK and
psbA
-trnH data
[see
Supporting Information
—Fig. S1
]
.
The NJ tree based on ITS2 sequences obtained by direct amplification of genomic DNA
according to the BOLD protocol
[see
Supporting Information—
Fig. S2
]
is similarly problematic. As described earlier (
Dickinson et al. 2011
), while some diploids formed well-resolved single-species clusters (
Supporting Information—Fig. S2
; e.g.
C. brachyacantha,
C. germanica,
C. spathulata), others did not (
Supporting Information—Fig. S2
; e.g.
C. marshallii,
C. punctata). Polyploids were found in heterogeneous clusters that in some cases did not include
the most closely related diploid species (
Supporting Information—Fig. S2
; e.g.
C. ser.
Cerrones).
Phylogenetic analysis of 14 plastid markers
No incongruence was detected between datasets in separate parsimony analyses of the
14 markers. In contrast to clustering based on one or a few barcode loci, phylogenetic
analysis of a total of 560 sequences for 14 markers
[see
Supporting Information
—Table S6
]
yielded much greater resolution, and recovered the groups and topological relationships
expected from earlier analyses (in Fig.
1, branches are labelled so as to correspond as nearly as possible with those in Fig. 4
of
Zarrei et al. 2014
). The concatenated plastid matrix comprised 10 570 sites; of which, 487 (4.6 %) were
variable and 190 (1.84 %) were parsimony-informative (including outgroups). The loci
with highest percentages of parsimony-informative sites were
rpl2-
trnH (3.65 %) and
psbA
-trnH (3.35 %). Two markers,
rpoC1 (0.18 %) and
rbcLa (0.36 %), yielded the fewest parsimony-informative sites. Due to the very low resolution
of the trees resulting from the individual markers, these trees are not shown. The
first and second stage of parsimony analysis (
Zarrei et al. 2014
) of the concatenated plastid matrix generated 18 trees, each with: 587 steps, a CI
of 0.86, a RC of 0.77 and a RI of 0.89 (Fig.
1). The ingroup is well supported (PP = 1; BS = 99).
Figure 1.
Crataegus phylogram based on sequence data from 14 plastid loci
[see
Supporting Information—
Table S2
]
; majority rule consensus of 15 000 Bayesian trees. Numbers above branches are PP;
numbers below the branches are percent BS. For ease of comparison, clades are labelled
as in Fig. 4 of
Zarrei et al. (2014)
. Scale for branch lengths is substitutions per site.
Crataegus suksdorfii 3
x* = sampled from Haida Gwaii;
C. suksdorfii 3
x^ = sampled from Vancouver Island;
C. rivularis* sampled from Colorado (NT273);
C. rivularis^ sampled from Wyoming (2001–42). An asterisk following the bootstrap value indicates
the branches collapse in the strict consensus tree of 18 trees. The infrageneric classification
mapped onto the tree is based on
Christensen et al. (2014)
, Dickinson
et al. (in prep.) and
Phipps (2015)
.
Topological relationships between groups expected from earlier analyses (
Lo et al. 2007
,
2009
;
Zarrei et al. 2014
) were found here (Fig.
1), as was not the case in the analysis of only three concatenated plastid loci
[see
Supporting Information—
Fig. S1
]
or in that of the ITS2 sequences amplified from genomic DNA
[see
Supporting Information—
Fig. S2
]
.
Crataegus germanica (
C. section
Mespilus) and
C. brachyacantha (
C. section
Brevispinae) branch as successive sisters to the remaining ingroup taxa.
Crataegus section
Crataegus forms a well-supported group (Fig.
1, clade A; PP = 1, BS = 94). Its sister clade (Fig.
1, Clade B) comprises
C. sections
Coccineae and
Macracanthae mainly of eastern North America (Fig.
1, clade E) and an unlabelled clade (star, Fig.
1). This unlabelled clade consists of the remaining Eurasian species (in
C. sect.
Sanguineae, branches G
1
and G
2
) and the primarily western North American
C. sect.
Douglasia (Fig.
1, clades F and H).
Clade D comprises species belonging to
C. section
Sanguineae and
C. section
Douglasia (Fig.
1). The phylogenetic relationship of
C. maximoviczii (
C. section
Sanguineae; Fig.
1, clade G
1
) is not resolved and this species is in a polytomy with clades D and F. Clade F comprises
C. series
Cerrones (PP = 1; BS = 95) from the central Rocky Mountains, and the southern British Columbia
allotetraploid,
C. shuswapensis (
C. series
Douglasianae).
As noted earlier (
Zarrei et al. 2014
), the behaviour of well-documented recent intersectional hybrids (
Christensen et al. 2014
) helps elucidate the allopolyploid status of a number of species in
C. section
Douglasia. Three individuals of
C. ×
ninae-celottiae (=
C. monogyna ×
C. punctata;
Christensen et al. 2014
) analysed here are grouped with other members of sect.
Crataegus in clade A with PP = 1 and BS = 99 (Fig.
1). In contrast, the two individuals of
C. ×
cogswellii (=diploid
C. suksdorfii×
C. monogyna;
Christensen et al. 2014
) in our sample form a clade (
I
3
, Fig.
1) with diploid
C. suksdorfii with PP = 1 and BS = 98. Both nothospecies arose from hybridization over the past
200 years between native North American diploids and the introduced Eurasian species,
C. monogyna (
Christensen et al. 2014
). The cladistic relationships between these hybrids and their parents seen in a phylogeny
based on maternally inherited loci provide a good indication of the predominant direction
in which hybridization has taken place (
Christensen et al. 2014
).
The same logic applies to the cladistic relationships between allopolyploids in
C. series
Douglasianae (Fig.
1, clade H, mostly) and those in
C. nothoseries
Montaninsulae and
Purpureofructus (Fig.
1, clades E
2
and E
3
). These relationships (Fig.
1) suggest that tetraploid
C. chrysocarpa (or another member of
C. series
Rotundifoliae) is the female parent of
C. okanaganensis (also tetraploid; clade E
2
, PP = 0.71, BS = 69), whereas tetraploid
C. macracantha (or another member of
C. sect.
Macracanthae) is the female parent of the remaining section
Douglasia species in clade E
3
(PP = 1, BS = 99). Members of
C. sect.
Coccineae (probably also either
C. chrysocarpa or
C. macracantha, as these species are the only ones with any appreciable range in the trans-Mississippi
west) appear to have been the male parents of the other allopolyploids in
C. section
Douglasia (Fig.
1; clades I
2
,
C. castlegarensis and
C. enderbyensis, and I
4
,
C. douglasii and
C. okennoni;
Zarrei et al. 2014
). As in the case of the two diploid nothospecies derived from
C. monogyna (
Christensen et al. 2014
), the presence of cloned ITS2 variants from both
C. section
Coccineae and
C. section
Douglasia in these tetraploid nothospecies clinched their hybrid status (
Zarrei et al. 2014
). Finally, the same logic elucidates the origin of polyploid
C. suksdorfii (Fig.
1, clade I4;
Zarrei et al. 2014
).
Metabolomic analysis of Crataegus species
Comparison of four
Crataegus species (Fig.
2) with respect to their
1H NMR metabolomics data demonstrates the greater similarity of the two allotetraploids
in the sample to each other, relative to their putative common ancestor, diploid
C. suksdorfii. Crataegus monogyna is most dissimilar, and in this respect these limited metabolomics results parallel
the phylogenetic relationships determined from both chloroplast DNA sequence data
(Fig.
1) and nuclear DNA (
Lo et al. 2007
,
2009
;
Zarrei et al. 2014
). This analysis targeted phenolic compounds because they have demonstrated cardioprotective
activity. As specialized metabolites they are also more likely to vary more between
species than within samples compared with primary metabolites such as sugars.
Figure 2.
Hierarchical cluster analysis of
1H NMR metabolomics data of phenolic compounds (6–8 ppm) from four
Crataegus species (Table
1
).
Discussion
Using data from 93 mostly species-level
Crataegus taxa that represent all major clades and 8 out of 10 sections of the genus, we assess
DNA barcode markers using the following three criteria: (i) universality and marker
amplification success, (ii) sequence quality and coverage and (iii) discriminatory
power among species. We will also comment on the additional information that our DNA
barcode data provide and on the serious limitations that our results place on using
DNA barcodes to identify hawthorn species and authenticate hawthorn NHPs.
Barcode universality and amplification success in Crataegus
The plastid markers met the first criterion for DNA barcoding, namely that amplification
succeeded with almost all hawthorn accessions tested (87.1–100 % of the taxa amplified;
Table
2
). In contrast, amplification of the ITS2 region was generally less successful, and
obtaining the data analysed here required recourse to additional primer pairs (65
taxa amplified; Table
2
).
Crataegus barcode sequence quality and coverage
The plastid markers also met the second criterion for DNA barcoding, namely that sequence
quality was generally high for each of the markers investigated here (Table
2
). However, the sequencing success for
matK was lower than that for the rest of the plastid markers. The ITS2 region had the
lowest rate of sequencing success (69.9 %). Sequence quality was also low so that,
overall, ITS2 yielded the fewest barcode sequences (Table
2
).
The limits of plastid DNA barcode discrimination of Crataegus species
There are more than 200
Crataegus species native to North America (
Phipps 2015
). We have sampled 93 mostly species-level taxa, and our accessions represent all
four native sections, one naturalized section and the four nothosections of the genus
that are currently recognized (
Lo et al. 2007
;
Brouillet et al. 2010+
;
Christensen et al. 2014
). In addition, our accessions represent a comprehensive sample of
Crataegus in western North America, and of
C. section
Douglasia, thus matching recommendations in
Piredda et al. (2011)
for ensuring that the correct relationship between barcode sequences and species
is obtained. Individually, the nucleotide diversity of the three plastid DNA barcode
markers was low and distinguishes only three species and one nothospecies (Table
2
; five in all, if the European species
C. nigra is included). Similar results using just the
psbA
-trnH barcode locus have been obtained in
Fragaria, where only two species out of 21 could be distinguished (
Njuguna and Bassil 2011
). In the NJ tree for the concatenated plastid loci (317 individuals with data for
at least two loci), only one more species forms a distinct single-taxon cluster (
Supporting Information—Fig. S1
, diploid
C. germanica). We have little doubt that these tallies could be marginally improved with further
sampling of species, and of individuals within species, but not to a large extent.
Comparison of the plastid and nuclear genomes (
Wolfe et al. 1987
;
Clegg et al. 1994
), as well as studies of the molecular systematics of the Rosaceae in general and
the Maleae in particular (
Evans et al. 2000
;
Campbell et al. 2007
;
Potter et al. 2007
; cf.
Nikiforova et al. 2013
), all point to low levels of sequence variation in plastid loci especially in recently
evolved species. As a result, in
Crataegus a reasonable degree of phylogenetic resolution was only obtained by concatenating
sequence data from 14 plastid loci (Fig.
1; cf.
Lo and Donoghue 2012
), but this is not a solution acceptable from the current barcoding point of view.
The limits of ITS2 DNA barcode discrimination of Crataegus species
The intragenomic variability of the ITS2 region in
Crataegus has negative consequences for DNA barcoding. Several different copies of ITS2 (ribotypes)
are present in the genomes not only of polyploids, but also diploids (
Zarrei et al. 2014
), including recent hybrids (e.g.
C.×
cogswellii and
C.×
ninae-celottiae;
Love and Feigen 1978
;
Wells and Phipps 1989
;
Christensen et al. 2014
). Both indels and APS among ribotypes limit direct amplification of sequences from
genomic DNA. For example, high-quality sequences could not be obtained from the recent
hybrids
C.×
cogswellii and
C.×
ninae-celottiae. Several indels at different sites caused electropherogram displacements. Although
bidirectionally sequencing this short marker (mean sequence length = 314) contributed
to sequence recovery, the problem associated with identifying the paralogs still remained.
Cloning the ITS2 amplicons revealed the extent of hybridization in polyploid black-fruited
taxa of
Crataegus by demonstrating the co-occurrence in a single individual of ITS2 sequences from
sections
Coccineae and
Douglasia (
Zarrei et al. 2014
). This highlights the limited utility of ITS2 as a barcoding marker particularly
for allopolyploid taxa (
Hollingsworth et al. 2011)
.
The DNA barcoding protocol of direct sequencing of ITS2 is thus likely to lead to
incorrect species identifications by randomly amplifying only a single ribotype, especially
from a polyploid in which the number of paralogs is unknown. In the case of diploid
C. spathulata, all three individuals form a single, distinct cluster (clade C
1
,
Supporting Information—Fig. S2
; see also
C. brachyacantha, clade A
2
, and
C. germanica, clade A
1
). However, an equally distinct cluster (
Supporting Information—Fig. S2
, clade C
2
) comprises all three individuals of diploid
C. marshallii (series
Apiifoliae in section
Crataegus) plus
C. displar, a tetraploid in series
Lacrimatae (section
Coccineae). Another example is
C. pinnatifida (section
Crataegus); ITS2 sequences were obtained for two of the individuals of this species
[see
Supporting Information
—Table S1
]
. One of these (TRT099) forms a distinct cluster with
C. hupehensis (section
Hupehenses;
Supporting Information—Fig. S2
), while the other (TRT100) clusters with
C. wilsonii (section
Sanguineae;
Supporting Information—Fig. S2
). In fact, few of the clusters found on the NJ tree of the ITS2 sequences
[see
Supporting Information—
Fig. S2
]
contain only a single species, even though these clusters may comprise taxa belonging
to the same series. We can offer no explanation for the examples described above of
disparate taxa forming small, well-defined clades. On the other hand, the way in which
some tetraploid individuals from section
Douglasia are found interspersed among individuals from section
Coccineae in this tree
[see
Supporting Information—
Fig. S2
]
is undoubtedly related to the way the
Douglasia taxa concerned were found by
Zarrei et al. (2014)
to comprise individuals containing both
Coccineae and
Douglasia ITS2 sequences.
The problem associated with ITS2 as a barcode marker stems partly from the limited
sequence variation that this locus exhibits in
Crataegus (
Zarrei et al. 2014
), and partly from the incomplete homogenization of this locus by concerted evolution
(
Arnheim 1983
;
Zarrei et al. 2014
). The rate at which molecular forces homogenize ITS2 is evidently lower than that
at which hybridization and polyploidization have added ribotypes to an individual's
genome (in a context where gametophytic apomixis produces unreduced female gametes
which then undergo either parthenogenesis or fertilization;
Talent and Dickinson 2005
,
2007a
,
b)
. Similar results are seen with low-copy number nuclear genes like AT1
[see
Supporting Information
—Fig. S3
]
and PEPC (
Supporting Information—Fig. S4
and File S1). Neither of these issues has been considered in recent evaluations of ITS2 as a
suitable DNA barcode marker in medicinal plants (
Chen et al. 2010
) or in the Rosaceae (
Pang et al. 2011
). In fact,
Chen et al. (2010)
did not sequence
Crataegus ITS2 themselves, relying instead on sequences deposited in GenBank by E. Y. Y. Lo
(
Table S5
in
Chen et al. 2010)
.
Pang et al. (2011
, their
Table S1
), only sequenced ITS2 in three varieties of
C. pinnatifida and relied again almost exclusively on sequences deposited in GenBank by Lo (
Table S2
in
Pang et al. 2011)
. In both these studies, only the BLAST- and distance-based methods of evaluation
of
Ross et al. (2008)
were used. Both these studies implicitly assumed a one-to-one correspondence between
species and unique ITS2 sequences. Such a correspondence is necessary for the success
of the BLAST- and distance-based methods of evaluation (
Ross et al. 2008
). These methods will break down when there is a one-to-many relationship between
species and sequences, as is the case when not all of the possible ITS2 paralogs have
been included in the reference dataset, and any given paralog may occur in more than
one species. As we have shown elsewhere (
Zarrei et al. 2014
), the ITS sequences obtained in our earlier work (
Lo et al. 2007
,
2009
) are likely to underestimate the intragenomic diversity at this locus in many
Crataegus taxa.
Metabolomics data
Relationships inferred from molecular data (Fig.
1) are also implied in the resemblances obtained with the small sample studied here
for the flavonoid component of the metabolome (Fig.
2). More metabolomics data from a more representative sample are needed, however, before
we can tell whether these data track the relationships seen in
Crataegus molecular data or not, and whether chemical tests will be more useful than DNA barcode
loci in discriminating hawthorn species used in NHPs.
Limited utility of DNA barcode data for studies of Crataegus phylogeny
Sequence data from DNA barcode loci have proved useful in clarifying relationships
between recent
Crataegus hybrids and their parents where the latter were both diploids and from different
clades (
Christensen et al. 2014
; cf.
Lo et al. 2007
). For the variety of reasons described above, these data are nevertheless inadequate
for either barcoding purposes or for revealing evolutionary relationships across the
entire genus
[see
Supporting Information—
Figs S1 and S2
]
. Plastid loci can be chosen much more strategically if appreciable phylogenetic resolution
is sought from a limited number of loci (
Zarrei et al. 2014
). Alternatively, alignments of sequences of considerably more than just three plastid
loci can be analysed together in order to obtain a useful degree of phylogenetic resolution.
When this approach is taken (Fig.
1), the results robustly corroborate earlier work on the same sample (
Zarrei et al. 2014
).
Comparison can also be made between our results and those of
Lo and Donoghue (2012
; a study of intergeneric relationships in the Maleae) as they relate to
Crataegus. Their Fig. 1 is a tree based on ITS (cloned only when direct sequencing gave ambiguous
nucleotides) plus the same 11 plastid loci studied here in addition to the barcoding
loci
rbcL,
matK and
psbA
-trnH, for a larger sample of hawthorn species than we have used (7 of the 47 Crataegus
accessions, and 20 of the 33 species in
Supporting Information—Table S2
are shared with the Lo and Donoghue study). Even after Lo and Donoghue removed the
two genera responsible for a lack of congruence between their ITS and plastid data,
their tree based on the combined datasets shows support values that are marginally
lower than those obtained here, with just 14 plastid loci, for branches A, B, C and
E (Fig.
1). In both their study and ours, it is noteworthy that
C. series
Cerrones (clade F, Fig.
1) is sister to clade D, comprising both East Asian
C. section
Sanguineae (clades G
1
and G
2
, Fig.
1) and North American
C. series
Douglasianae (clade H), suggesting that the origin of section
Sanguineae involved an east to west trans-Beringian migration, from western North America into
eastern Asia. These results also warrant possibly recognizing the
Cerrones as a section, that is, at the same taxonomic rank as sections
Douglasia and
Sanguineae (Fig.
1)
[see
Supporting Information—
Table S1
]
.
Limited utility of DNA barcode data for Crataegus NHP development
Various authors have pointed out that DNA barcoding will not be useful in particular
plant groups.
Spooner (2009)
examined the utility of barcoding in wild potatoes and concluded that plastid loci
may lack the necessary polymorphism, while ITS may exhibit too much intraspecific
variation, much as we have seen here.
Hollingsworth et al. (2011)
list factors that will work against barcoding success: breeding system, hybridization,
polyploidy, long generation times (or reduced mutation rates), narrow taxon concepts,
species history and seed dispersal. Like many other genera in the Rosaceae,
Crataegus is a woody perennial that exhibits a nexus of frequent hybridization, production
and fertilization of unreduced gametes, hence polyploidy and accompanying shifts to
self compatibility (
Dickinson et al. 2007
;
Hojsgaard et al. 2014
;
Zarrei et al. 2014
). Arguably as a result of the patterns of morphological variation associated with
frequent apomixis and selfing (
Dickinson and Phipps 1985
;
Dickinson 1986
; cf.
Lo et al. 2010
), the (morphological) species concepts used in
Crataegus have been quite narrow, and in many cases do not likely reflect a high degree of
genetic differentiation. Concerning species history,
Hollingsworth et al. (2011)
refer to the effects of recent, rapid radiation on the one hand, and on the other
hand, to the maintenance of genetic polymorphisms in large populations, as also contributing
to the failure of DNA barcoding within a group. In the case of
Crataegus, it seems likely that many hybridization and polyploidization events have been relatively
recent, post-Pleistocene (<12 000 years) in any case, and possibly just in the last
millennium, as a consequence of First Nation and then European land-clearing activities
(
Marie-Victorin 1938
;
Dickinson et al. 2008
).
In fact, the morphology visible in hawthorn flowering and fruiting voucher specimens
is adequate for identification of most western North American species (
Dickinson 2012
) because, being long-lived woody perennials, wild hawthorns are readily marked and
vouchered at both seasons for comparison (
Hildreth et al. 2007
). It is also significant that in this geographic area there are only a limited number
of common species, almost all of which have now been included in flow cytometric surveys
of ploidy level and breeding system (
Supporting Information—Tables S1 and S2
;
Talent and Dickinson 2005
; Talent unpubl. data). In contrast, the
Crataegus flora of eastern North America is much richer, and is less well represented in molecular
phylogenetic studies (
Lo et al. 2009
;
Zarrei et al. 2014
). As a consequence, only a few groups can be considered even moderately well-characterized
[e.g. series
Aestivales and
Brevispinae, and the North American series assigned to section
Crataegus by
Phipps (2015)
]. More data are available from flow cytometry, and these have informed regional studies
(
Lance 2014
), but coverage is not yet complete. Fortunately, a comprehensive floristic treatment
of North American
Crataegus, complete with extensive synonymies, is available now as a part of the
Flora North America project (
Phipps 2015
). By providing testable taxonomic hypotheses, this treatment should stimulate the
collection and analysis of new data with which to make sense of the taxonomic complexity
that has been the hallmark of eastern North American hawthorns for over 100 years.
Production of hawthorn NHPs that employ native North American
Crataegus species as raw materials thus should not be impeded by an inability to employ DNA
barcoding to authenticate source taxa. Data on the predominant agamospermy of polyploid
Crataegus (all western species except for two;
Talent and Dickinson 2007a
,
b
) suggest that orchards raised from seeds or developed by grafting from previously
identified and vouchered genotypes can be harvested over multiple years, thus minimizing
the need for raw material authentication. Limited trials in an animal model of human
metabolic syndrome of hawthorn preparations from native
C. chrysocarpa fruit and BC-grown
C. monogyna leaves have shown significant improvements over untreated controls (F. Borthwick
et al., unpubl. data—presented in part as
Dickinson et al. 2014
). In addition to information on the taxonomy and phylogeny of hawthorns, information
on hawthorn chemistry, analytical methods and the validation of those methods are
increasingly available (
Kirakosyan et al. 2005
;
Edwards et al. 2012
). Discovery of metabolomic variation between hawthorn species suggests the possibility
that different therapeutic outcomes may be obtained when North American NHPs are administered
rather than the more ubiquitous hawthorn NHPs originating from European species.
Conclusions
We have examined the utility of DNA barcoding in a sample of 355 accessions representing
93 mostly species-level taxa from all major clades known to date, in a moderately
large plant genus,
Crataegus. Our sequence data and voucher information (including specimen images) represent
well-studied authoritatively identified individuals and are publicly available on
the BOLD website (dx.doi.org/10.5883/DS-NAMCRAT; sequence data also on GenBank,
Supporting Information—Tables S1–S4
) where they can be consulted, downloaded and reanalysed. The preliminary results
from the small metabolomics dataset studied here show the promise of NMR chemotaxonomic
data for studies of
Crataegus in relation to variation in therapeutic applications or NHP raw material authentication.
Our analyses of these sequence data from three plastid loci and ITS2 generally failed
to recover either the cladistic structure or the morphology-based infrageneric classification
of
Crataegus. We attribute this result to the lack of variation within Rosaceae tribe Maleae in
the plastid loci chosen as barcodes. The use of biparentally inherited ITS2 as a DNA
barcode is confounded by the frequency of allopolyploidy in
Crataegus combined with incomplete homogenization of this locus by concerted evolution. Incomplete
concerted evolution of this kind leading to the presence of multiple gene copies is
also common in the human genome (
Zarrei et al. 2015
).
In
Crataegus, resolution of species or of groups of closely related species, depends on having
more phylogenetically informative sites than can be provided by a small number of
plastid loci. Relatively well-resolved phylogenetic analyses required concatenated
sequences from a total of 14 plastid loci (Fig.
1). High-resolution phylogenetic analyses based on the nuclear genome will require
data from very low-copy number loci, the paralogs of which are readily identifiable.
Since phenolic compounds, widely purported to be beneficial in cardiovascular health,
vary in composition between species, there is considerable potential for using this
chemical information to choose an optimal species for NHP formulation. However, development
of hawthorn NHPs using North American species will require a taxonomy bolstered by
molecular data that are interpretable in the field using morphological characters.
This is now largely available for western North America, but remains a challenge in
the much more complex
Crataegus flora of eastern North America.
Accession Numbers
See
Supporting Information—Tables S1–S4
for GenBank accession numbers for the DNA sequences studied here.
Sources of Funding
We gratefully acknowledge the
Canada Foundation for Innovation
and the
Ontario Research Fund
for supporting the Canadensys infrastructure that enabled TRT to database, image
and curate voucher specimens for this project. Part of the laboratory work for this
project was undertaken at the Canadian Centre of DNA Barcoding at Guelph where DNA
barcoding was funded by the Government of Canada through Genome Canada and the
Ontario Genomics Institute
(
2008-OGI-ICI-03
). Fieldwork, and labwork in Toronto and Kelowna, were supported by a
Natural Sciences and Engineering Research Council of Canada Strategic Research Project
grant
, ‘Hawthorn as a new Canadian agroforestry crop for functional foods and nutraceuticals,’
STPGP 381073-09 to T.A.D., S.S., P.R.S. and Spencer D. Proctor, who is a co-PI on
the Strategic Research Project grant, but was not involved in the research that resulted
in this manuscript. The generous support of the Louise Hawley Stone Charitable Trust
enabled the Royal Ontario Museum Green Plant Herbarium to accept the
University of Western Ontario's
gift of the J.B. Phipps Hawthorn Research Collection. Additional support from the
ROM Reproductions, Acquisitions, and Research Fund
and the
Department of Natural History
, as well as from the Department of Ecology and Evolutionary Biology at the
University of Toronto
is also gratefully acknowledged.
Contributions by the Authors
M.Z. designed the initial sampling, and carried out the sequencing and data analyses
represented in Fig.
1 and
Supporting Information Figs S1–S4
. N.T. carried out most of the flow cytometric analyses and curates these data. M.K.
sampled additional individuals and carried out all of the DNA barcode sequencing.
J. Lee took part in fieldwork and record-keeping for the project. J. Lund and P.R.S.
collected and analysed the metabolomics data used here. S.S. and T.A.D. advised on
sampling and data analysis. The manuscript was prepared by M.Z. and T.A.D., based
on contributions from, and revisions by, all of the authors.
Conflict of Interest Statement
J. Lee is on the board of directors of the Naturally Grown Herb & Spice Producers
Cooperative (HerbPro), and chairs their value added committee that is focussed on
development of hawthorn-based products.
Supporting Information
The following additional information is available in the online version of this article
–
Table S1. Voucher information and GenBank accession numbers for the three plastid DNA barcode
loci, and nrITS2 amplified directly from genomic DNA as a DNA barcode locus, used
in the current study (
Supporting Information—Figs S1 and S2
; BOLD Dataset NAMCRAT; further details of the barcode sequences are available at
dx.doi.org/10.5883/DS-NAMCRAT).
Table S2. Phylogenetic analysis of 14
Crataegus plastid DNA loci (Fig.
1). Voucher information and GenBank accession numbers for 11 supplementary plastid
DNA loci and the three plastid DNA barcode loci (
Supporting Information—Table S1
; further details of the barcode sequences are available at dx.doi.org/10.5883/DS-NAMCRAT).
Table S3.
Crataegus voucher information and GenBank accession numbers for the AT1 region used in the
current study.
Table S4.
Crataegus voucher information and GenBank accession numbers for the PEPC region used in the
current study.
Table S5. Models of nucleotide evolution in
Crataegus selected using the AIC for analyses of plastid (Fig.
1;
Supporting Information—Table S2
) and nuclear
[see
Supporting Information
—Figs S3 and S4
;
Supporting Information—Tables S3 and S4
] markers.
Table S6. Comparison of
Crataegus sequence variation between different markers utilized for the phylogenetic analyses
(Fig.
1;
Supporting Information—Figs S3 and S4
).
File S1; AT1 and PEPC Supporting Information. Low-copy nuclear gene methods, data analyses and results.
Figure S1. Neighbour-Joining tree for three concatenated
Crataegus plastid DNA barcode markers (
matK,
rbcLa and
psbA
-trnH). The numbers preceding the taxonomic information are
Crataegus sample identifiers (
Supporting Information—Table S1
; BOLD Dataset NAMCRAT). Ploidy level for the vouchered individual is given where
known (in parentheses, if voucher information unavailable, but species has a single
characteristic ploidy level). Scale for branch lengths in substitutions per site.
Leaves are coloured to show
Crataegus infrageneric classification
[see
Supporting Information—Table S1
], with labelling of clades following that in
Lo et al. (2007)
: blue rectangles, section
Mespilus (clade A
1
); blue text, section
Brevispinae (clade A
2
); red rectangles, section
Crataegus (clade B); orange text, sections
Coccineae and
Macracanthae (clade D); purple rectangles, series
Cerrones (clade E
1
); purple text, series
Douglasianae (clade E
2
) and green rectangles, section
Sanguineae (clade E
3
). Clade C as described earlier (
Lo et al. 2007
), and in the text.
Figure S2. Neighbour-Joining tree for ITS2 amplified directly from
Crataegus genomic DNA as a DNA barcode locus. The numbers preceding the taxonomic information
are
Crataegus sample identifiers (
Supporting Information—Table S1
; BOLD Dataset NAMCRAT). Ploidy level for the vouchered individual is given where
known (in parentheses, if voucher information unavailable, but species has a single
characteristic ploidy level). This figure includes sequences (filled diamonds) from
four accessions of
C. douglasii (TRT157, 175, 177 and 184;
Supporting Information—Table S1
), two of
C. orbicularis (MKTRT587, 588;
Supporting Information—Table S1
) and one of
C. sheila-phippsiae (MKTRT617;
Supporting Information—Table S1
) with sequences that were not barcode compliant, but nevertheless could be fitted
into an alignment. Scale for branch lengths in substitutions per site. Leaves are
coloured, and clades are labelled, as described for
Supporting Information—Fig. S1
.
Figure S3. The Bayesian phylogram for AT1, the PPR homologue of the AT1G09680 gene in
Arabidopsis. Branch support values are indicated as PP above branches, and bootstrap (BS) values
below branches. Branches with PP <0.5 are shown as polytomies. BS values <50 % are
not shown. Asterisks indicate branches retained in the strict consensus of 243470
trees. Scale for branch lengths in substitutions per site. The numbers preceding the
taxonomic information are
Crataegus sample identifiers
[see
Supporting Information—
Table S3
]
and clone numbers (separated by a hyphen). Clades a–d are described in the
Supporting Information Text
—File S1. Leaves are coloured as described for
Supporting Information—Fig. S1
.
Figure S4. The Bayesian phylogram for PEPC sequences. Branch support values are indicated as
PP above branches. Branches with PP <0.5 are shown as polytomies (PP values <0.7 are
not shown). Asterisks indicate branches retained in the strict consensus of 102 420
trees. Leaves are coloured as in
Supporting Information—Fig. S3
. Scale for branch lengths in substitutions per site. S, short paralog; L, long paralog.
The numbers preceding the taxonomic information are
Crataegus sample identifiers
[see
Supporting Information—
Table S4
]
and clone numbers (separated by hyphen). Clade a is described in the
Supporting Information Text—
File S1. Leaves are coloured as described for
Supporting Information—Fig. S1
.
Acknowledgements
We thank A. Anderson, the late K. I. Christensen, G. Cooley, J. M. Coughlan, C. Delong,
A. A. Dönmez, W. Earle, M. Graham, J. Herrick, B. Jensen, R. and M. Johnson, R. W.
Lance, T. Lewis, E. Y. Y. Lo, R. M. Love, H. Massicotte and L. Tackaberry, H. Moothoo,
S. Nguyen, R. and J. Pojar, G. Powell, B. Rogers, T. Romankova, C. Shaw, D. Smith,
T. Steen, R. Thompson, P. Zika and others mentioned in
Supporting Information—Tables S1–S4
for assistance with plant collecting. The following organizations kindly provided
us with access to plant material growing under their care, or on their property: the
Arkansas Natural Heritage Commission; the Arnold Arboretum of Harvard University;
the Deer Creek Center of the Siskiyou Field Institute; the Jardin Botanique de Montréal,
the Morton Arboretum; the Nature Conservancy; Point Reyes National Seashore and the
University of California Botanical Garden, Berkeley. We are indebted to J. M. Coughlan
for sharing her flow cytometry data with us. James B. Phipps kindly identified several
of our 2007 and earlier collections. For assistance in the herbarium, managing the
voucher material, we are indebted to K. Buck, R. Martin and C. Ng. Dan Potter and
an anonymous reviewer provided many suggestions that greatly improved portions of
the text. This work could not have been completed without the help of A. Rodrigues,
T. Braukmann, K. Choffe and O. Haddrath. Paula Brown (British Columbia Institute of
Technology) was instrumental in helping us obtain the NSERC Strategic Research Project
grant. Her lab at BCIT was responsible for storing and curating collections of fruits
and leaves made for this project.
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Before Change
RunStatus.to_string(RunStatus.KILLED)
]
previous_run_status = [
RunStatus.to_string(RunStatus.SCHEDULED),
RunStatus.to_string(RunStatus.FAILED),
RunStatus.to_string(RunStatus.FINISHED),
RunStatus.to_string(RunStatus.RUNNING)
]
def _has_check_constraints():
inspector = Inspector(context.get_bind().engine)
After Change
// the collection of CHECK constraints that should be preserved when performing the migration.
// The "status" constraint is excluded from this set because it is explicitly modified
// within the migration"s `upgrade()` routine.
check_constraint_table_args = [
CheckConstraint(SqlRun.source_type.in_(SourceTypes), name="source_type"),
CheckConstraint(SqlRun.lifecycle_stage.in_(LifecycleStage.view_type_to_stages(ViewType.ALL)),
name="runs_lifecycle_stage"),
]
def upgrade():
with op.batch_alter_table("runs", table_args=check_constraint_table_args) as batch_op:


The Walk
The walk from Monterosso to Riomaggiore will take you approximately two hours, give or take an hour depending on the weather conditions and your physical shape.
The walk from Monterosso to Riomaggiore will take you approximately two hours, give or take an hour depending on the weather conditions and your physical shape.
Cinque Terre comprises five villages: Monterosso, Vernazza, Corniglia, Manarola, and Riomaggiore.
On the northwest cost of the Italian Riviera, north of the city La Spezia.
The Walk is free!