Botanical Journal of the Linnean Society, 2021, 197, 1–14. With 4 figures. Can plastid genome sequencing be used for species identification in Lauraceae? 1 Plant Phylogenetics and Conservation Group, Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming, China 2 University of Chinese Academy of Sciences, Beijing, China 3 Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Mengla, China 4 Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, China 5 State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China 6 Sino-African Joint Research Center, Chinese Academy of Sciences, Wuhan, China 7 Herbarium (KUN), Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China 8 Tibet Agriculture & Animal Husbandry University, Nyingchi, China 9 Shandong Provincial Key Laboratory of Plant Stress Research, College of Life Sciences, Shandong Normal University, Ji’nan, China 10 Australian Centre for Evolutionary Biology and Biodiversity & Sprigg Geobiology Centre, School of Biological Sciences, University of Adelaide, Adelaide, Australia 11 Institute of Evolutionary Biology, Ashworth Laboratories, The University of Edinburgh, Edinburgh, UK 12 Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China 13 Genetics and Conservation Section, Royal Botanic Garden Edinburgh, Edinburgh, UK Received 23 June 2020; revised 27 December 2020; accepted for publication 25 January 2021 Using DNA barcoding for species identification remains challenging for many plant groups. New sequencing approaches such as complete plastid genome sequencing may provide some increased power and practical benefits for species identification beyond standard plant DNA barcodes. We undertook a case study comparing standard DNA barcoding to plastid genome sequencing for species discrimination in the ecologically and economically important family Lauraceae, using 191 plastid genomes for 131 species from 25 genera, representing the largest plastome data set for Lauraceae to date. We found that the plastome sequences were useful in correcting some identification errors and for finding new and cryptic species. However, plastome data overall were only able to discriminate c. 60% of the species in our sample, with this representing a modest improvement from 40 to 50% discrimination success with the standard plant DNA barcodes. Beyond species discrimination, the plastid genome sequences revealed complex relationships in the family, with 12/25 genera being non-monophyletic and with extensive incongruence relative to nuclear ribosomal DNA. These results highlight that although useful for improving phylogenetic resolution in the family and providing some species-level insights, plastome sequences only partially improve species discrimination, and this reinforces the need for large-scale nuclear data to improve discrimination among closely related species. ADDITIONAL KEYWORDS: cytonuclear discordance – DNA barcoding – nrDNA – phylogenetics – plastomes. *Corresponding authors. E-mails: jieli@xtbg.ac.cn; Alex. Twyford@ed.ac.uk; jbyang@mail.kib.ac.cn; PHollingsworth@ rbge.org.uk. © 2021 The Linnean Society of London. 1 This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 ZHI-FANG LIU1,2,13, HUI MA1, XIU-QIN CI1,3, LANG LI1,3, YU SONG4, BING LIU5,6, HSI-WEN LI7, SHU-LI WANG1,2,8, XIAO-JIAN QU9, JIAN-LIN HU1,2, XIAO-YAN ZHANG1,2, JOHN G. CONRAN10, ALEX D. TWYFORD11,*, JUN-BO YANG12,*, PETER M. HOLLINGSWORTH13,* and JIE LI1,3,* 2 Z.-F. LIU ET AL. INTRODUCTION © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 The aim of DNA barcoding is to use standardized DNA sequences to aid in species identification (Hebert et al., 2003; Hollingsworth, 2011). Various regions have been proposed for DNA barcoding in plants (Kress & Erickson, 2007; Lahaye et al., 2008), with the plastid loci matK+rbcL adopted as core DNA barcodes (CBOL Plant Working Group, 2009), with these loci now widely used alongside the nuclear region ITS and other plastid loci such as trnH–psbA (Chase et al., 2005; Kress et al., 2005; China Plant BOL Group, 2011; Hollingsworth, Graham & Little, 2011). Despite many benefits of using these standardized loci for plant DNA barcoding, it has long been recognized that no single suite of loci will be suitable across all plant taxa. In groups where standard DNA barcoding ‘fails’ due to technical issues, such as mutations in primer-binding regions, or biological issues, such as rapid divergence, researchers must augment the standard loci with additional sequence data. The massive improvements in genomic sequencing technologies allow researchers to explore many possible options for ‘genomic DNA barcodes’ to improve plant species identification. Whole plastid genomes (plastomes) have been proposed as suitable targets for the next wave of plant DNA barcoding approaches (Kane et al., 2012; Ruhsam et al., 2015; Hollingsworth et al., 2016; Twyford & Ness, 2017; Krawczyk et al., 2018), as they can be recovered using ‘genome skimming’ (low-coverage whole genome sequencing), a cost-effective and scalable sequencing approach that can be performed on a range of material (such as degraded herbarium samples) without prior sample optimization (Alsos et al., 2020). As well as plastome sequences, genome skimming also typically recovers the nuclear ribosomal DNA (nrDNA) assembly, collectively extending the plant barcode from a few thousand to hundreds of thousands of bases. Genome skimming also helps to circumvent primer issues, polymerase chain reaction (PCR) failures from amplicon sequencing of degraded DNA and different loci being preferred for different taxonomic groups, because shotgun sequencing is effective in routinely recovering plastid loci and nuclear ribosomal sequences due to their high copy numbers in plant cells (Coissac et al., 2016). However, there remain drawbacks to this approach for DNA barcoding of plants, as the plastid is a small organelle in which all loci are tightly linked and it therefore does not necessarily reflect the diverse history of the nuclear genome. This is compounded by the typically uniparental inheritance of the plastid genome and resulting sensitivity to demographic change. Similarly, the associated nrDNA, although a useful additional source of characters, still represents a fraction of the nuclear genome and can be problematic for species identification and phylogenetic analysis due to a range of issues, such as high diversity affecting the reliability of sequence alignments, incomplete concerted evolution and frequent paralogy. These issues create a tension between the technical appeal of plastomes and nrDNA in terms of ease of use, vs. their suitability as representatives of the evolutionary history of a species. Although the discriminatory power of next-generation DNA barcoding in plants has been evaluated in some recent studies (e.g. Kane et al., 2012; Li et al., 2015; Ruhsam et al., 2015; Ji et al., 2019; Pang et al., 2019), few studies have undertaken direct comparisons between the suitability of standard DNA barcodes and plastomes for genus and species identification using multiple individuals per species from a specific family. Lauraceae were established by de Jussieu (1789) in his Genera Plantarum, based on the type genus Laurus L. (Linnaeus, 1753). Lauraceae are evergreen or sometimes deciduous shrubs or trees (except for Cassytha L., which is a twining, virtually leafless, parasitic perennial vine), often with aromatic bark and foliage (Chanderbali, van der Werff & Renner, 2001; Li et al., 2008a). Lauraceae comprise c. 50 genera and 2500–3000 species from predominantly tropical and subtropical regions (van der Werff & Richter, 1996), and they are most diverse in tropical Asia, tropical America and Madagascar (Gentry, 1988; van der Werff & Richter 1996; Li et al., 2008a). They are economically and ecologically important as sources of medicines, timber, fruits, spices and perfumes (Kostermans, 1957; van der Werff & Richter, 1996; Li et al., 2008a), and are present in wet forests at any elevation and are frequently forest dominants (van der Werff & Richter, 1996). Nevertheless, despite their importance, the classification of Lauraceae is poorly known (van der Werff & Richter, 1996) and their broadscale classification has depended traditionally on the morphology of inflorescences and flowers (Nees von Esenbeck, 1836; Rohwer, 1993; van der Werff & Richter, 1996), although many groups have species that show exceptions. For example, whereas most Lauraceae flowers are regular with three whorls, groups such as Laureae have flowers that are frequently irregular, sometimes with more than three whorls of fertile stamens (Rohwer, 1993). Vegetative morphological similarities between taxa and intra-taxon variability are also causes of taxonomic confusion. Previous phylogenetic studies have used various plastid (matK, trnK, trnL–trnF, psbA–trnH, trnT– trnL, rps16) and nuclear regions (26S, RPB2, LEAFY and ITS) to study relationships in Lauraceae (Rohwer, 2000; Chanderbali et al., 2001; Rohwer & Rudolph, 2005; Li et al., 2008a, 2011; Rohwer et al., 2009; Huang et al., 2016; Mo et al., 2017). Recently, Song et al. (2020) showed that expanding to whole plastome PLASTOMES FOR SPECIES IDENTIFICATION MATERIAL AND METHODS SAMPLING AND SEQUENCING Our data set consists of plastid genomes and nrDNA from 80 de novo genome skims, augmented with plastid genome-only data from GenBank and LCGDB (https:// lcgdb.wordpress.com) for a further 111 individuals (last search 3 September 2019). The resulting 191 plastome samples represented 133 species, 131 of which represent 25 of the 55 currently recognized genera of Lauraceae and two of which represent the outgroup family Calycanthaceae. The 191 samples included 101 species with N = 1 sample, and a further 90 individuals from 34 species with N > 1 individual plastid genome sampled (mean three individuals per species, range two to five) from 16 genera. At the genus level, 25 genera were sampled, with 21 genera with more than one individual species sampled. A summary of the data set generated for this study is shown in Table 1 with details of the taxa sampled in the Supporting Information (Table S1). From the complete plastid genomes, we could also subsample regions for comparative analyses of species discrimination. For these analyses we compared (1) the complete plastid genome, (2) the gene regions from the plastid genomes, and (3) the standard DNA barcode matrix (rbcL+matK+trnH–psbA) and some barcode regions proposed as being useful for the family, e.g. Lauraceae-specific barcodes (ycf1+ndhH–rps15+trnL– ycf2; for further information see Note S1). The 80 de novo plastid genomes (including one individual sequenced twice) were derived from samples collected from eight provinces in China (Guangdong, Guangxi, Hainan, Hubei, Jiangxi, Sichuan, Yunnan and Xizang) and sites in Japan and Myanmar (Supporting Information, Table S2). Leaf tissue for each taxon was dried with silica gel and vouchers were deposited at the Herbarium of Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences (HITBC), Yunnan, China. The specimens and vouchers were identified by morphological and molecular comparisons as described previously (Liu et al., 2017). Total genomic DNA was extracted using a modified CTAB method (Doyle & Doyle, 1987) with a Tiangen DNA secure Plant Kit (DP320). Yield and integrity of genomic DNA extracts were quantified by fluorometric quantification on the Qubit (Invitrogen, Carlsbad, CA, USA) using the dsDNA HS kit and by visual assessment on a 1% agarose gel. The extracted DNA was sheared Table 1. Comparison of characteristics of different data sets in Lauraceae Data sets Subsets Number of taxa Number of species Number of genera Number of sites Best fit model of ML analysis 191 plastomes data set Plastomes Concatenated genes Extracted specific matrix Extracted standard matrix 80 plastomes 80 rDNA 191 191 131 131 25 25 180 129 79 387 TVM+F+I+G4 GTR+F+I+G4 191 129 24 2704 TVM+F+G4 191 131 25 2144 K3Pu+F+I+G4 79 79 71 71 21 21 172 022 6281 TVM+F+I+G4 TN+F+I+G4 Cytonuclear discordance data set © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 sequences can produce better resolved evolutionary relationships than Sanger sequencing of a few key loci. Although overall relationships among Lauraceae are mostly well known, species relationships in genera are still poorly understood. Most studies to date have only sampled a single individual per taxon, and sampling multiple individuals per species across diverse taxa would allow us to test for species-level monophyly and discrimination (Ji et al., 2019). Our previous study (Liu et al., 2017) used standard DNA plant barcodes to resolve Lauraceae relationships and classification by sampling multiple individuals per species; however, the resolution was poor. Accordingly, here we investigate whether the plastome can improve species discrimination relative to standard DNA barcodes in Lauraceae. Specifically, we have four aims: (1) to determine if plastome-based DNA barcodes improve taxonomic resolution and the potential for species identification compared to standard DNA barcodes; (2) to establish whether some proposed ‘Lauraceae-specific’ plastid barcodes provide useful information for species discrimination; (3) to relate genetic to morphological data to detect cases of mistaken identity and facilitate species discovery; and (4) to reconstruct phylogenetic relationships in Lauraceae and see if plastid genomes match the species boundaries determined from analysis of nrDNA sequences. 3 4 Z.-F. LIU ET AL. into c. 500-bp fragments for library construction using the standard protocol for the NEBNext Ultra IITMDNA Library Prep Kit for Illumina. All samples were sequenced on the Illumina HiSeq 2000 and Illumina HiSeq X at BGI and Novogene (Supporting Information, Table S2). AMAS (Borowiec, 2016). In addition, the specific and standard plastid barcode sequences from the 191 plastomes were extracted and concatenated using Geneious11.1.4. SPECIES DISCRIMINATION AND PHYLOGENETIC ANALYSES ASSEMBLY, ANNOTATION AND GENE SUBSAMPLING Our measures of species discrimination success for the genomic regions in question sampled multiple individuals per species to assess if these individuals were more closely related to each other than to other species. The species discrimination statistics only used cases where N > 1 individual sampled per species, but singleton species samples were included as decoys, as they occupy phylogenetic space and can ‘disrupt’ species-level monophyly, causing species recovery to ‘fail’, but they are not themselves included in the discrimination statistics. Overall, we recorded the proportion of species and genera that resolved as monophyletic following phylogenetic analysis. The utility of different data sets for species and genera identification were investigated using the two tree-based approaches: ML (maximum likelihood) methods using IQTREE (Trifinopoulos et al., 2016) and NJ (neighbour joining) methods using Geneious11.1.4. The best-fit model for each data set was determined using ModelFinder (Kalyaanamoorthy et al., 2017), with the best-fit substitution model selected by the option –TEST and using a tree search with 1000 bootstrap replicates in a single run (Kalyaanamoorthy et al., 2017). The number of species or genera with multiple accessions resolving as monophyletic was recorded, as was the branch support for each node with > 50% support. To provide a best estimate of the phylogeny of Lauraceae, we also undertook phylogenetic analysis using ASTRAL-III (Zhang et al., 2018), as a recent study verified that the multispecies coalescent method for determining phylogeny offered a high level of accuracy with plastid data (Gonçalves et al., 2019). This approach considers variation in the phylogenetic signal across plastid genes, so we based our family-level phylogenetic tree on concatenated gene regions (excluding intergenic spacers) from the 191 plastome data set, summarized by the coalescent-based ASTRAL method. The concatenated matrix yielded 113 gene trees (absent genes were treated as missing data). Construction of the species tree was performed using the separate gene ML trees from the 191 plastomes as input for ASTRAL-III (nodes with < 10% bootstrap support were collapsed), with 100 bootstrap replicates generated to assess bootstrap support using the coalescent model. The R package phytools (Revell, 2012) was used to compare © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 GetOrganelle (Jin et al., 2018) was used for assembly of plastomes and nrDNA (18S–ITS1–5.8S–ITS2–26S). GetOrganelle uses baiting and iterative mapping to assemble plastomes with minimal manual intervention and integrates SPAdes (Bankevich et al., 2012), Bowtie2 (Langmead & Salzberg, 2012), BLAST+ (Camacho et al., 2009) and Bandage (Wick et al., 2015). Comparison of the published plastomes for Lauraceae (Song et al., 2015, 2016, 2017a, b, 2018, 2020; Hinsinger & Strijk, 2017; Wu et al., 2017; Zhao et al., 2018) led us to choose Litsea glutinosa (Lour.) C.B.Rob (KU382356) as the plastid genome reference for assembly, and the pipeline reference Embryophyta plant nuclear as the partial or complete nrDNA (18S–ITS1–5.8S–ITS2–26S) sequence assembly reference https://github.com/Kinggerm/GetOrganelle. All plastid genomes were checked manually for assembly quality, particularly at the inverted repeat boundaries. MAFFT (Kuraku et al., 2013; Katoh, Rozewicki & Yamada, 2017) was used for sequence alignment, followed by a manual check using Mesquite (Maddison & Maddison, 2018) and Geneious11.1.4. Alignments in FASTA format were exported for each data set. Plastid genomes were annotated using PGA (Qu et al., 2019) and GeSeq (Tillich et al., 2017). For plastome annotations, as well as Litsea glutinosa, two other well-annotated early-diverging species were also used as references [Caryodaphnopsis henryi Airy Shaw (MF939346) and a new unpublished species of Beilschmiedia Nees (C4011)]. To standardize annotation, we also re-annotated the previously published sequences with this workflow. After annotation, a manual check was undertaken and the reading frame was verified in Geneious11.1.4 (https:// www.geneious.com) by visually inspecting the start and stop codons. The orientations of the inverted repeats (IRs) were checked by LASTZ (Harris, 2007). Transfer RNAs (tRNAs) were confirmed by their specific structure predicted by tRNAscan-SE 2.0 (Lowe & Chan, 2016; de Santana Lopes et al., 2019) compared with other published annotated genomes (Shinozaki, 1986; Song et al., 2017b; Qu et al., 2019). Gene extraction was performed using the script ‘get_annotated_regions_from_gb.py’ of Jin (https:// github.com/Kinggerm/PersonalUtilities) to obtain the annotated regions, then checked manually using Geneious11.1.4 with the matrix concatenated using PLASTOMES FOR SPECIES IDENTIFICATION RESULTS SEQUENCE CHARACTERISTICS The aligned consensus length of the 191 complete plastomes was 180 129 bp, with the corresponding concatenated genes, the extracted ‘Lauraceae-specific’ and ‘standard’ barcode matrices being 79 387, 2704 and 2144 bp, respectively. For the newly sequenced samples used in the analysis of cytonuclear discordance, the nrDNA (18S–ITS1–5.8S–ITS2–26S) alignment was 6281 bp, with the corresponding plastome length 172 022 bp (Table 1). The plastid genome sizes were similar between accessions, except for the parasitic genus Cassytha (Supporting Information, Table S3), with Cassytha filiformis L. MH03, MH04 having the smallest plastid genome (114 705 bp). Cassytha has lost one IR region and most ndh genes, with remnants of some ndh regions as pseudogenes. The largest plastid genome is Syndiclis sp. ZF61 (Cryptocaryeae) with 158 639 bp, and Cryptocaryeae overall have larger plastome genomes (157 057–158 639 bp based on the unaligned sequences; Table S3), due in part to multiple large insertions in Beilschmiedia, Cryptocarya R.Br., Endiandra R.Br. and Syndiclis Hook.f. For example, in Beilschmiedia, there are insertions up to 723 bp relative to the related genus Neocinnamomum H.Liu. However, there are also large deletions, such as a 1657-bp deletion in Beilschmiedia compared with other early-diverging genera. For most species with more than one individual, the genome sizes were mostly the same, although some were variable, e.g. Neocinnamomum delavayi (Lecomte) H.Liu and Phoebe bournei (Hemsl.) Yen C.Yang (Table S3). These length variations mainly relate to indels located at the beginning of the large single copy (LSC) region. MISTAKEN IDENTIFICATION AND SPECIES DISCOVERY After combining DNA sequences and relating these sequences to existing morphological characters, a few putative species were divergent from most individuals sequenced for their assigned species or genus, and these were found to be nested in other taxa (labelled red in Fig. 1 and Supporting Information, Figs S1–S9). For the publicly available downloaded samples, we can only speculate about potential misidentifications, as even checking voucher specimens can leave uncertainty. For the individuals that we sampled and sequenced, the examination procedure of Liu et al. (2017) was followed; we rechecked our sequences together with the morphology of our vouchers, herbarium specimens from HITBC, KUN and living specimens in the XTBG and KIB botanic gardens. Twelve individuals were found to be mislabelled or potentially so (Table 2), including ZF14, which was similar vegetatively to Alseodaphnopsis petiolaris (Meisn.) H.W.Li & J.Li and initially identified as such. However, the plastome sequence of ZF14 clustered with Machilus Nees. Recollecting the sample and repeating the experimental procedures and analyses resulted in ZF14b (Supporting Information, Tables S1– S3) still clustering with Machilus (Fig. 1; Figs S1–S9); however, as Machilus was found to be monophyletic in previous studies (Li et al., 2011; Song et al., 2020), we therefore assumed our initial identification of ZF14 as Alseodaphnopsis petiolaris was an error (Table 2). An additional anomaly in Cassytha was deemed worthy of further investigation. As there is just one species of Cassytha (C. filiformis) described in China (Li et al., 2008a), we treated all Cassytha samples as C. filiformis; however, our plastome data showed that MH01, 02 and SZ01 clustered with the GenBank plastome of C. capillaris Meisn. 1258175302 collected from Indonesia. A comparison of all plastomes of Cassytha spp. showed that the plastome sizes of the GenBank C. capillaris 1258175302 and our new sequences of MH01, 02 and SZ01 were much larger than those of the remaining samples assigned to C. filiformis (MH03, 04, 1258175251, 1243302039 and 1474379909), with clear insertion/deletion sites separating these sample groups. Morphological comparisons were also made and the sample fruits of SZ01 were found to be reddish and barely strigose. These features are recorded as distinguishing characteristics of C. capillaris (Weber, 1981, 2007). The specimens of MH01 and 02 were older, and less suited for comparisons, particularly as the colours have faded on their specimens. In addition, Mo et al. (2017) described GLQ26 and GLQ33 as a new record for Yunnan Province, China, of Alseodaphnopsis rugosa (Merr. & Chun) H.W.Li & J.Li. However, our results placed these samples instead with the recently described Alseodaphnopsis maguanensis L.Li & J.Li (Li et al., 2020). Further comparisons of other samples using genetic data matched against morphological characters suggests that several of them represent potential © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 ML trees between the 191 plastomes and concatenated genes trees. To understand the relationships between plastomes and nrDNA better, a further analysis was conducted using only our 80 assembled whole plastid genomes and associated nrDNA (18S–ITS1–5.8S–ITS2–26S). This data set was used as the nrDNA and the plastome sequence data are derived from the same individuals. Cytonuclear discordance analysis of the 80 newly sequenced plastomes and nuclear DNA data sets was performed using ML and phytools was used for comparing the resulting ML trees. 5 6 Z.-F. LIU ET AL. Table 2. Original species determinations and correct species using DNA barcodes Corrected species determination Actinodaphne pilosa GLQ34 Alseodaphnopsis rugosa GLQ26 Neolitsea sp. GLQ34 Alseodaphnopsis maguanensis GLQ26 Alseodaphnopsis maguanensis GLQ33 Machilus sp. ZF14 Endiandra sp. C40 Cassytha capillaris MH01 Cassytha capillaris MH02 Cassytha capillaris SZ01 Lindera sp. JP31 Machilus sp. ZF59 Lindera communis 1433040893 Persea americana SY9559 Alseodaphnopsis rugosa GLQ33 Alseodaphnopsis petiolaris ZF14 Beilschmiedia robusta C40 Cassytha filiformis MH01 Cassytha filiformis MH02 Cassytha filiformis SZ01 Cinnamomum caudiferum JP31 Cinnamomum sp. ZF59 Lindera nacusua 1433040893 Persea americana var. drymifolia SY9559 new species of Alseodaphnopsis, Beilschmiedia and Phoebe Nees (labelled in blue in Fig. 1 and Supporting Information, Figs S1–S9). These samples warrant further investigation and are noted here as having either divergent sequences or atypical morphologies compared to their sister species in the phylogenetic tree. COMPARISON OF DISCRIMINATION EFFICIENCY The resolution rates of species (41.2–58.8%) and genera (52.4–66.7%) varied by data source and analytical method (Table 3; Fig. 2). The species and genera successfully distinguished are indicated with a circle and a star in Supporting Information Figures S1–S8. The two tree-based methods (ML and NJ) have the same discrimination ability at the species level, whereas ML performed better than NJ at the genus level (Fig. 2). The plastomes and concatenated genes gave the highest resolution rates (Table 3; Fig. 2; Figs S1–S4) and a comparison is shown in Figure S9, with lower resolution from the Lauraceae-specific barcodes, and the standard barcodes giving the lowest resolution of all (Table 3; Fig. 2; Figs S5–S8). ANALYSES OF PHYLOGENY AND Figure 1. Phylogenetic relationships of Lauraceae species tree generated from concatenated genes of the plastid genomes bases on ASTRAL analysis. CYTONUCLEAR DISCORDANCE Along with a comparison of the previous phylogenetic hypotheses and based on all previous studies, Figure 3 © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 Original species determination 11/21 (52.4%) 12/21 (57.1%) 13/21 (61.9%) 14/21 (66.7%) 14/21 (66.7%) 13/21 (61.9%) 12/20 (60%) 11/20 (55%) 14/34 (41.2%) 14/34 (41.2%) 20/34 (58.8%) 20/34 (58.8%) Successful species/ sampled species Successful genera/ sampled genera 20/34 (58.8%) 20/34 (58.8%) 16/32 (50%) 16/32 (50%) Standard-NJ Standard-ML Specific-NJ Specific-ML Concatenated genes-NJ Concatenated genes-ML Plastomes-ML Barcode regions Plastomes-NJ 7 Figure 2. Discrimination efficiency comparison of 191 plastomes and sub-sampled regions. shows the current most likely phylogenetic backbone of Lauraceae. The results of our study are shown in Figure 1. Our results strongly support Lauraceae as monophyletic [bootstrap support (BS) = 100%] (Fig. 1), sister to a clade containing the outgroup species [Calycanthus chinensis (W.C.Cheng & S.Y.Chang) P.T.Li and Calycanthus floridus var. glaucus (Willd.) Torr. & A.Gray; Calycanthaceae]. Lauraceae formed seven clades (Fig. 1), agreeing with previous phylogenetic analyses (Fig. 3). In the first-diverging clade I, Cryptocaryeae comprised five genera, with Eusideroxylon Teijsm. & Binn. sister to a clade with three monophyletic genera (Cryptocarya, Endiandra and Syndiclis) and Beilschmiedia paraphyletic (Fig. 1). Clade II (BS = 100%) consisted of Cassytheae with one genus, Cassytha, but displaying long branch lengths (Supporting Information, Fig. S9). Clade III (BS = 100%), Neocinnamomeae, included only Neocinnamomum. Clade IV (BS = 100%), Caryodaphnopsideae, similarly only contained Caryodaphnopsis Airy Shaw. Seven genera of Perseeae (Persea Mill., Dehaasia Blume, Nothaphoebe Blume, Alseodaphne Nees, Alseodaphnopsis, Phoebe and Machilus) were sister to a clade comprising taxa from Cinnamomeae and Laureae (Fig. 1). Persea was separated into two clades, with P. borbonia L. mixed with Dehaasia, Nothaphoebe and Alseodaphne, whereas P. americana Mill. was sister to the remaining Perseeae. Species of Alseodaphnopsis were found in two separate clades: one resolved at the base of the clade containing the Phoebe–Machilus lineage, and the other sister to Machilus (Fig. 1). The sister relationship between Cinnamomeae and Laureae was moderately supported (BS = 64%) (Fig. 1). For Cinnamomeae, Nectandra angustifolia Nees & Mart. ex Nees was sister to the remainder. Sassafras J.Presl was nested in Cinnamomum Schaeff., making the latter paraphyletic. In Laureae, Iteadaphne Blume (one species only), Laurus (two sampled species), © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 Table 3. Success in species discrimination based on data from the 191 plastomes data set (based on species with two or more sampled individuals per species) PLASTOMES FOR SPECIES IDENTIFICATION 8 Z.-F. LIU ET AL. Neolitsea (Benth.) Merr. and Parasassafras D.G.Long (one species only) were monophyletic (Fig. 1), whereas Lindera Thunb., Litsea Lam. and Actinodaphne Nees were either poly- or paraphyletic. Alseodaphnopsis was monophyletic in a previous nrDNA study (Mo et al., 2017), but our study using plastid genes did not support this. Phylogenetic incongruence of plastomes and nuclear DNA extends across the hierarchical taxonomic levels of Lauraceae, even though the information provided by nrDNA is limited (Fig. 4). First, although two earlydiverging tribes, Cryptocaryeae and Cassytheae, gave consistent relationships, there were conflicting patterns on the placement of Cryptocarya depauperata H.W.Li and Cryptocarya hainanensis Merr. Second, Neocinnamomeae and Caryodaphnopsideae changed their phylogenetic positions in the nrDNA tree relative to the plastome tree, and this inconsistency was well supported (100%) in a bootstrap analysis (Fig. 4). Third, although Cinnamomeae, Laureae and Perseeae were consistent at the tribe level, cytonuclear discordance occurred within them (Fig. 4.2). In total, 19 individuals from our 80 samples were consistent across the plastome and nrDNA trees, with the remaining 61 individuals showing conflict between the nuclear and plastome phylogenomic analyses. DISCUSSION DNA BARCODING PERFORMANCE There remain relatively few studies assessing the power of complete plastome sequences in plant barcoding (Ji et al., 2019). The discriminatory power revealed by previous studies sampling multiple individuals from multiple congeneric species is variable. For instance, the plastome was shown to successfully distinguish some closely related species in Quercus L. (Pang et al., 2019), Stipa L. (Krawczyk et al., 2018) and Taxus L. (Fu et al., 2019). However, plastomes failed to significantly improve species identification in Panax L. (Ji et al., 2019) and New Caledonian Araucaria Juss. (Ruhsam et al., 2015). Our comparison in Lauraceae indicates that the discrimination rates of the plastome was higher than those of standard DNA barcodes or Lauraceaespecific barcodes. The Lauraceae-specific barcodes (i.e. loci selected as having potential for use in Lauraceae) gave a modest increase in resolution, but this was still only improved from 41% at the species level (for standard barcodes) to 50%. The highest species resolution in our study was c. 60% from the complete plastome sequences. Even here, however, with far from complete species-level © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 Figure 3. Review of current phylogenetic relationships of Lauraceae based on previous Sanger and plastid genome sequences. PLASTOMES FOR SPECIES IDENTIFICATION 9 Cinnamomeae Clade I Cinnamomeae Clade II Neolitsea levinei 20160028 Neolitsea homilantha JP20 Neolitsea sp. GLQ34 Actinodaphne henryi ZF41 100 Lindera villipes SL05 100 100 100 100 100 100 Lindera thomsonii var.vernayana ZF44 Iteadaphne caudata ZF56 Parasassafras confertiflorum LC001 Litsea liyuyingi ZF20 Litsea dilleniifolia ZF39 Litsea monopetala ZF04 100 100 100 100 Lindera obtusiloba var.heterophylla SL07 Litsea sericea SL06 Litsea rubescens KZ04 Litsea tibetana SL09 Litsea glutinosa ZF03 Laurus nobilis KZ02 100 100 61 100 100 Lindera communis ZF21 Lindera communis KZ06 Lindera sp. JP31 100 100 100 100 100 100 100 100 100 100 96 Cinnamomum glanduliferum KZ08 Cinnamomum camphora KZ05 Cinnamomum japonicum ZF50 Cinnamomum burmannii ZF38 Cinnamomum verum ZF33 Cinnamomum tamala YB08 Sassafras tzumu ZF48 Sassafras albidum KZ23 Cinnamomum porrectum YB04 Cinnamomum caudiferum FD24 Machilus rufipes s20 Machilus duthiei KZ03 98 Machilus yunnanensis HLT Machilus faberi WH02 Machilus pauhoi WH03 94 100 Machilus sp. ZF14b 100 100 100 100 Machilus sp. ZF14 Machilus minutiflora ZF37 100 Machilus sp. ZF59 Alseodaphnopsissp. sp. ZF57 100 99 100 100 Alseodaphnopsis hainanensis ZF68 Alseodaphnopsis rugosa ZF67 Alseodaphnopsis sp. nov. C4013 100 100 100 52 100 100 100 80 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 Caryodaphnopsis tonkinensis GLQ08 Caryodaphnopsis malipoensis GLQ13 Neoinnamomum delavayi KZ01 Neocinnamomum caudatum ZF22 Neocinnamomum mekongense ZF23 Neolitsea homilantha JP20 100 53 100 79 97 52 100 100 Neolitsea sp. GLQ34 100 Parasassafras confertiflorum LC001 62 Lindera sp. JP31 Cinnamomum glanduliferum KZ08 Cinnamomum camphora KZ05 Cinnamomum porrectum YB04 Cinnamomum caudiferum FD24 100 71 100 100 99 Sassafras tzumu ZF48 Sassafras albidum KZ23 Cinnamomum verum ZF33 Cinnamomum tamala YB08 Cinnamomum japonicum ZF50 Cinnamomum burmannii ZF38 Phoebe sheareri WH05 Phoebe sheareri WH01 Phoebe sheareri ZF45 Phoebe zhennan JY10 Phoebe bournei SCH08 100 99 100 100 94 100 80 97 100 99 Phoebe hui ZF49 Phoebe sp. nov. ZF55 100 Phoebe cavaleriei SN01 Alseodaphnopsis hainanensis ZF68 Alseodaphnopsis sp. nov. C4013 99 92 Alseodaphne gracilis GLQ03 Phoebe yunnanensis ZF51 100 95 98 Alseodaphnopsis rugosa ZF67 79 88 100 Alseodaphnopsis sp. ZF57 Alseodaphnopsis petiolaris ZF64 Alseodaphnopsis andersonii ZF01 Alseodaphnopsis ximengensis XM01 Persea americana YL01 Machilus pauhoi WH03 Machilus duthiei KZ03 Machilus rufipes s20 95 93 97 65 79 79 Machilus minutiflora ZF37 Machilus ynnanensis HLT Machilus faberi WH02 50 79 Machilus sp. ZF14b 96 100 Machilus sp. ZF14 Machilus sp. ZF59 Neocinnamomum mekongense ZF23 Neocinnamomum caudatum ZF22 Neoinnamomum delavayi KZ01 100 100 Caryodaphnopsis tonkinensis GLQ08 Caryodaphnopsis malipoensis GLQ13 Cassytha capillaris MH02 Cassytha capillaris MH01 Cassytha capillaris MH01 Cassytha capillaris SZ01 Cassytha capillaris SZ01 Cassytha filiformis MH04 Cassytha filiformis MH03 Cassytha filiformis MH04 Cassytha filiformis MH03 Beilschmiedia sp. nov. C4011 Beilschmiedia sp. nov. YB43 Beilschmiedia yunnanensis C25 Syndiclis sp. ZF61 Syndiclis marlipoensis ZF60 Beilschmiedia sp. nov. C4011 Beilschmiedia sp. nov. YB43 Beilschmiedia yunnanensis C25 Syndiclis sp. ZF61 Syndiclis marlipoensis ZF60 Endiandra dolichocarpa TN01 Endiandra dolichocarpa TN01 Cryptocarya brachythyrsa ZF02 91 100 Actinodaphne henryi ZF41 Cassytha capillaris MH02 Cryptocarya depauperata ZF11 Cryptocarya hainanensis ZF10 95 Neolitsea levinei 20160028 Alseodaphnopsis maguanensisi GLQ26 Cryptocarya yunnanensis YB13 100 100 100 Litsea sericea SL06 Litsea rubescens KZ04 Lindera villipes SL05 Lindera thomsonii var.vernayana ZF44 Iteadaphne caudata ZF56 Lindera obtusiloba var.heterophylla SL07 Alseodaphnopsis maguanensisi GLQ33 Phoebe sp. nov. ZF55 Phoebe cavaleriei SN01 Phoebe yunnanensis ZF51 Alseodaphnopsis petiolaris ZF64 Alseodaphnopsis andersonii ZF01 Alseodaphnopsis ximengensis XM01 Persea americana YL01 Alseodaphne gracilis GLQ03 99 100 Litsea glutinosa ZF03 Litsea tibetana SL09 Alseodaphnopsis maguanensisi GLQ33 Phoebe sheareri WH05 Phoebe sheareri WH01 Phoebe sheareri ZF45 Phoebe zhennan JY10 Phoebe hui ZF49 Phoebe bournei SCH08 100 Laurus nobilis KZ02 Alseodaphnopsis maguanensisi GLQ26 Endiandra sp. C40 100 Litsea liyuyingi ZF20 Litsea dilleniifolia ZF39 Litsea monopetala ZF04 Lindera communis ZF21 Lindera communis KZ06 100 84 95 100 99 100 76 100 99 100 Endiandra sp. C40 Cryptocarya yunnanensis YB13 Cryptocarya hainanensis ZF10 100 100 57 98 Cryptocarya depauperata ZF11 Cryptocarya brachythyrsa ZF02 100 Figure 4. Discordance between 80 GetOrganelle-assembled plastomes and nrDNA sequences based on ML analyses. © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 100 100 100 10 Z.-F. LIU ET AL. PHYLOGENETIC RELATIONSHIPS AND INCONGRUENCE BETWEEN PLASTOMES AND NRDNA The plastome sequence analysis recovered seven tribes using the multispecies coalescent method ASTRAL, with this approach giving the most detailed insight into the relationships of Lauraceae, although we lack samples from two remaining clades in Figure 3 for which previous molecular data exist: Hypodaphnis Stapf from Cameroon, Gabon and Nigeria (Rohwer, 1993); and Mezilaurus Taub. from South America (Rohwer, 1993; Chanderbali et al., 2001; Rohwer & Rudolph, 2005). Our results provide the most comprehensive plastome-based phylogenetic hypothesis for relationships in Lauraceae. However, there are still many non-monophyletic groups and taxonomic issues that need to be resolved. The paraphyletic relationships in Actinodaphne, Beilschmiedia, Lindera, Litsea and Persea have been documented in previous studies (Rohwer, 2000; Chanderbali et al., 2001; Li, Li & Conran, 2007; Li et al., 2008b, 2011; Rohwer et al., 2009), whereas the relationships of Alseodaphnopsis seen here conflict with previous studies (Mo et al. 2017). Mo et al. (2017) published the new genus Alseodaphnopsis based on nuclear DNA regions, but the genus is poorly known; the limited availability of collections makes morphological diagnostic characters hard to find (van der Werff, 2019), and our study recovered the genus as polyphyletic. Similar to Rohde et al. (2017) and Trofimov & Rohwer (2020), we found that Sassafras was nested in Cinnamomum, with their morphological similarities discussed above. Cytonuclear discordance has been observed in many plant groups (Rieseberg & Soltis, 1991; Soltis & Kuzoff, 1995; Folk et al., 2018; Liu et al., 2018, 2019; Ji et al., 2019; Lee-Yaw et al., 2019). The relationships in Lauraceae reconstructed using nrDNA sequences contrast with the phylogenetic tree derived from plastomes (Fig. 4). This incongruence between the maternally inherited plastid and biparentally inherited nuclear DNA has been reported in Lauraceae by Rohde et al. (2017) using psbA–trnH plus trnG–trnS plus ITS. The results seen here show that is is feasible to use either plastomes or nrDNA for early-diverging groups such as Cryptocaryeae and Cassytheae, as the relationships were consistent with either data source, but the conflicts in the remaining tribes caution against the use of plastomes and nrDNA to infer relationships in isolation. Specifically, the wellsupported incongruent sister relationship between Caryodaphnopsideae and Neocinnamomeae suggests that there may have been historical reticulation or other complex processes shaping the early evolutionary history of these groups. In addition, the incongruent phylogenetic relationships in Laureae, Perseeae and © 2021 The Linnean Society of London, Botanical Journal of the Linnean Society, 2021, 197, 1–14 Downloaded from https://academic.oup.com/botlinnean/article/197/1/1/6179569 by guest on 01 March 2023 sampling and 180 kb of sequence data, many species are not distinguishable with sequence data. Further sampling is likely to decrease this discrimination success, as the phylogenetic space becomes more densely occupied, and the situations where DNA barcodes did not discriminate between species are typically associated with higher sample density of co-occurring congeneric species. It is not clear what the primary driver(s) is for this discrimination failure in Lauraceae; plastid genomes being shared by hybridization, recent diversification or rapid radiations, slow sequence mutation rates and/or restricted infraspecific gene flow could be involved (Fazekas et al., 2009; Hollingsworth et al. 2011, 2016; Ruhsam et al., 2015). Although we are focusing on the ‘failure’ of the DNA barcoding data to discriminate among taxa in Lauraceae, an additional factor to consider is whether the taxonomy of the family needs further revision. There are many species from different genera of Lauraceae with similar morphological characteristics. For example, some Machilus spp. are similar to Phoebe, as are some Dehassia to Alseodaphne and Alseodaphnopsis. Conversely, some taxa that were thought to be easy to discriminate using morphological characteristics were grouped closely on the phylogenetic tree. For example, the simple leaved taxa of Cinnamomum showed a close relationship with the lobed leaved taxa of Sassafras. Building on this example, the affinity of taxa in these genera is further revealed by reconsideration of morphological characters. Thus, simple leaves also exist in Sassafras which are also morphologically quite similar to Cinnamomum section Camphora Meissn. Likewise, the flowers of Sassafras in the Asian species show similarities to those of Cinnamomum, and the fruits of Sassafras species are similar to those of Cinnamomum section Camphora. Thus, part of the conflicting signal between the plastid data and morphology-based classifications may also be due to a complex history of the interpretation of morphological characters in the family. Despite the data showing imperfect resolution at the species level, our results also enabled the detection of misidentifications as well as the identification of cryptic species and potential new species. Previously only Cassytha filiformis was known in China (Li et al., 2008a). Here, through our barcode research, we can now confirm that there is another Cassytha sp., Cassytha capillaris, present in China, representing a new record for the country. Our study also highlighted other potential new taxa in Alseodaphnopisis, Beilschmiedia and Phoebe that warrant further investigation (Fig. 1; Supporting Information, Figs S1–S9). PLASTOMES FOR SPECIES IDENTIFICATION CONCLUSIONS Our plastid genome data resulted in a modest increase in discriminatory power in Lauraceae compared to standard DNA barcodes or regions selected for the family. Using plastomes as genomic DNA barcodes was nevertheless useful in the correction of misidentified species, the discovery of cryptic species and in forming the foundation of the description of new species. The plastome data set also provided a useful phylogenetic framework for the family, but cytonuclear discordance suggests caution is needed in the interpretation of plastomes and/or nrDNA phylogenetic analyses of the family. This case study reiterates the value of accessing multi-locus information from the nuclear genome for species discrimination and understanding phylogenetic relationships, especially among closely related taxa. DATA ACCESSIBILITY GenBank numbers, plastid genomes MT621572– MT621650 and nrDNA MT628590–MT628656, MT669015–MT669026, noted in Table S2. ACKNOWLEDGEMENTS The authors would like to thank Hua-Jie Zhang, JieQiong Li, Xian-Hui Shen, Wei-Yue Zhao, Xue Bai, Cai-Yu Sheng, Ji-Pu Shi, Yun-Xue Xiao, Lin-Li Zheng, Zhi-Yuan Lu, Zhi-Xiang Liu, Jian-Hua Xiao, Ding Xin, Chao-Nan Cai, Qin-Xi Hou, Yue-Qing Mo, Zhi-Yi Liu, Hong-Hu Meng, Can-Yu Zhang and Jian-Wu Li for collection assistance and Jens G. Rohwer for some species morphological identification. We are grateful to Chun-Yan Lin and Jing Yang for experiment assistance, and Yu-Hsin Tseng, Xiang-Qin Yu, Xiao-Yang Gao, Zhen-Shan He, Catherine Kidner, Markus Ruhsam, Linda Neaves, Laura Forrest, Li-Na Dong, Xiu Hu, Peng-Cheng Fu, the ICT of RBGE and the CyVerse Atmosphere Team for data analysis assistance. Special thanks go to Jian-Jun Jin and Wen-Bin Yu for their kind help with plastome assembly and to Stephen Jones for copy-editing an earlier version of the manuscript. We also thank Jens G. Rohwer for his comments on the manuscript. We acknowledge the China Scholarship Council who supported Zhi-Fang Liu as a joint PhD student at the Royal Botanic Garden Edinburgh. 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Taxon sampling, material sources and GenBank accession numbers for de novo sequenced individuals. Table S3. Plastid genome sizes of the 191 individuals. Figure S1. ML tree of 191 whole plastid genomes. Figure S2. NJ tree of 191 whole plastid genomes. Figure S3. ML tree of concatenated genes extracted from 191 whole plastid genomes. Figure S4. NJ tree of concatenated genes extracted from 191 whole plastid genomes. Figure S5. ML tree of the Lauraceae-specific barcode matrix (ycf1+ndhH–rps15+trnL–ycf2) extracted from 191 whole plastid genomes. Figure S6. NJ tree of the Lauraceae-specific barcode matrix (ycf1+ndhH–rps15+trnL–ycf2) extracted from 191 whole plastid genomes. Figure S7. ML tree of the standard barcode matrix (rbcL+matK+trnH–psbA) extracted from 191 whole plastid genomes. Figure S8. NJ tree of the standard barcode matrix (rbcL+matK+trnH–psbA) extracted from 191 whole plastid genomes. Figure S9. 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