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Botany

DNA barcoding of a complex , L. () reveals lack of -level resolution

Journal: Botany

Manuscript ID cjb-2019-0018.R2

Manuscript Type: Article

Date Submitted by the 10-May-2019 Author:

Complete List of Authors: Aygoren Uluer, Deniz; Ahi Evran Universitesi, Cicekdagi Vocational College, Department of and Animal Production; Alshamrani, Rahma; King Abdulaziz University, Department of Biological Sciences Draft Keyword: Aesculus, DNA barcoding, ITS/ITS2, matK, phylogeny

Is the invited manuscript for consideration in a Special Not applicable (regular submission) Issue? :

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DNA barcoding of a complex genus, Aesculus L. (Sapindaceae) reveals lack of species-level

resolution

Deniz Aygoren Uluer1,3, Rahma Alshamrani 2

1 Ahi Evran University, Cicekdagi Vocational College, Department of Plant and Animal Production,

Boyalık Mahallesi, Stadyum Caddesi, Turan Sok. No:18 40700 Cicekdagi, Kirşehir, Turkey.

[email protected]

2 King Abdulaziz University, Department of Biological Sciences, PO Box 80206, 21589, Jeddah, Saudi Arabia, email: [email protected]. Draft

3Author for correspondence: Deniz Aygoren Uluer, Ahi Evran University, Cicekdagi Vocational

College, Department of Plant and Animal Production, Boyalık Mahallesi, Stadyum Caddesi, Turan

Sok. No:18 40700 Cicekdagi, Kirşehir, Turkey, email: [email protected], Work phone:

+903862805500, Fax: +903862805528.

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Abstract

Aesculus L. is a small genus of horticulturally important and , comprising 13-19 species.

Frequent hybridization among species, particularly in cultivation, has contributed to taxonomic confusion and difficulties in identification of . In this study, we evaluated three widely employed plant DNA barcode loci, matK, and the entire ITS region (ITS1+5.8S+ITS2) as well as subunit ITS2 for 50 individuals representing 13 species of Aesculus, excluding only A. wangii (=A. assamica). In contrast to the plastid matK region, both the ITS and ITS2 loci displayed low levels of species discrimination, especially in our “first hit” BLASTn searches. We also presented the phylogeny of Aesculus based on matK and the entire ITS region, with additional matK and ITS sequences from GenBank. Our results show that Aesculus chinensis, A. flava, A. glabra, A. pavia and

A. sylvatica are probably not monophyletic.Draft Furthermore, with the widest taxon coverage until now, the current study highlights the importance of sampling multiple individuals, not only for DNA barcoding, but also for phylogenetic studies.

Keywords: Aesculus, DNA barcoding, ITS/ITS2, matK, phylogeny

Introduction

Aesculus L. (Sapindaceae) is a small, but taxonomically difficult genus comprising 13-19 species of horticulturally important shrubs and trees. The genus is noticed with its palmately compound , large and showy and poisonous (buckeyes or horse- chesnuts) (Turland and Xia 2005; Zhang et al. 2010). Aesculus is distributed in North America, south- eastern Europe and Asia (Turland and Xia 2005). Frequent hybridization among species, particularly in cultivation, has contributed to taxonomic confusion and difficulties in identification of plants.

Aesculus is traditionally divided into five sections: Aesculus, Calothyrsus, Macrothyrsus, Parryana and

Pavia, according to colour, petals, bud viscidity, exocarp morphology and geographic

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distribution (Hardin 1957; Hardin 1960). However, previous studies have shown that, these five

traditionally accepted sections of Aesculus as well as species boundaries are problematic; the

phylogenetic relationships of these sections change from one study to another, and recognition of

some recently suggested species such as, A. assamica Griff. (=A. wangii Hu) and A. tsiangii Hu&Wang

are still doubtful (Hardin 1957; Hardin 1960; Turland and Xia 2005; Xiang et al. 1998; Forest et al.

2001; Harris et al. 2009; Harris et al. 2016).

DNA barcoding is a tool for quick identification of organisms by the use of a short gene sequence

from short standardized gene region(s) and comparison with a barcode library (Hebert et al. 2003a,

b). DNA barcoding, as a fast and inexpensive method, can be used where morphological

identification is not possible, such as in the food industry, herbal medicines, conservation, forensic

investigations, biodiversity inventories, animal diet, sterile material, and seedlings (Cowan et

al. 2006; Taberlet et al. 2006; Barcaccia etDraft al. 2015; Larranaga and Hormaza 2015; Ivanova et al.

2016). It may also help to identify new species in (Hebert et al. 2004; Hajibabae et al.

2007).

In this study, we explored the utility of DNA barcoding of Aesculus, since identification of Aesculus

species heavily depends on floral and fruit characters, in which DNA barcoding could permit

identification of these sterile materials. Therefore, we evaluated the use of one chloroplast coding

region, namely matK, nuclear internal transcribed spacer (ITS) region and subunit ITS2 singly and in

combination in 50 individuals of 13 Aesculus species.

Intron Group II maturase matK, is one of the most rapidly evolving coding regions in plants (CBOL

2009), and many studies have reported its successful use (e.g., Clerc-Blain et al. 2010; Seberg and

Petersen 2009) from family to even species level (Dong et al. 2012). However, not having universal

primers, reported PCR problems and less discrimination power in some groups are the most

important drawbacks of this region (Chase et al. 2007; Newmaster et al. 2008; CBOL 2009; Barcaccia

et al. 2015).

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In plants, the ITS region has been used in plant systematic studies frequently, especially in low-level taxonomic studies (Baldwin 1992; Baldwin et al. 1995; Sonnante et al. 2003). The success of this locus as a DNA barcode has also been reported by many studies (e.g., Ellison et al. 2006; Clement and Donoghue 2012) due to its ease of amplification and rapidly evolving nature (Baldwin et al.

1995; Baker et al. 2000; Kress and Erickson 2007; Huang et al. 2015). However, gene conversions, concerted evolution, requirement of different PCR conditions and additives, fungal contamination, cloning requirement in some cases and not being amplifiable with universal primers are some reasons that limit the use of this nuclear region as a DNA barcode (Alvarez and Wendel 2003;

Wendel et al. 1995; Kress et al. 2005; Cowan et al. 2006; Chase et al. 2007). Therefore, CBOL (2009) regarded this region as a supplementary barcode. While the multiple copy problem still exists (Bailey et al. 2003), ITS2, on the other hand, as one of the two very variable internal transcribed spacers of the ITS region, has been reported as a novelDraft barcode across land plants by many studies, with a high level of discrimination rate with universal primers and ease of amplification compared to ITS, even with herbarium specimens or in challenging environments (Chen et al. 2010; Yao et al. 2010; Li et al.

2011; Xu et al. 2015; Braukmann et al. 2017; Ramalho et al. 2018). We evaluated both the entire ITS region (ITS1+5.8S+ITS2) and ITS2 alone as a DNA barcode for Aesculus, due to the ease of amplification and sequencing of the ITS2 region with available universal primers, the cases where obtaining the entire ITS locus is problematic (Li et al. 2011).

Over the past years, several studies have assessed the phylogenetic relationships of Aesculus using morphological characters and markers. However, none of these studies have yielded a species-rich phylogeny of Aesculus, which may indicate monophyly problems of taxonomic groups. Therefore, the second aim of the current paper is to present the phylogeny of Aesculus based on these two

DNA regions, namely matK and ITS.

Materials and methods

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Taxon sampling, DNA extraction, amplification and sequencing

Fieldwork in this study was conducted from 2012 to 2014. Specimens representing Aesculus were

collected from the University of Reading Whiteknights campus, as well as from the Royal

Horticultural Society Garden at Wisley. All the trees were previously identified in the field using

morphological characters (i.e. available reproductive or vegetative characters) based on Sell and

Murrell’s (2009) and Stace’s (2010) identification keys. Furthermore, we compared our specimens

with the dry specimens at the Royal Botanic Gardens, Kew Herbarium and Royal Horticultural Society

Garden at Wisley Herbarium. All corresponding voucher samples are curated in the King Abdulaziz

University Herbarium.

The genomic DNA was extracted from freshDraft material using the DNeasy Plant Mini Kit (Qiagen) following the manufacturer's instructions and were held at the University of Reading herbarium.

Except for Aesculus assamica (=A. wangii), all species of Aesculus were included to the current study.

Polymerase chain reactions were performed in 25 µL reaction volumes, with 12,5 µL of Biomix

(Bioline, 2x), 2 µL bovine serum albumin (Sigma-Aldrich, 10 mg/mL), 0.875 µL of each primer

(20mM), and 1 µL of template DNA and made up to 25 µL with distilled water. For the nuclear

regions, the DNA templates were diluted to 1:50. For reactions amplifying ITS2, if the first PCR

attempt was unsuccessful, 1 µL of dimethyl sulfoxide (DMSO) was added to reduce the effect of

secondary structures and increase efficiency of PCR. We followed Harris et al. (2009) and used the

primers which are shown in Table 1. The PCR profiles for the matK and the ITS (ITS 1, ITS2 and the

5.8s ribosomal gene) regions were also shown in Table 1. All amplifications were performed on a

GeneAmp PCR system 2700 (Applied Biosystems). Products were sent to Source BioScience

(Nottingham, UK) for purification and sequencing.

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The matK data matrix comprised 46 sequences, the entire ITS and ITS2 matrices contained 44 sequences and ITS+matK and ITS2+matK matrices contained 50 samples. The National Center for

Biotechnology Information (NCBI/GenBank) accession numbers for these newly produced DNA sequences are provided in Supplementary data1.

Sequence editing, alignment and phylogenetic analyses

Sequences were assembled and aligned using the Geneious alignment option in Geneious Pro 4.8.4

(Kearse et al. 2012) with the automatic pairwise alignment tool and subsequently edited manually.

Equivocal base calling at the beginning and end of assembled complementary strands were trimmed. All indels were scored as missing data. WeDraft also extracted the ITS2 region from the entire ITS alignment to see whether this 195 bp region is as useful as the entire ITS region.

The substitution models for each of the individual genes were estimated using jModelTest 2.1.10

(Guindon and Gascuel 2003; Darriba et al. 2012).

ML analyses were performed using RAxML version 7.0.4 as implemented on http://embnet.vital- it.ch/raxml-bb/web-server (Stamatakis et al. 2008). The GTRGAMMA model was applied to each partition individually and default maximum likelihood search options were selected with 100 bootstrap replicates. The best scoring trees with bootstrap values were saved. We used a cutoff of

50% to define support for “successful” resolution of monophyletic species.

For the phylogeny analyses, 40 each of matK, entire ITS and ITS2 sequences of Aesculus and outgroups were obtained from GenBank; accession numbers for these previously published DNA

1 Supplementary data are available with the article through the journal Web site at http://nrcresearchpress.com/doi/suppl/10.1139/cjb- 2019-0018.

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sequences are also provided in Supplementary data. In some cases, ITS1, 5.8S and ITS2 sequences

were downloaded separately and concatenated. GenBank accession numbers for these sequences

are also provided in Supplementary data. To reduce the problems associated with LBA (Felsenstein

1978) by breaking long branches between the ingroup and outgroup, we chose our 10 outgroup taxa

to root the ingroup representing the remaining four genera of the subfamily,

other than Aesculus. Other than outgroup sequences, we used the same sample (i.e., same voucher

numbered sample) for our matK, ITS and ITS2 phylogenetic analyses. We also sequenced matK and

ITS loci for hippocastanum Peyr. and deposited them in Genbank.

BLAST analysis Draft Since similarity-based approaches such as BLASTn are the most commonly used for DNA barcode

data analysis (Huang et al. 2015), all barcodes were tested singly and in combination by running a

BLASTn search in the GenBank global database to evaluate the taxonomic resolution. We used a

cutoff of 98% species identity for the BLASTn similarity approach. Additionally, we ‘BLASTed’ our

sequences again to see whether the first hit on the BLASTn results represented the correct species

names (i.e., unambiguous identification) (Vences et al. 2005; Brock et al. 2009).

Results

DNA barcoding of Aesculus

In total, we obtained 46 matK and 44 ITS sequences from tissue samples of 50 specimens,

representing 11 and 12 species, respectively (Table 2). While the outgroup-excluded alignment of

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matK was 1,726 bp long, outgroup-excluded alignments of ITS and ITS2 were 605 and 195 bp, respectively. Of these, 94 characters were variable for both matK and ITS, while 36 were variable for the short ITS2 region. In terms of parsimony-informative characters, compared to the region’s length, ITS2 showed the highest percentage (12.8%), followed by ITS (11.7%) and matK (2.6%), revealing matK to have the lowest phylogenetic informativeness despite its length (1,726 bp).

However, between matK and ITS, matK showed the highest PCR and sequencing success (Table 2).

On the other hand, the entire ITS+matK had 187 variable characters, of which 115 were parsimony- informative. For the ITS2+matK region, among 132 total variable characters, 71 were parsimony- informative. All these alignment details for all datasets are summarized in Table 2.

The length of ITS is well suited for DNA barcoding (605 bp). In terms of primer pairs used, ITS required fewer primer pairs (i.e., three primerDraft pairs) compared to the matK region (i.e., four primer pairs). None of the loci could be successfully amplified for all taxa; while PCR and sequencing success for matK was 92%, it was 88% for the ITS region (Please note that we were able to sequence all PCR products successfully).

BLAST delivered a very high species resolution for matK, ITS2 and matK+ITS2 (98% to 100%) (Table

3). However, of the single barcodes (ITS, ITS2 and matK), most of our Aesculus ITS sequences were misidentified, even if the “discontinuous megablast” and “blastn” options were used instead of the

“megablast” option. Therefore, we did not include our ITS BLASTn search results in Table 3. On the other hand, ITS2 had a slightly better discriminatory power compared to matK. Combining matK with

ITS2 did not improve the BLASTn search results in general (Table 3). In contrast to the high species resolution percentages for matK, ITS2 and matK+ITS2, when we BLASTed our ITS2 sequences, the

“first hit” referred as the unambiguous identification for only four of the Aesculus species (A. californica, A. indica, A. parryi and A. parviflora) (Table 3). There were five species for the matK region (A. californica, A. indica, A. parryi, A. parviflora and A. tsiangii). Furthermore, for four

Aesculus species (A. turbinata, A. pavia, most of A. sylvatica and some of A. flava), we correctly

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identified the species almost always in the “first hit”. Combining matK with ITS2 did not improve the

the “first hit” BLASTn search results.

Our ML results have shown that, while there was no difference between matK, ITS and ITS2 in terms

of retrieving monophyletic species (five for each region), genus Aesculus was monophyletic only in

the matK analysis (Table 3). However, combining ITS and ITS2 with matK definitely resulted in better

resolution, with eight monophyletic species for both regions.

Relationships within Aesculus

In this section, the results of the ITS2 analysesDraft are excluded. Only bootstrap support values above 50% are discussed.

The outgroup-included alignment of matK was 1,726 bp long; alignments of ITS and ITS2 were 657

and 209 bp, respectively. While Aesculus was found to be monophyletic in most of the analyses (77-

88%), three Billia Peyr. samples plus Handeliodendron bodinieri (H. Lév.) Rehder were grouped

within Aesculus, in the ITS . In general, among 13 Aesculus species, only A. californica Nutt. (84

to 100%), A. parviflora Walter (95 to 100%) and A. parryi A. Gray (100%) were found to be

monophyletic in all analyses (Table 4).

Species borders within section Pavia and the situation of A. californica and A. chinensis also seemed

to be problematic in all analyses (Figure 1, Table 3 and 4). However, there was noteworthy close

relationship between section Parryana and section Pavia (note that section Parryana was embedded

in the section Pavia in the matK tree). Section Macrothyrsus was monophyletic in all analyses.

Section Aesculus was monophyletic in ITS and matK+ITS analyses (Figure 1); however, one of the A.

chinensis samples was embedded in section Aesculus in the matK tree. Section Calothyrsus was not

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monophyletic in any of the analyses, because, either all A. californica samples or one of the A. chinensis samples were embedded in other sections.

Discussion

DNA barcoding of Aesculus

Identifying phylogenetically problematic and horticulturally important Aesculus species using short

DNA sequences would be remarkably practical, especially for sterile Aesculus samples. Indeed, the genus proved to be a challenging phylogeny and barcoding test case, due to the low levels of DNA sequence variation. Our data showed that morphological species borders do not correlate with the phylogeny of Aesculus, particularly withinDraft section Pavia. Ancient-rapid radiation of the genus, which involves short internal branches (Harris et al. 2009), frequent hybridization, reticulation and continuous gene flow, gene duplication, polyploidy, long generation times and possible polyphyletic taxa could be the reason (Yan et al. 2015; Zarrei et al. 2015).

Unfortunately, our DNA barcoding study showed that both ITS and ITS2 loci have advantages with respect to length (i.e., relatively short as a DNA barcode), being amplifiable with universal primers

(note that we did not test this for the ITS2 locus) and retrieving monophyletic species in our ML trees; neither the ITS nor ITS2 loci yielded unambiguous species discrimination in most of our

BLASTn “first hit” searches (Table 3). Furthermore, most of our Aesculus ITS sequences were misidentified in our BLASTn searches when we used a cutoff of 98% species identity. However, like

Harris et al. (2009), our ITS sequencing results did not show significant double peaks in chromatograms; this would not rule out the possibility of paralogous copies and/or pseudogenes due to gene duplication and incomplete concerted evolution (Álvarez and Wendel 2003; Pelser et al.

2010). Furthermore, when employing either ITS or ITS2 regions as a DNA barcode for Aesculus,

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extensive cloning of PCR products may be necessary, which is not a desired feature of a DNA

barcode. Further work is required in order to clarify this point. On the other hand, verified voucher

numbers and possible unreliable specimen identifications are one of the major drawbacks of not

only DNA barcoding (Kress and Erickson 2007; Deichmann et al. 2017) but also other botanical

studies (Eisenman et al. 2012; Culley 2013). Additionally, the amount of inaccurate identifications in

GenBank records could also be extremely high (e.g. Nilsson et al. 2006). Nevertheless, we certainly

believe that this was not the case for our study. First, after a detailed identification step using the

appropriate identification keys (Sell and Murrell 2009; Stace 2010), we compared our specimens

with several dry specimens deposited at the Royal Botanic Gardens, Kew and the Royal Horticultural

Society Garden at Wisley Herbariums. Second, almost all ITS sequences that we included in our study

were identified, sequenced and deposited to GenBank by Aesculus experts (i.e. Harris et al. 2009). Thus, we deduced that incorrect identificationDraft was not the cause for these mismatches. The rbcL+matK combination has been adopted as a standard DNA barcode for plants (CBOL 2009).

However, unsatisfactory results from closely related groups, especially woody plant groups, because

of their long generation times, have been reported (Clement and Donoghue 2012). From these

results, researchers concluded that standard DNA barcodes are not useful in every case, and

addition or substitution of other regions (e.g., ITS, ITS2, trnH-psbA) is necessary (e.g., Huang et al.

2015; Braukmann et al. 2017). In the case of Aesculus, our preliminary results have shown that

sequencing the rbcL coding region would be both time and money-consuming. However, in contrast

to having fewer parsimony-informative characters (2.6%) compared to ITS (11.7%) and ITS2 (12.8%),

and requiring more primer pairs compared to the ITS region, the matK region did well in both our

BLASTn and ML analyses (Table 3). In contrast to previous studies, which reported its problematic

performance in broad floristic experiments, the matK region also displayed the highest PCR and

sequencing success (92%), when compared to the ITS nuclear region (88%) (Tables 2 and 3).

Furthermore, the matK region was mostly successful in yielding the correct species identification,

other than for all A. glabra samples, almost all A. hippocastanum samples, some A. flava samples,

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one A. sylvatica sample and one A. turbinata sample (note that we could not sequence A. californica and A. parryi for this region) (Table 3). Interestingly, our “first hit” searches for A. flava for example, resulted in A. pavia, while our A. glabra searches resulted in either A. pavia or A. flava, in which the monophyly of the above-mentioned species was also problematic in our ML analyses. On the other hand, while combining matK with ITS or ITS2 clearly improved results in terms of phylogenetic analyses, it did not improve the results of BLASTn searches.

In summary, even our preliminary results (unpublished data) have shown that sequencing the rbcL coding region would be both time and money-consuming; nevertheless, we recommend using at least the matK region as a DNA barcode for Aesculus. In the case of Aesculus hybrids, however, adding ITS or ITS2 may be helpful, because compared to nuclear genes, chloroplast loci do not present many problems like multiple copyDraft and fungal contamination; yet using only chloroplast loci cannot help to detect the paternal parent (Kress et al. 2005; Cowan et al. 2006). Therefore, comparing the ITS/ITS2 phylogeny with the chloroplast phylogeny can identify Aesculus hybrids

(Sang et al. 1997). However, particular caution must still be exercised when working with hybrids

(note that we did not include any hybrids in the current study), because ITS can easily have paralogous sequences as a result of gene duplication and incomplete concerted evolution (Alvarez and Wendel 2003).

Phylogeny of Aesculus

Despite its popularity and horticultural importance with a complex history of hybridization ex situ, the taxonomy and systematics of Aesculus are confused. While we did not include any hybrids, our study is still the first attempt to reveal phylogenetic relationships within the genus Aesculus, with the widest taxon coverage to date. We were able to include most of the Aesculus species in our

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phylogenetic study (in total, 91 taxa in 13 species) except for A. assamica. Even though we recovered

all five sections of Aesculus, the taxonomy of the genus is still poorly resolved, even with the highly

informative matK and ITS regions and the wider taxon coverage that we employed. However,

whether this problem is caused by incomplete lineage sorting, frequent hybridization (Jakob and

Blattner 2006; Zarrei et al. 2015), low levels of genetic variation among Aesculus species or another

potential reason is still unkown, and indicates that further work is required.

On the other hand, increasing number of species sampling has clearly showed that many Aesculus

species are not monophyletic (e.g., A. chinensis, A. flava, A. glabra, A. pavia, A. sylvatica W. Bartram)

(Table 3 and Figure 1). Indeed, the results obtained by Harris et al. (2009) and Harris et al. (2016)

also support the notion that A. chinensis (including A. chinensis var. wilsonii (Rehder) Turland & N.H.Xia), A. glabra, A. pavia and A. sylvaticaDraft may not be monophyletic species. Our study has shown that monophyly of almost half of the species of Aesculus (i.e., A. chinensis, A. flava, A. glabra, A.

pavia, A. sylvatica) is doubtful; therefore, in contrast to sparsely sampled previous studies (Table 4),

a wide species sampling is clearly necessary, not only for DNA barcoding, but also for phylogenetic

studies (Clement and Donoghue 2012). Our results have also shown the following:

1) while sections Macrothyrsus, Parryana, Pavia and Aesculus are monophyletic, the monophyly of

section Calothyrsus is doubtful. Furthermore, the phylogenetic relationships inferred by previous

studies within five sections of Aesculus are still controversial, changing from one study to another

(e.g., Hardin 1957 and 1960; Xiang et al. 1998; Forest et al. 2001; Harris et al. 2009; Harris et al.

2016) (Table 4). Therefore, we believe that, there is an urgent need for further studies on the

placement of A. californica and the phylogenetic relationships within five sections of Aesculus.

2) Monophyly of species within section Pavia should be revised using wider species sampling. This is

because our phylogenetic analyses as well as our field trips have shown that the species borders

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among four taxa of section Pavia are not clear. For example, during our field trips, we observed A. flava samples with characteristics similar to A. sylvatica, such as plants with 18 mm petioles and +22 mm stamens. On the contrary, it is possible that frequent hybridization within these four species may indeed constitute a species complex (Chase et al. 2005). However, this needs more work to be confirmed.

3) The situation of A. chinensis should be revised using wider species sampling. Interestingly, while one A. chinensis sequence downloaded from GenBank (GenBank# AY724267.1) was grouped with A. hippocastanum samples in our matK tree, another A. chinensis (A. chinensis var. wilsonii, Alshamrani

103 (H)) was grouped within section Pavia in our ITS tree.

4) Finally, our ML analyses of ITS yielded mixedDraft results for the monophyly Aesculus; similar results were also reported by Buerki et al. (2010) and Harris et al. (2016). However, we believe that Aesculus is monophyletic, and this is also supported not only by previous studies (e.g., Harris et al. 2009;

Harris et al. 2016), but also morphological characters (e.g., Forest et al. 2001). Therefore, it only seems that species boundaries in Aesculus are especially difficult and further studies are definitely needed.

Conclusions

The current study is the first attempt to barcode genus Aesculus. Our BLASTn cutoff of 98% species identity, BLASTn first hit and ML analyses showed that matK is the most useful DNA barcode for

Aesculus. Second, our phylogenetic analyses with the largest taxon sampling to date have also shown that monophyly of many species of Aesculus is doubtful; therefore, further studies with a wide taxon coverage are definitely needed. We think that inclusion of more samples from non-

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monophyletic species of Aesculus is particularly necessary. On the contrary, we are confident that

the inclusion of more samples from already monophyletic taxa (e.g., A. californica) would not affect

the results. For some taxa, we were able to include only a few individuals (i.e., A. parryi, A. polyneura

Hu&Fang. and A. tsiangii) or no sequences at all (i.e., A. assamica) in our study; thus, we could not

properly assess their resolvability. Future studies should definitely include samples from these taxa.

Alternatively, employing more informative (i.e., variable) nuclear or chloroplast regions or whole

chloroplast genomes would yield better resolution for the taxonomically complex genus Aesculus.

Acknowledgments

We are grateful to the anonymous reviewerDraft for helpful comments.

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Table 1: PCR profiles and primers used for amplifying and sequencing.

Name of Region Primer sequence Source the primer 1F ACT GTA TCG CAC TAT GTA TCA Modliszewski et al. 2006; Harris et al. 2009 300F GGG ATT TGC AGT CAT TGT GG Xiang Lab (unpub.); Harris et al. 2009 500R TGG ACR GGR TRG GGT ATT AG Xiang Lab (unpub.); Harris et al. 2009 3F AAG ATG CCT CTT CTT TGC AT Modliszewski et al. 2006; Harris et al. 2009 matK 799F TTC TGG ACT CCT TCT TGA GCA Harris et al. 2009 1288F TAT TAT CGA CCG GTT TGT GC Harris et al. 2009 1416R CGC GCA CAG TAC TTT TGT GT Harris et al. 2009 1R GAA CTA GTC GGA TGG AGT AG Modliszewski et al. 2006; Harris et al. 2009 17SE ACG AAT TCA TGG TCC GGT GAA GTG TTCG Sun et al. 1995 ITS5f GGA AGG AGA AGT CGT AAC AAG G Xiang et al. 1998; Harris et al. 2009 ITS2r GCT GCG TTC TTC ATC GAT GC Xiang et al. 1998; Harris et al. 2009 ITS ITS3f GCA TCG ATG AAG AAC GCA GC Xiang et al. 1998; Harris et al. 2009 ITS4r TCC TCC GCT TAT TGA TAT GC Xiang et al. 1998; Harris et al. 2009 26SE TAG AAT TCC CCG GTT CGC TCG CCG TTAC Sun et al. 1995 Region PCR profile matK ITS Initial denaturation 94 °C for 2 minutes Draft 94 °C for 2 minutes denaturationDenaturation 94 °C for 30 seconds 94 °C for 1 minute Annealing 52 °C for 1 minute 48 °C for 1 minute Extension 72 °C for 1.5 minutes 72 °C for 1.5 minutes Final extension 72 °C for 7 minutes 72 °C for 7 minutes Number of cycles 35 cycles 35 cycles

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Table 2: PCR amplification and sequencing success, alignment length or ingroup taxa, total variable characters, parsimony-informative characters, number of total individuals and number of species sampled for 50 Aesculus samples in total for matK, ITS, ITS2, ITS+matK and ITS2+matK.

Region PCR amplification Aligned ingroup Total variable Parsimony- Total Species and sequencing length (bp) characters informative individuals sampled success (50 samples characters in total) matK 92% 1,726 94 45 (2.6%) 46 11 ITS 88% 605 94 71 (11.7%) 44 12 ITS2 88% 195 36 25 (12.8%) 44 12 ITS+ matK 100% 2,331 72 115 50 13 ITS2+ matK 100% 1,921 132 71 50 13

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Table 3: Identification success of ITS, ITS2, matK, ITS+matK and ITS2+matK using ML and BLAST methods. Crosses (X) indicate the species was not monophyletic in the ML tree, and check marks () indicate monophyletic species. One asterisk (*) indicates that the “first hit” on the BLASTn results was correctly identified (i.e., unambiguous identifications), and two asterisks (**) indicate that at least more than half of the species were correctly identified. Empty cells indicate that data is not available.

Monophyletic species in the ML trees Percentage of BLASTn identification success

ITS ITS2 matK ITS+matK ITS2+matk ITS2 matK ITS2+matK

Aesculus X X  (88%)  (77%)  (88%)

A. californica  (100%)  (100%)  (84%)  (100%)  (100%) 100%* A. chinensis (including A. X X X X X 98% to 100% 100%* 100%* chinensis var. wilsonii) A. flava+A glabra+A. X X X  (80%) X 98% to 100% 98% to 100%** 98% to 100%** sylvatica+A. pavia A. hippocastanum  (67%) X X  (98%)  (90%) 100% 98% to 100% 99% to 100% A. indica  (100%)  (83%) X  (99%)  (93%) 100%* 99% to 100%* 99%* A. parryi  (100%)  (100%) Draft (100%)  (100%) 100%* A. parviflora  (100%)  (95%)  (98%)  (100%)  (100%) 100%* 100%* 100%* A. polyneura  (100%)  (98%)  (95%) 100%* A. tsiangii X  (55%)  (99%)  (88%)  (98%) 100% 100%* 100%*

A. turbinata X X  (63%)  (56%)  (59%) 99% to 100% 99% to 100%** 99% to 100%**

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Table 4: Summary of the results of the total evidence tree from the current study and previous studies. The studies and phylogenetic trees, which sampled only one taxon from each species, were not included. The species sampling of the current study includes both newly created sequences and sequences downloaded from GenBank. The dark grey cells indicate that the species was not monophyletic in the study, and the light grey cells indicate a monophyletic species. Crosses (X) indicate this taxon was not included in the study. Asterisks (*) indicate only one taxon was sampled.

Study Name of the species Xiang et al. (1998) (matK) Harris et al. (2009) Harris et al. (2016) Current study (matK+ITS) (cpDNA) (cpDNA+nDNA) Aesculus californica monophyletic (2 spp) monophyletic (5 spp) * monophyletic (6 spp) Aesculus chinensis (including * not monophyletic (6 spp) not monophyletic (4 spp) not monophyletic (5 spp) Aesculus chinensis var. wilsonii) Aesculus flava not monophyletic (2 spp) not monophyletic (2 spp) monophyletic (2 spp) not monophyletic (9 spp) monophyletic (2 spp) * not monophyletic (3 spp) not monophyletic (4 spp) Aesculus hippocastanum * * * monophyletic (17 spp)

Aesculus indica * not monophyletic (2 spp) * monophyletic (7 spp) not monophyletic (2 spp) not monophyletic (2 spp) not monophyletic (4 spp) not monophyletic (7 spp) * * monophyletic (2spp) monophyletic (6 spp) Aesculus parryi Draft * * * monophyletic (2 spp) Aesculus polyneura * X monophyletic (2 spp) Aesculus sylvatica not monophyletic (2 spp) * not monophyletic (2 spp) not monophyletic (6 spp) Aesculus turbinata * not monophyletic (2 spp) * monophyletic ( 8 spp) Aesculus tsiangii X * X monophyletic (2 spp) A. wangii (=A. assamica) * not monophyletic (2 spp) * X

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Figure 1: Phylogenetic relationships within Aesculus inferred from ML analysis of matK+ITS. Outgroups and five Aesculus sections (section Aesculus, section Calothyrsus, section Macrothyrsus, section Pavia and section Parryana) are indicated. Bootstrap values are indicated below branches.

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Figure 1: Phylogenetic relationships within Aesculus inferred from ML analysis of matK+ITS. Outgroups and five Aesculus sections (section Aesculus, section Calothyrsus, section Macrothyrsus, section Pavia and section Parryana) are indicated. Bootstrap values are indicated below branches.

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