New reports of nuclear DNA content for 66 traditional Chinese medicinal plant taxa in China

Abstract

The amount of DNA in the unreplicated haploid nuclear genome (C-value) provides important information for genome biodiversity. Genome size is used in a strikingly wide variety of plant biological fields with both practical and biological significance. To extend previously published datasets on plant nuclear content and to compile information on the DNA content of traditional Chinese medicinal plants in China, flow cytometry (FCM) was used to estimate C-values of medicinal plants in Shaanxi province, China. A total of 80 medicinal plant species and vouchers were collected from locations across Shaanxi province in China. Nuclei were extracted from fresh leaves in one of two buffers, stained with fluorochrome propidium iodide (PI), and analyzed on a Guava flow cytometer to measure the position of the fluorescence peaks relative to those of an internal calibration standard. Replicate extractions, low coefficients of variation and comparisons with published C-values in the same and related species were used to confirm the accuracy and reliability of our results. Prime C-values for 66 medicinal plant taxa are provided for which no published data exist, comprising 66 angiosperms, one gymnosperm and one pteridophyte. C-values for 14 additional taxa where a genome size has previously been published are also provided. The prime values represent new reports for 27 genera (out of the 48 genera and 38 families sampled). These data provide the foundation to enable phylogenetic analysis of C-value variation and karyotype diversity in Chinese traditional medicinal plants and assist future analyses aimed at analyzing how C-values co-vary with effective components and functional traits in Chinese traditional medicinal plants.

Keywords:

• C-value
• traditional Chinese medicinal plant
• flow cytometry
• plant phylogenetics

Introduction

Genome sizes are characterized in terms of their C-value, the picograms of DNA present in an unreplicated haploid or gametic nucleus (Swift 1950). The size of an organism’s genome reflects a fundamental aspect of its biology as well as a character of considerable practical use (Fay et al. 2005; Bennett and Leitch 2005, 2011; Beaulieu, Leitch, et al. 2007; Beaulieu, Moles, et al. 2007; Beaulieu et al. 2008; Leitch et al. 2009, 2010; Chung et al. 2012; Leitch and Leitch 2012; Janousek et al. 2013). To date, researchers have estimated C-values for 8509 plant species, as reported in the most recent release of the Plant DNA C-values Database (Release 6.0): http://data.kew.org/cvalues/ (Bennett and Leitch 2012). The electronic databases have now been cited > 230 times with > 250,000 hits (Bennett and Leitch 2011), and provide a powerful global research platform for biological scientists across the world. Researchers have used DNA C-values to address questions in cellular, developmental, ecological, evolutionary and molecular biology as well as systematics, physiology and paleontology (e.g. Bennett et al. 2000; Bennett and Leitch 2005; Leitch and Bennett 2007; Franks et al. 2012; Greilhuber and Leitch 2013). Recent work includes studies of the relationships between genome size and seed mass (Beaulieu, Moles, et al. 2007), photosynthetic rate (Beaulieu, Leitch, et al. 2007), leaf cell size and stomata density (Beaulieu et al. 2008; Hodgson et al. 2010) and patterns of genome size evolution (Leitch et al. 2005, 2009; Beaulieu et al. 2010; Chung et al. 2012). With the increase in the number of plant C-values in the Plant DNA C-values Database, studies of the relationship between genome size and various biological characteristics is likely to continue to expand.

Over the years, flow cytometry and Feulgen microdensitometry have both been used extensively to estimate C-values in plants, although flow cytometry is becoming increasingly the method of choice as the machinery needed for Feulgen microdensitometry becomes less widely available (Bennett and Leitch 2011). Nevertheless, flow cytometry is not without its problems and careful application of the technique is essential for generating reliable data (Doležel et al. 2007a; Greilhuber et al. 2007). Indeed, there are multiple factors that can affect the reliability of C-value data, including the choice of extraction buffer (with over 28 different buffers in use; Lourerio et al. 2007), how raw FCM data are analyzed (forward scatter, side scatter and relative fluorescence intensity), which plant species are used as calibration standards (Doležel and Greilhuber 2010; Suda and Leitch 2010) and the potentially confounding effects of cytosolic compounds (e.g. anthocyanin and tannic acid) (Doležel et al. 2007a, 2007b; Bennett and Leitch 2011; Loureiro, Suda, et al. 2007; Loureiro, Rodriguez, et al. 2007; Greilhuber et al. 2007).

Traditional Chinese medicine (TCM) is a system of medicine with the longest history in the world and it plays an important role in health maintenance within China and Asia. In recent years TCM has also become increasingly popular in the western world although there have been some problems arising from misunderstandings about what specific plant species are used in TCM and what standards they conform to (Tian 2011; Tu 2011). TCM has been developed over thousands of years of empirical testing and refinement and the compatibility and quality of the particular medicinal plant or animal species used is critical for its successful application. Indeed, selection of the wrong original medicinal plant in TCM can lead to unpredictable consequences (Xu 2011). Though there are lots of plant taxa that contain many of the same main active ingredients in one genus, specific plant species containing the most medicinal ingredients cannot be replaced in TCM. In recent years there has been increasing interest in the genetic diversity, and phylogenetic and evolutionary relationships between the medicinal plants that have been used for TCM (Li et al. 2012; Bai et al. 2013). One genomic character which has been poorly studied in species used for TCM is genome size, so there is little knowledge about how much variation there is in this character and how it co-varies with phenotypic characters and phylogenetic relationships in the same genus or across the family. Estimating C-values can therefore give us insights into the diversity of this genomic character for medicinal plants and how it varies.

In this study we report C-value estimates for 80 taxa of medicinal plants collected from the medicinal plant germplasm repository or field in Shaanxi province. Most of these reports (83%, 66 taxa) are new to the Plant DNA C-values Database. We had two goals in collecting these data. First, we sought to augment the amount of genome size data available for research generally. More specifically, we sought to start the construction of a database of C-values for Chinese traditional medicinal plant species to explore phylogenetic patterns of C-value variation and relationships between genome size and other qualitative characteristics or functional traits. This work therefore represents the first phase of a broader project to explore how genetic, phylogenetic and qualitative characteristics among medicinal plants vary in same genus or family.

Materials and methods

Plant material

We first identified a list of traditional Chinese medicinal plant species for which we had test data concerning genetic resources and pharmacological active ingredients. We sought to sample fresh leaf material from these species from across the region (Table 1). Fresh leaf material was stored at 4°C for no more than three days until it could be processed. For each sample, we collected a herbarium voucher serving as a permanent record (starting with DMP001) of the species identity, and deposited these at the herbarium in Shaanxi Normal University. The taxonomic identities of all field-collected material were confirmed by a medicinal botanist to ensure accurate identifications. We also collected small backup samples of leaf tissue in silica gel. These were used in the few cases where the fresh tissue did not provide a C-value and the DNA was extracted for molecular analysis.

Table 1. Provenance of the 80 plant species collected for this study in Shaanxi province (SN), China.

Location of sample collection	No. of samples	Latitude N range	Longitude E range
Germplasm repository of medicinal plant in Shaanxi Normal University, Xi’an, SN	21	Approximately 34°09′	Approximately 108°53′
Germplasm repository of medicinal plant in Xi’an Botanical Garden, SN	34	Approximately 34°12′	Approximately 108°57′
Wild germplasm resources field of medicinal plant in National Engineering Laboratories for Resource Developing of Endangered Chinese Crude Drugs in Northwest of China, Taibai county, Baoji city, SN	13	Approximately 34°03′	Approximately 107°18′
Foping county, SN	6	33°28′–33°32′	107°50′–107°59′
Taibai county, SN	3	34°02′–34°03′	107°18′–107°19′
Ningqiang county, SN	3	32°43′–34°48′	106°14′–106°23′

Estimating DNA C-values

We estimated 2C-values from leaf nuclei using flow cytometry with the fluorochrome propidium iodide (PI, Sigma®, USA, Pcode: 1001159523) as described by Doležel et al. (2007b). We relied primarily on the Otto and LB01 isolation buffers (Doležel et al. 1989; Otto 1990; Doležel and Gohde 1995) using the methods (reagent preparation, selection of standards, etc.) laid out initially by Otto (1990) and available on the flow cytometry methodology webpage (www.ibot.cas.cz/fcm/method.html).

In brief, we placed ~1 cm² of leaf tissue from both the sample and a known plant calibration standard into a 100 mm diameter Petri dish with 1.0–1.5 ml of ice-cold buffer (Otto I or LB01). We then finely chopped the tissue using a new Blade (Gillette ®, Shanghai, China) for one minute. After mixing this solution using a disposable graduated transfer pipet, we filtered it through a 30 μm disposable nylon filter (Celltrics®, Partec, GmBH, Munster, Germany) into a 1.5 ml round-bottom tube. The filter isolated the somatic nuclei from much of the cellular debris in the isolation buffer. For samples chopped in the Otto I buffer, the filtered suspension was centrifuged at 1000 g for 5 min at 4°C and the supernatant was carefully removed. Then 500 μl of Otto II stock solution (0.02 mg ml⁻¹ RNase + 0.02 mg ml⁻¹ PI) was added at room temperature. For samples chopped in the LB01 buffer 20 μl of the PI stock solution and 20 μl of an RNAase stock solution were added to the nuclei suspension (both stocks were 1 mg ml⁻¹, giving final concentrations of 0.05 mg ml⁻¹). The LB01 or Otto II suspensions were kept on ice. Immediately prior to analysis on the flow cytometer, the nuclei suspensions were vortex-mixed at 2000 rpm for 5–10 s and then placed onto a Guava flow cytometer. Typically, we prepared several samples of each species and analysed > 10,000 nuclei per sample to evaluated the coefficient of variation (where CV = SD/mean channel number, as Ormerod 2008). If the CV was more than 5%, we obtained further estimates until the CV was less than 5%. In general, the two-step procedure of Otto (1990) gave lower CVs and hence more accurate C-value estimates. The most likely reason for this is that the centrifugation of the samples in Otto I buffer removes complex secondary metabolites that can affect nucleus extraction, stability and PI staining. In cases where the Otto buffers did not provide a reliable C-value estimate, we tried using the LB01 buffer to extract nuclei. Overall, we used the Otto and LB01 isolation buffers to estimate C-values in 78 and two species respectively. The 2C-value for each sample was estimated using the following formula: (mean of sample peak/mean of standard peak) × 2C DNA amount (pg) of the calibration standard.

Internal calibration standards

We used three internal standards of different DNA content to calibrate our estimates: Oryza sativa L. subsp. japonica var. nippobare, Pisum sativum var. Bakana, and Vicia faba. We determined the 2C-values of the latter two species in our laboratory (8.32 and 26.57 pg, respectively) using Oryza sativa L. subsp. japonica var. nippobare (2C = 0.91 pg) as the primary reference standard. We grew plants of our three standards in the greenhouse to ensure access to fresh young leaves. To choose the best standard for a given sample, we followed the same protocol as described in Bai et al. (2012). The P. sativum standard, which generated reliable, reproducible, and discernible peaks with low CVs in our pilot tests, was first used to estimate C-values. If it failed, we turned to Oryza sativa and Vicia faba to measure the sample. Since the leaves of the medicinal plants often contain complex secondary metabolites it can be difficult to find the right combination of buffer and internal standard for accurate 2C estimations by FCM. In the few cases where the sample could not be reliably estimated using the approaches outlined above, we abandoned further efforts. In total, we used P. sativum, O. sativa, and V. faba as internal standards to estimate C-values of 55, 24, and one species, respectively.

Results

Accuracy and reliability of the estimated C-values

To assess the quality of the data generated, we compared our C-value estimates for 14 species whose C-values had been previously published (see Bennett and Leitch 2012; Table 2). The overall linear regression analysis showed that there was generally good agreement between the C-values estimated in the current work and those previously published (Figure 1, R ² = 0.91, p < 0.0001). For the subset of 10 values (71%) that agreed within 30%, the relationship was even tighter (Figure 1, R ² = 0.99, p < 0.0001). In the remaining four species, our estimates differed from previous C-value estimates by > 30%. Though there are differences of the estimation methods and internal calibration standards between our tests and previous references, the C-values of same plant taxa should not have a significant difference. The possible causes of such discrepancies are unclear, but may include intraspecific ploidy and dysploid variation in chromosome numbers, taxonomic discrepancies or genuine intraspecific variation. There were three species where our C-values were half the size or 4× as big as previous estimates. For example, our C-value estimates for Foeniculum vulgare Mill. (1C = 2.39 pg) and Equisetum hyemale L. (1C = 11.32 pg) were half the size of the values in the database (1C = 4.55 pg and 1C = 22.60 pg, respectively) (Bennett et al. 2005; Das and Mallick 1989) whereas the C-value of Cassia tora L. in the database (1C = 0.68 pg) was just one quarter the size of our estimate 2.85 pg (Ohri et al. 1986). We had confidence in our identifications of field-collected plants and all samples are vouchered. Indeed, such variation does highlight the importance of including proper vouchers in all rigorous studies of C-value variation.

Table 2. C-values of 14 species obtained in the current work and those from previous studies.

Taxon	1C-value (pg)		Estimation method	Ploidy	No. of chromosomes	Original reference
	Our test	Database
Bletilla striata (Thund.) Reichb. f.	2.62	2.95	FC : PI	—	—	Zonneveld et al. 2005
Cassia tora L.	2.85	0.68	Fe	2	26	Ohri et al. 1986
Cinnamomum camphora (L.) Nees & Eberm.	0.88	0.6	Fe	2	14	Nagl et al. 1977
Coix lacryma-jobi L.	1.59	1.63	Fe	4	20	Bennett and Smith 1976
Equisetum hyemale L.	11.32	26.3	FC : PI	2	216	Bennett et al. 2005
Eucommia ulmoides Oliv	0.56	0.74	Fe	2	34	Hanson et al. 2001
Foeniculum vulgare Mill.	2.39	4.55	Fe	2	22	Das and Mallick 1989
Hypericum perforatum L.	0.76	0.78	FC : PI	4	32	Temsch et al. 2010
Nandina domestica Thunb.	2.28	2.2	FC : PI	2	20	Bharathan et al. 1994
Pueraria lobata (Willd.) Ohwi.	1.21	1.1	FC : PI	2	22	Bennett et al. 2000
Ricinus communis L.	0.41	0.52	FC : PI	—	—	Houben et al. 2003
Tussilago farfara L.	2.45	2.3	Fe	2	60	Grime and Mowforth 1982
Hosta plantaginea (Lam.) Asch.	9.91	12.35	FC : PI	2	60	Zonneveld and Van Iren 2001
Pinellia pedatisecta Schott	1.4	1.22	FC : PI	—	—	Vesely et al. 2011

—: The ploidy and number of chromosome were not estimated in this reference.

Figure 1. Comparisons of 1C DNA amounts of 14 taxa tested in this study versus values for the same species taken from the Plant DNA C-values Database (Bennett and Leitch 2012).

Reported C-values of Chinese medicinal plants

Appendix Table A1 lists the C-values for the 80 Chinese medicinal plant species studied in this work. Of these, 66 (83%) comprise reports for taxa with no previously reported C-value as of release 6.0, December 2012 (Bennett and Leitch 2012). The range of 1C-values reported here (0.20–25.2 pg; Figure 2) covers a substantial part of the variation in 1C-values reported in the Plant DNA C-values Database (0.0648–152.23 pg) (Greilhuber et al. 2006; Pellicer et al. 2010). These new C-values represent a valuable addition to the global pool of information on plant genome sizes, with an especially significant addition to knowledge of this character in species used in TCM. The data include several first values at the level of genus. For example, 27 of the 48 genera in 38 families represent new reports at that level for the C-value Plant DNA C-values Database. The C-values of medicinal plant taxa in new genera will give valuable references for estimating other plant C-values and revealing the phylogenetics of total plant taxa.

Figure 2. Distribution of 1C-values of the 80 medicinal plants included in this study (from 0.2 to 25.2 pg).

Discussion

Genome size, as reflected in these plant C-values, represents a key diversity character as well as one that is often associated with other traits such as nuclear and cell size, seed mass, specific leaf area, growth rate and /or cell- and life-cycle length (see Introduction). To better understand the chemical diversity, genetic diversity and phylogenetic relationships of medicinal plant species in the same genus or family, we are also quantifying an array of other attributes for many of the 80 taxa reported here. These include analyses of their karyotypes, chemical composition as well as RNA sequence data for plant taxa in the same genus. Together these data will allow us to gain greater insight into the genomic diversity and phylogenetic relationships among these medicinal plants and compare them with their non-medicinal relatives in a genus or family. This will allow us to analyze how genome size co-varies with these traits. And furthermore, knowledge of a medicinal plant species’ genome size is essential for many genomic studies such as those aiming to embark on complete genome sequencing, transcriptome studies, repetitive DNA characterization, and AFLP and microsatellite analyses for population genetics (Bennett and Leitch 2011; Kelly and Leitch 2011; Kelly et al. 2012; Vallès et al. 2013). Although C-value or genome size data are still available for only a small part of the medicinal plants, future analysis will permit us to postulate some hypotheses about systematic, phylogenetic and evolutionary aspects of the genome size (C-value) or chemical diversity of medicinal plants with the data accumulating. For example, we firstly aim to characterize patterns of phenotypic variation, karyotype diversity, genetic diversity by AFLP, chemical composition, phylogenetic relationship and RNA sequences within at least 10 of species of Scutellaria so that we can examine whether genome sizes are associated with such traits. Collectively, these and further studies will extend our ability to understand how genome size varies with phylogenetic, chemical components and genetic diversity.

Appendix. Table A1. C-values of 80 Chinese traditional medicinal plants.

Table

New?	Taxon	Family	Order	Class	Life cycle	1C	1C	2C	Standard	Voucher
						（Mbp)	（pg）	（pg）
+	Aesculus chinensis Bunge	Sapindaceae	Sapindales	Dic	P	595	0.61	1.22	Pis	DMP062
++	Akebia trifoliate (Thunb.) Koidz.	Lardizabalaceae	Ranunculales	Dic	P	743	0.76	1.52	Pis	DMP074
+	Amorphophallus rivieri Durieu ex Carriere	Araceae	Alismatales	Mon	P	193	0.20	0.39	Pis	DMP087
++	Arctium lappa L.	Asteraceae	Asterales	Dic	B	971	0.99	1.99	Ory	DMP024
+	Asarum pulchellum Hemsl.	Aristolochiaceae	Piperales	Dic	P	2975	3.04	6.08	Ory	DMP020
+	Asarum sieboldii Miq.	Aristolochiaceae	Piperales	Dic	P	2594	2.65	5.30	Ory	DMP006
+	Asarum porphyronotum var. atrovirens	Aristolochiaceae	Piperales	Dic	P	3149	3.22	6.44	Ory	DMP021
+	Asparagus cochinchinensis (Lour.) Merr.	Asparagaceae	Asparagales	Mon	P	2397	2.45	4.90	Ory	DMP054
++	Atractylodis chinensis (DC.) Koidz.	Asteraceae	Asterales	Dic	P	2654	2.71	5.43	Ory	DMP022
+	Berberis gilgiana Fedde	Berberidaceae	Ranunculales	Dic	P	2132	2.18	4.36	Pis	DMP045
+	Berberis soulieana Schneid.	Berberidaceae	Ranunculales	Dic	P	1345	1.38	2.75	Pis	DMP043
–	Bletilla striata (Thund.) Reichb. f.	Orchidaceae	Asparagales	Mon	P	2565	2.62	5.25	Ory	DMP019
++	Caragana sinica (Buc’hoz) Rehd.	Fabaceae	Fabales	Dic	P	2443	2.50	5.00	Ory	DMP035
–	Cassia tora L.	Fabaceae	Fabales	Dic	A	2784	2.85	5.69	Ory	DMP023
+	Celtis bungeana Bl.	Cannabaceae	Rosales	Dic	P	8183	8.37	16.73	Pis	DMP030
++	Chimonanthus praecox (L.) Link	Calycanthaceae	Laurales	Dic	BP	834	0.85	1.71	Pis	DMP034
–	Cinnamomum camphora (L.) Nees & Eberm.	Lauraceae	Laurales	Dic	P	864	0.88	1.77	Pis	DMP041
++	Clerodendrum trichotomum Thunb. ex A. Murray	Lamiaceae	Lamiales	Dic	P	1131	1.16	2.31	Pis	DMP036
–	Coix lacryma-jobi L.	Poaceae	Poales	Mon	AB	1555	1.59	3.18	Ory	DMP061
+	Cornus officinalis Sieb.et Zucc.	Cornaceae	Cornales	Dic	P	2946	3.01	6.02	Vic	DMP015
+	Dendrobium officinale Kimura et Migo	Orchidaceae	Asparagales	Mon	P	4196	4.29	8.58	Ory	DMP073
+	Deutzia acabra Thunb.	Hydrangeaceae	Cornales	Dic	P	420	0.43	0.86	Pis	DMP067
+	Dioscorea zingiberensis C. H. Wright	Dioscoreaceae	Dioscoreales	Mon	P	971	0.99	1.99	Pis	DMP025
++	Diphylleia sinensis H.L.Li	Berberidaceae	Ranunculales	Dic	P	521	0.53	1.07	Pis	DMP096
++	Distylium chinense (Fr.) Diels.	Hamamelidaceae	Saxifragales	Dic	P	551	0.56	1.13	Pis	DMP037
–	Equisetum hyemale L.	Equisetaceae	Equisetales	Equ	P	11071	11.32	22.63	Pis	DMP099
++	Eribotrya japonica (Thunb.) Lindl.	Rosaceae	Rosales	Dic	P	829	0.85	1.70	Pis	DMP064
–	Eucommia ulmoides Oliv	Eucommiaceae	Garryales	Dic	P	551	0.56	1.13	Pis	DMP047
+	Eupatorium fortunei Turcz	Asteraceae	Asterales	Dic	P	3880	3.97	7.94	Ory	DMP060
++	Evodia rutaecarpa (Juss.) Benth.	Rutaceae	Sapindales	Dic	P	4949	5.06	10.12	Ory	DMP071
–	Foeniculum vulgare Mill.	Apiaceae	Apiales	Dic	BP	2339	2.39	4.78	Pis	DMP088
+	Gardenia jasminoides Ellis	Rubiaceae	Gentianales	Dic	P	695	0.71	1.42	Pis	DMP083
+	Gentiana macrophylla Pall.	Gentianaceae	Gentianales	Dic	P	1743	1.78	3.56	Pis	DMP010
+	Gentiana macrophylla Pall. var. fetissowii (Regel et Winkl.) Ma et K.C.Hsia	Gentianaceae	Gentianales	Dic	P	2240	2.29	4.58	Pis	DMP094
++	Gynostemma pentaphyllum（Thunb.) Makino	Cucurbitaceae	Cucurbitales	Dic	P	1771	1.81	3.62	Pis	DMP004
++	Heracleum moellendorffii Hance	Apiaceae	Apiales	Dic	P	4505	4.61	9.21	Ory	DMP072
–	Hosta plantaginea (Lam.) Asch.	Asparagaceae	Asparagales	Mon	P	9692	9.91	19.81	Ory	DMP058
–	Hypericum perforatum L.	Hypericaceae	Malpighiales	Dic	P	740	0.76	1.51	Pis	DMP093
+	Ilex cornuta Lindl.ex Paxton	Aquifoliaceae	Aquifoliales	Dic	P	640	0.65	1.31	Pis	DMP048
+	Iris tectorum Maxim	Iridaceae	Asparagales	Mon	P	1042	1.07	2.13	Pis	DMP091
+	Isatis indigotica Fortune	Brassicaceae	Brassicales	Dic	B	447	0.46	0.91	Pis	DMP009
++	Leonurus japonicus Houtt.	Lamiaceae	Lamiales	Dic	AB	542	0.55	1.11	Pis	DMP056
++	Libanotis spodotrichoma K.T.Fu	Apiaceae	Apiales	Dic	P	1658	1.70	3.39	Pis	DMP092
+	Ligustrum quihoui Carr.	Oleaceae	Lamiales	Dic	P	1392	1.42	2.85	Pis	DMP039
+	Lonicera fragrantissima Lindl.et Paxt.	Caprifoliaceae	Dipsacales	Dic	P	818	0.84	1.67	Pis	DMP027
+	Lonicera japonica L.	Caprifoliaceae	Dipsacales	Dic	P	700	0.72	1.43	Pis	DMP008
+	Lonicera maackii (Rupr.) Maxim.	Caprifoliaceae	Dipsacales	Dic	P	1119	1.14	2.29	Pis	DMP029
++	Mahonia confusa Sprague	Berberidaceae	Ranunculales	Dic	P	1276	1.31	2.61	Pis	DMP044
+	Mentha rotundifolia (L.) Huds.	Lamiaceae	Lamiales	Dic	P	626	0.64	1.28	Pis	DMP055
–	Nandina domestica Thunb.	Berberidaceae	Ranunculales	Dic	P	2229	2.28	4.56	Pis	DMP032
+	Notholirion bulbuliferum (Lingelsh.ex H.Limpricht) Steam	Liliaceae	Liliales	Mon	P	24624	25.18	50.36	Pis	DMP097
++	Orixa japonica Thunb.	Rutaceae	Sapindales	Dic	P	1792	1.83	3.66	Pis	DMP042
++	Perilla frutescens (L.) Britt.	Lamiaceae	Lamiales	Dic	A	1395	1.43	2.85	Pis	DMP052
++	Phellodendron amurense Rupr.	Rutaceae	Sapindales	Dic	P	2764	2.83	5.65	Ory	DMP046
++	Photinia serrulata Lindl.	Rosaceae	Rosales	Dic	P	981	1.00	2.01	Pis	DMP031
+	Phytolacca acinosa Roxb.	Phytolaccaceae	Caryophyllales	Dic	P	1230	1.26	2.52	Pis	DMP049
–	Pinellia pedatisecta Schott	Araceae	Alismatales	Mon	P	1366	1.40	2.79	Pis	DMP057
++	Platycodon grandiforus(Jacq.)A.DC.	Campanulaceae	Asterales	Dic	P	587	0.60	1.20	Pis	DMP051
–	Pueraria lobata (Willd.) Ohwi.	Fabaceae	Fabales	Dic	P	1183	1.21	2.42	Pis	DMP078
++	Pyrrosia lingua (Thunb.) Farwell	Polypodiaceae	Polypodiales	Lep	P	9921	10.14	20.29	Ory	DMP082
++	Reineckea carnea (Andr.) Kunth	Asparagaceae	Asparagales	Mon	P	1270	1.30	2.60	Pis	DMP066
++	Reynoutria japonica Houtt.	Polygonaceae	Caryophyllales	Dic	P	760	0.78	1.55	Pis	DMP007
+	Ribes odoratum Wendl	Grossulariaceae	Saxifragales	Dic	P	833	0.85	1.70	Pis	DMP040
–	Ricinus communis L.	Euphorbiaceae	Malpighiales	Dic	AB	398	0.41	0.81	Pis	DMP053
+	Salvia miltiorrhiza Bunge	Lamiaceae	Lamiales	Dic	P	2007	2.05	4.10	Ory	DMP013
+	Schisandra sphenanthera Rehd.et Wils.	Schisandraceae	Austrobaileyales	Dic	P	7208	7.37	14.74	Pis	DMP012
+	Scrophularia ningpoensis Hemsl.	Scrophulariaceae	Lamiales	Dic	P	3028	3.10	6.19	Ory	DMP063
+	Scutellaria baicalensis Georgi	Lamiaceae	Lamiales	Dic	P	561	0.57	1.15	Pis	DMP016
+	Scutellaria viscidula Bunge	Lamiaceae	Lamiales	Dic	P	424	0.43	0.87	Pis	DMP017
+	Sedum aizoon L.	Crassulaceae	Saxifragales	Dic	P	299	0.31	0.61	Pis	DMP002
+	Sedum spectabile Boreau	Crassulaceae	Saxifragales	Dic	P	1817	1.86	3.72	Ory	DMP089
++	Silybum marianum (L.) Gaertn.	Asteraceae	Asterales	Dic	AB	748	0.76	1.53	Ory	DMP005
+	Taxus chinensis (Pilger) Rehd.	Taxaceae	Taxales	Tax	P	7575	7.75	15.49	Ory	DMP018
++	Tetrapanax papyriferus (Hook.) K.Koch.	Araliaceae	Apiales	Dic	P	1323	1.35	2.71	Pis	DMP068
++	Toricellia angulata Oliv.var.intermedia (Harms) Hu	Torricelliaceae	Apiales	Dic	P	1775	1.82	3.63	Pis	DMP038
–	Tussilago farfara L.	Asteraceae	Asterales	Dic	P	2394	2.45	4.90	Pis	DMP090
+	Urtica fissa E.Pritz.	Urticaceae	Rosales	Dic	P	848	0.87	1.73	Ory	DMP070
+	Viburnum rhytidopayllum Hembl.	Adoxaceae	Dipsacales	Dic	P	3525	3.60	7.21	Ory	DMP033
++	Xanthoceras sorbifolia Bunge	Sapindaceae	Sapindales	Dic	P	493	0.50	1.01	Pis	DMP065
+	Zingiber mioga (Thunb.) Roscoe	Zingiberaceae	Zingiberales	Mon	P	23814	24.35	48.70	Pis	DMP086

The format of this table is modified from that used by Bennett and colleagues (Bennett and Leitch 1997, 2011; Bennett et al. 2000; Zonneveld et al. 2005 – see main text for references). Notes on its structure are as follows.

• “New” reports at specific and generic levels. Taxa with C-values first reported here (i.e. for which no previous C-value has been published for this species; Bennett and Leitch 2012) are indicated with “+” and appear in bold text; “+ +” indicates that the C-value also is the first report for the genus; “–” indicates that at least one C-value for the taxon has already been published.

• Taxa. Names of taxa correspond generally to those provided in the Flora Republicae Popularis Sinicae (http://frps.plantphoto.cn/) and the Directory of Chinese medicinal plants.

• Family, order, and class. The family and order assigned to angiosperms correspond with assignments under the Angiosperm Phylogeny Group system (APG III 2009; Stevens 2012). Dic = dicotyledoneae; Mon = monocotyledonae; Equ = Equisetopsida; Lep = Leptosporangiopsida; Taxus = Taxopsida.

• Life cycle types. Information on the type of life cycle for each taxon was gleaned from the literature or from www.plants.usda.gov/classification.htm: A = annual; B = biennial; P = perennial; AP = annual–perennial (including annual–biennial); BP = biennial–perennial.

• DNA amounts and conversion factors. 1C-values were calculated from the available 2C-values. For 1C-values given in megabase pairs (Mbp), we used the conversion factor of 1 pg = 978 Mb (Doležel et al. 2003).

• Buffers. We relied primarily on the Otto and LB01 isolation buffers (Doležel et al. 1989; Otto 1990; Doležel and Gohde 1995) using the methods (reagent preparation, selection of standards, etc.) laid out initially by Otto (1990) and available on the flow cytometry methodology webpage (www.ibot.cas.cz/fcm/method.html).

• Vouchers. This study is part of a larger Diversity of Medicinal Plants (DMB) project at the Shaanxi Normal University (SNNU). To permanently document the taxonomic identity of the source material, and to serve as a reference point for future changes in determinations or nomenclature, we collected herbarium vouchers and deposited these at the herbarium in SNNU.

Acknowledgments

This work was partially funded by Natural Science Foundation of China (No. 31100241), Shaanxi science and technology plan projects (2011K16-02-05), Xi’an key scientific and technological project (NC1116 (1)) and Innovation funds of graduate programs, SNNU (2013CXS017). The authors thank Dr. Leitch IJ (Royal Botanic Gardens, UK) for her kind revisions on the manuscript.