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Study on the DNA Barcoding of Genus Ligularia Cass. (Asteraceae)

菊科橐吾属植物的DNA条形码研究



全 文 :菊科橐吾属植物的 DNA条形码研究∗
何维颖1ꎬ2ꎬ3ꎬ 潘跃芝1ꎬ2∗∗
(1 中国科学院昆明植物研究所资源植物与生物技术重点实验室ꎬ 昆明  650201ꎻ 2 云南省野生资源
植物研发重点实验室ꎬ 昆明  650201ꎻ 3 中国科学院大学ꎬ 北京  100049)
摘要: DNA条形码是一项利用短的、 标准的 DNA片段对物种进行快速、 有效识别和鉴定的新技术ꎮ 菊科
橐吾属约 140种ꎬ 是典型的高山植物ꎬ 种间杂交频繁ꎬ 形态变异复杂ꎬ 从形态学方面鉴定近缘种较为困
难ꎮ 本研究选取 4个 DNA核心条形码片段 (ITSꎬ matKꎬ psbA ̄trnH和 rbcL)ꎬ 对橐吾属 35种 144个个体进
行条形码研究ꎮ 研究结果显示叶绿体基因 matKꎬ psbA ̄trnH和 rbcL在种内和种间变异都很小ꎬ 对橐吾属的物
种鉴定率极低ꎻ ITS在种间变异率相对较大ꎬ 物种鉴定率为 60%ꎮ 而各片段联合后的物种鉴定率并未提高ꎮ
关键词: DNA条形码ꎻ 橐吾属ꎻ 物种鉴别ꎻ ITSꎻ matKꎻ psbA ̄trnHꎻ rbcL
中图分类号: Q 949ꎬ Q 781          文献标志码: A          文章编号: 2095-0845(2015)06-693-11
Study on the DNA Barcoding of Genus Ligularia Cass. (Asteraceae)∗
HE Wei ̄ying1ꎬ2ꎬ3ꎬ PAN Yue ̄zhi1ꎬ2∗∗
(1 Key Laboratory for Economic Plants and Biotechnologyꎬ Kunming Institute of Botanyꎬ Chinese Academy of Sciencesꎬ
Kunming 650201ꎬ Chinaꎻ 2 Yunnan Key Laboratory for Wild Plant Resourcesꎬ Kunming 650201ꎬ Chinaꎻ
3 University of Chinese Academy of Sciencesꎬ Beijing 100049ꎬ China)
Abstract: DNA barcoding is a new technology which can identify species rapidly based on short and standardized
DNA sequences. Ligulariaꎬ a genus of Asteraceae with about 140 speciesꎬ exhibits high morphological and ecological
diversityꎬ which makes the classification and species delimitation difficultꎬ especially in the cases of closely related
taxa. In this studyꎬ we tested four DNA core barcoding regions ( ITSꎬ matKꎬ psbA ̄trnH and rbcL) in 144 samples
representing 35 species of Ligularia. The results revealed that the chloroplast regions (matKꎬ psbA ̄trnH and rbcL)
have extremely low species identification rate due to low interspecific variation. Converselyꎬ ITS sequence showed
higher species identification rate (60%) and could discriminate the species which are difficult to identify. The com ̄
bination of these four gene fragments did not improve the ability of species discrimination.
Key words: DNA barcodingꎻ Ligulariaꎻ species identificationꎻ ITSꎻ matKꎻ psbA ̄trnHꎻ rbcL
  DNA barcoding is a new technology which can
identify species rapidly based on a short and stand ̄
ardized DNA sequence (Hebert et al.ꎬ 2003ꎻ Kress
et al.ꎬ 2005ꎻ Hollingsworthꎬ 2011ꎻ Schoch et al.ꎬ
2012). This technology has been widely used as a
tool for species identification and discovery of cryptic
species ( Zemlak et al.ꎬ 2009ꎻ Liu et al.ꎬ 2011ꎻ
Huemer et al.ꎬ 2014) since it was proposed (Hebert
et al.ꎬ 2003). At presentꎬ the mitochondrial gene
cytochrome c oxidase I (COI) has been proven to be
a universal and effective barcode for discriminating
species in animalsꎬ such as birds ( Hebert et al.ꎬ
2003ꎬ 2004)ꎬ fishes (Ward et al.ꎬ 2005)ꎬ insects
(Linares et al.ꎬ 2009). Howeverꎬ gene COI can not
植 物 分 类 与 资 源 学 报  2015ꎬ 37 (6): 693~703
Plant Diversity and Resources                                    DOI: 10.7677 / ynzwyj201515082

∗∗
Funding: The National Natural Science Fundation of China (31470336)ꎬ Large ̄Scale Scientific Facilities Research Project of Chinese
Academy of Sciences (2009 ̄LSFG130WS ̄01)
Author for correspondenceꎻ E ̄mail: panyuezhi@mail􀆰 kib􀆰 ac􀆰 cn
Received date: 2015-03-27ꎬ Accepted date: 2015-09-21
作者简介: 何维颖 (1988-) 男ꎬ 硕士研究生ꎬ 主要从事橐吾属的分子生物学研究ꎮ E ̄mail: heweiying@mail􀆰 kib􀆰 ac􀆰 cn
be applied in most of plant taxa because of the low
substitution rate (Kress et al.ꎬ 2005). No DNA re ̄
gion universally suitable and meeting all of the nec ̄
essary criteria has been found for all plants (Fazekas
et al.ꎬ 2008ꎻ Hollingsworth et al.ꎬ 2011ꎻ Li et al.ꎬ
2011). Searching for DNA barcode in plants proved
to be a more challenging task (Kress et al.ꎬ 2005ꎻ
Chase et al.ꎬ 2007ꎻ Kress and Ericksonꎬ 2007ꎻ La ̄
haye et al.ꎬ 2008). Based on the previous researchꎬ
rbcL + matK has been suggested to be the core plant
barcode by the Consortium for the Barcode of life
(CBOL) Plant Working Group (PWG) (CBOL Plant
Working Groupꎬ 2009). The China plant work group
for the Barcode of life proposed that ITS / ITS2 should
be incorporated into the core barcode for seed plants
according to the study in 1 757 species of 75 families
(Li et al.ꎬ 2011). And Chen et al. ( 2010) also
found that the ITS2 performed well in the identifica ̄
tion of medicinal plants. In additionꎬ the plastid in ̄
tergenic spacer region psbA ̄trnH was recommended
as a candidate barcode (Hollingsworth et al.ꎬ 2011).
The four core barcodes ( rbcLꎬ matKꎬ psbA ̄
trnH and ITS) have been proved to have highly uni ̄
versal primers and high species identification rate in
some plant groups (Kress et al.ꎬ 2005ꎬ 2009ꎻ Kress
and Ericksonꎬ 2007ꎻ Fazekas et al.ꎬ 2008ꎻ Lahaye
et al.ꎬ 2008ꎻ Newmaster et al.ꎬ 2006ꎻ 2008ꎻ Holl ̄
ingsworth et al.ꎬ 2009ꎻ Jiao and Shuiꎻ 2013ꎻ Liu et
al.ꎬ 2013)ꎬ but there are still debate about these
DNA regions as barcodes. Of the four single ̄marker
barcodes for plantsꎬ for exampleꎬ ITSꎬ as a standard
barcodeꎬ is often questioned because of the potential
fungal contamination and the presence of paralogous
copies (Hollinsworth et al.ꎬ 2011). Howeverꎬ the
research work including 6 286 individuals represen ̄
ting 1 757 species in 141 genera of 75 families re ̄
vealed that ITS region performed the highest resolu ̄
tion in species discrimination of seed plants ( Li et
al.ꎬ 2011). Although rbcL showed good universali ̄
tyꎬ its variation mainly existed above the species lev ̄
el and exhibited low species identification ability
(Gonzalez et al.ꎬ 2009). MatK showed high species
identification ability in the study of Lahaye et al.
(2008) and De Vere et al. (2012) with low primer
generalityꎬ but it performed extremely low species i ̄
dentification rate in Berberis and Ligustrum (Roy et
al.ꎬ 2010ꎻ Gu et al.ꎬ 2011). DNA segment psbA ̄
trnH had high sequence variation in angiosperms
(Kress et al.ꎬ 2005)ꎬ and was considered perfect as a
DNA barcode (Chase et al.ꎬ 2007ꎻ Roy et al.ꎬ 2010).
Howeverꎬ its identification ability was poor in the
medicinal plants Paris (Zhu et al.ꎬ 2010)ꎬ and the
sequence alignment was difficult because of the se ̄
quence structure variation (Kress et al.ꎬ 2005ꎻ Zhu
et al.ꎬ 2010).
Ligularia Cass.ꎬ belonging to the family Aster ̄
aceaeꎬ tribe Senecioneaeꎬ subtribe Tussilagininaeꎬ
is a highly diversified genus. It includes six sections
and about 140 species (Liuꎬ 2011)ꎬ and most of which
are distributed in Asia with only two species in Eu ̄
rope (Liuꎬ 1989ꎻ Liu et al.ꎬ 1994). Liu (1985ꎬ
1989) studied the Chinese species of Ligularia com ̄
prehensively and systematicallyꎬ and 112 species
were describedꎬ of which 67 species were distributed
in Hengduan mountainous area with 61 species en ̄
demic to this area. The Hengduan mountains were
considered to be the center of evolution and diversity
for Ligularia (Liu et al.ꎬ 1994). The plants of this
genus exhibit remarkably morphological variation in
leaf shape and textureꎬ indumenta and inflorescence
among species. One species may present significant
diversification in different populations. For exampleꎬ
Ligularia sibiricaꎬ the type species of this genusꎬ
has diversified leaf blade with ovate ̄cordateꎬ trian ̄
gular ̄cordateꎬ reniform ̄cordateꎬ or broadly cordate
shape (Liuꎬ 1989). This makes it difficult to iden ̄
tificate Ligularia species with traditional morphology ̄
based methodsꎬ especially in the vegetative period of
this taxa. DNA barcode technology can overcome this
issueꎬ and it only needs a small part of the organism
tissue (e􀆰 g. a piece of leaf blade) to rapidly identify
species. In this studyꎬ we tested the discriminatory
power of four DNA fragments (ITSꎬ matKꎬ rbcL and
psbA ̄trnH) and evaluated the DNA barcoding per ̄
496                                  植 物 分 类 与 资 源 学 报                            第 37卷
formance in species identification for the genus Ligu ̄
laria.
1  Materials and methods
1􀆰 1  Experimental materials
A total of 144 individuals of 35 species from
Yunnanꎬ Sichuanꎬ Qinghai and Gansu province were
collectedꎬ and each species included at least two in ̄
dividuals ( Table 1). The voucher specimens were
deposited in Herbarium of Kunming Institute of Bota ̄
nyꎬ CAS (KUN). Specimen identification was based
on the classification system of Liu (1989).
1􀆰 2  Experimental methods
Total DNA was extracted from silica ̄gal dried
leaf tissues using the CTAB method ( Doyle and
Doyleꎬ 1987). Informations about the primers used
in the present study are listed in Table 2. The PCR
profiles for three chloroplast DNA fragments (matKꎬ
psbA ̄trnH and rbcL) included an initial denatur ̄
ation step at 94 ℃ for 5 minꎬ followed by 30 cycles
of 30 s at 94 ℃ꎬ 30 s at 53 ℃ꎬ 1 min at 72 ℃ and
finished with an extension step of 7 min at 72 ℃ .
The PCR conditions for ITS consisted of an initial
denaturation at 56 ℃ for 5 minꎬ followed by 30 cy ̄
cles of 30 s at 94 ℃ꎬ 30 s at 53 ℃ꎬ 1 min at 72 ℃
and finished with an extension step of 7 min at
72 ℃ . The PCR reaction system was carried out in a
total volume of 20 μL contained 13􀆰 1 μL of ultrapure
waterꎬ 2􀆰 0 μL 10 × PCR bufferꎬ 1􀆰 0 μL MgCl2ꎬ
1􀆰 0 μL dNTPꎬ 1􀆰 0 μL BSAꎬ 0􀆰 3 μL Taq polymer ̄
aseꎬ 0􀆰 3 μL each primerꎬ 1􀆰 5 μL template DNA
(20-60 ng). The purified PCR products were run
on an ABI 3730 automated sequencerꎬ completed by
sequencing company.
Table 1  The information of the samples
Species name Sample ID Locality Latitude Longitude Atitude / m
L􀆰 hodgsonii PG100806 Miyaluoꎬ Li Countyꎬ Sichuan N31°38′18″ E102°49′10″ —
L􀆰 hodgsonii PG100869 Guandiꎬ Dangchang Countyꎬ Gansu N34°15′13″ E104°11′21″ 2293
L􀆰 hodgsonii PG100871 Wen Countyꎬ Gansu N33°05′21″ E104°45′51″ 1462
L􀆰 stenoglossa PG090978 Laojun Mountainꎬ Yulongꎬ Yunnan N26°39′28″ E99°48′20″ 3039
L􀆰 stenoglossa PG100961 Cangshanꎬ Daliꎬ Yunnan N25°40′48″ E100°05′41″ 3760
L􀆰 duciformis PG090905 Xiaozhongdianꎬ Shangri ̄Laꎬ Yunnan N27°38′32″ E99°47′48″ 3607
L􀆰 duciformis PG110810 Jiajinshanꎬ Baoxingꎬ Sichuan N30°51′25″ E102°41′23″ 3910
L􀆰 duciformis PG110820 Dambaꎬ Sichaun N30°32′06″ E101°35′55″ 3750
L􀆰 duciformis PG110873 Tianchiꎬ Shangri ̄Laꎬ Yunnan — — 3890
L􀆰 nelumbifolia PG090924 Xiaoxueshanꎬ Shangri ̄Laꎬ Yunnan N28°18′54″ E99°45′12″ 3872
L􀆰 nelumbifolia PG090934 Bealockꎬ Daxueshanꎬ Yunnan N28°35′46″ E99°50′09″ 4173
L􀆰 nelumbifolia PG100816 Zhegushanꎬ Hongyuanꎬ Sichuan N31°52′40″ E102°40′14″ 3984
L􀆰 nelumbifolia PG100820 Li Countyꎬ Sichuan N32°19′31″ E102°27′09″ 3694
L􀆰 nelumbifolia PG100828 Hongyuanꎬ Sichuan N32°42′30″ E102°08′50″ 3748
L􀆰 nelumbifolia PG110812 Balangshanꎬ Wenchuanꎬ Sichuan N30°54′27″ E102°53′60″ 4300
L􀆰 nelumbifolia PG110825 Ganziꎬ Sichuan N31°36′56″ E100°12′48″ 3930
L􀆰 nelumbifolia PG110843 Queershanꎬ Baiyu Countyꎬ Sichuan N31°24′50″ E99°56′02″ 4330
L􀆰 purdomii PG100833 Gemoxiangꎬ Abaꎬ Sichuan N333°02′03″ E101°33′29″ 3429
L􀆰 purdomii PG100838 Jiuzhiꎬ Qinghai N33°24′25″ E101°25′39″ 3708
L􀆰 purdomii PG100843 Tangkexiangꎬ Abaꎬ Sichuan N33°02′57″ E102°17′13″ 3562
L􀆰 yunnanensis PG090982 Laojun Mountainꎬ Yulongꎬ Yunnan N26°37′55″ E99°43′28″ 3845
L􀆰 yunnanensis PG100963 Cangshanꎬ Daliꎬ Yunnan N25°40′45″ E100°05′36″ 3780
L􀆰 atroviolacea PG100907 Yanchengꎬ Sichuan N27°41′14″ E101°13′24″ 3250
L􀆰 atroviolacea PG100951 Wenhaiꎬ Lijiangꎬ Yunnan N26°58′44″ E100°10′25″ 3120
L􀆰 cymbulifera PG090910 Haba Snow Mountainꎬ Yunnan N27°40′07″ E99°48′32″ 3888
L􀆰 cymbulifera PG090915 Gezaxiangꎬ Shangri ̄Laꎬ Yunnan N28°02′52″ E99°45′56″ 3164
L􀆰 cymbulifera PG090936 Dongwangꎬ Shangri ̄Laꎬ Yunnan N28°36′55″ E99°49′19″ 3749
L􀆰 cymbulifera PG090937 Wumingshanꎬ Xiangchengꎬ Sichuan N29°07′20″ E100°00′54″ 4130
L􀆰 cymbulifera PG090950 Litangꎬ Sichuan N29°47′51″ E100°01′22″ —
L􀆰 cymbulifera PG090962 Daochengꎬ Sichuan N29°07′43″ E100°10′59″ 3848
L􀆰 cymbulifera PG090975 Baimaxueshanꎬ Deqinꎬ Yunnan N28°24′01″ E98°58′58″ 4141
L􀆰 lapathifolia PG100920 Muliꎬ Sichuan N28°07′01″ E101°05′57″ 3130
L􀆰 lapathifolia PG100922 Wachang Streetꎬ Muliꎬ Sichuan N28°06′19″ E100°49′05″ 2580
5966期              HE and PAN: Study on the DNA Barcoding of Genus Ligularia Cass. (Asteraceae)              
Table 1 continued
Species name Sample ID Locality Latitude Longitude Atitude / m
L􀆰 lapathifolia PG100942 Suberbꎬ Lijiangꎬ Yunnan — — —
L􀆰 tongolensis PG090906 Haba Snow Mountainꎬ Yunnan N27°38′53″ E99°47′53″ 3717
L􀆰 tongolensis PG090946 Chituxiangꎬ Daochengꎬ Sichuan N28°40′18″ E100°14′24″ 3474
L􀆰 tongolensis PG090949 Litangꎬ Sichuan N29°47′51″ E100°21′21″ 3815
L􀆰 tongolensis PG090965 Yadingꎬ Daochengꎬ Sichuan N28°30′41″ E100°20′51″ 3985
L􀆰 vellerea PG090911 Haba Snow Mountainꎬ Yunnan N27°39′29″ E99°47′56″ 3805
L􀆰 vellerea PG090914 Zagexiangꎬ Shangri ̄Laꎬ Yunnan N28°07′43″ E99°49′47″ 3711
L􀆰 vellerea PG090932 Daxueshanꎬ Shangri ̄Laꎬ Yunnan N28°34′17″ E99°49′49″ 4131
L􀆰 sibirica PG100812 Zhegushanꎬ Hongyuanꎬ Sichuan N31°53′13″ E102°40′07″ 3900
L􀆰 sibirica PG100857 Songfanꎬ Sichuan N32°53′04″ E103°29′03″ 3230
L􀆰 sibirica PG110876 Tianchiꎬ Shangri ̄Laꎬ Yunnan — — 3890
L􀆰 cyathiceps PG090904 Xiaozhongdianꎬ Shangri ̄Laꎬ Yunnan N27°38′32″ E99°47′48″ 3602
L􀆰 cyathiceps PG110872 Tianchiꎬ Shangri ̄Laꎬ Yunnan — — 3890
L􀆰 lamarum PG100829 Hongyuanꎬ Sichuan N32°43′34″ E102°06′32″ 3911
L􀆰 lamarum PG100945 Xuesongcunꎬ Lijiangꎬ Yunnan N27°02′19″ E100°12′08″ 3140
L􀆰 lamarum PG100962 Cangshanꎬ Daliꎬ Yunnan N25°40′63″ E100°05′34″ 3800
L􀆰 subspicata PG090912 Haba Snow Mountainꎬ Yunnan N27°39′29″ E99°47′56″ 3802
L􀆰 subspicata PG090925 Xiaoxueshanꎬ Shangri ̄Laꎬ Yunnan N28°18′53″ E99°45′01″ 3871
L􀆰 subspicata PG090938 Wumingshanꎬ Xiangchengꎬ Sichuan N29°07′14″ E100°01′23″ 4202
L􀆰 subspicata PG090959 Haizishanꎬ Daochengꎬ Sichuan N29°20′13″ E100°06′01″ 4352
L􀆰 subspicata PG090972 Dashanꎬ Xiangchengꎬ Sichuan N29°07′53″ E99°36′48″ 3762
L􀆰 subspicata PG090981 Laojun Mountainꎬ Yulongꎬ Yunnan N26°37′55″ E99°43′27″ 3846
L􀆰 subspicata PG100915 Changhaiziꎬ Muliꎬ Sichuan N28°07′28″ E101°11′09″ 3630
L􀆰 subspicata PG100927 Wachang Streetꎬ Muliꎬ Sichuan N28°03′13″ E100°46′08″ 3950
L􀆰 hookeri PG090918 Gezaxiangꎬ Shangri ̄Laꎬ Yunnan N28°07′59″ E99°53′18″ 4111
L􀆰 hookeri PG090980 Laojun Mountainꎬ Yulongꎬ Yunnan N26°38′22″ E99°43′48″ 3847
L􀆰 hookeri PG100960 Cangshanꎬ Daliꎬ Yunnan N25°40′48″ E100°05′41″ 3760
L􀆰 fischeri PG100810 Zhegushanꎬ Hongyuanꎬ Sichuan N31°48′25″ E102°41′25″ 3241
L􀆰 fischeri PG110802 Jiajinshanꎬ Baoxingꎬ Sichuan N30°51′30″ E102°43′13″ 2870
L􀆰 fischeri PG110805 Jiajinshanꎬ Baoxingꎬ Sichuan N30°49′48″ E102°42′36″ 3320
L􀆰 fischeri PG110811 Jiajinshanꎬ Xiaojin Countyꎬ Sichuan N30°51′25″ E102°41′23″ 3913
L􀆰 fischeri PG110815 Balangshanꎬ Xiaojin Countyꎬ Sichuan N30°58′06″ E102°52′19″ 3650
L􀆰 veitchiana PG090985 Laojun Mountainꎬ Yulongꎬ Yunnan N26°38′31″ E99°53′01″ 2378
L􀆰 veitchiana PG100856 Songfanꎬ Sichuan N32°53′04″ E103°29′03″ 3230
L􀆰 veitchiana PG100882 Jiuzhaigouꎬ Sichuan N32°54′32″ E104°14′42″ 2686
L􀆰 anoleuca PG090917 Gezaxiangꎬ Shangri ̄Laꎬ Yunnan N28°07′49″ E99°51′11″ 3870
L􀆰 anoleuca PG100706 Cangshanꎬ Daliꎬ Yunnan — — —
L􀆰 anoleuca PG100872 Wen Countyꎬ Gansu N33°03′20″ E104°41′57″ 2059
L􀆰 anoleuca PG100879 Tielouxiangꎬ Wen Countyꎬ Gansu N32°52′00″ E104°22′09″ 1871
L􀆰 latihastata PG090908 Haba Snow Mountainꎬ Yunnan N27°38′53″ E99°47′48″ 3717
L􀆰 latihastata PG100708 Sanbaxiangꎬ Shangri ̄Laꎬ Yunnan — — —
L􀆰 latihastata PG100953 Wenhaiꎬ Lijiangꎬ Yunnan N26°58′44″ E100°10′25″ 3125
L􀆰 caloxantha PG090979 Laojun Mountainꎬ Yulongꎬ Yunnan N26°39′41″ E99°46′48″ 3090
L􀆰 caloxantha PG100702 Tuguancunꎬ Diqingꎬ Yunnan N27°22′59″ E99°57′11″ 2990
L􀆰 villosa PG090903 Baishuitaiꎬ Shangri ̄Laꎬ Yunnan N27°30′26″ E100°02′22″ 2517
L􀆰 villosa PG100909 Yanchengꎬ Sichuan N27°41′14″ E101°13′24″ 3250
L􀆰 villosa PG100937 Muliꎬ Sichuan N27°38′34″ E100°40′56″ 3100
L􀆰 villosa PG100941 Lugu Lakeꎬ Ninglangꎬ Yunnan N27°35′58″ E100°48′54″ 2760
L􀆰 przewalskii PG100807 Zhegushanꎬ Li Countyꎬ Sichuan N31°43′46″ E102°44′31″ 2994
L􀆰 przewalskii PG100808 Yaxiucunꎬ Hongyuanꎬ Sichuan N31°56′46″ E102°38′04″ 3227
L􀆰 przewalskii PG100858 Chuanzhu Templeꎬ Songfanꎬ Sichuan N32°49′58″ E103°33′44″ 3086
L􀆰 przewalskii PG100863 Ruoergaiꎬ Sichuan N34°07′08″ E102°38′48″ 3580
L􀆰 przewalskii PG100867 Lintanꎬ Gansu N34°36′43″ E103°42′39″ 2875
L􀆰 przewalskii PG100881 Jiuzhaigouꎬ Sichuan N32°54′32″ E104°14′42″ 2686
L􀆰 przewalskii PG110801 Baoxingꎬ Sichuan N30°38′28″ E102°49′29″ 1800
L􀆰 przewalskii PG110816 Balangshanꎬ Xiaojinꎬ Sichuan N30°58′29″ E102°51′59″ 3620
L􀆰 lankongensis PG090923 Gezaxiangꎬ Shangri ̄Laꎬ Yunnan N28°07′34″ E99°45′17″ 3036
L􀆰 lankongensis PG090977 Nixixiangꎬ Shangri ̄Laꎬ Yunnan N28°03′13″ E99°30′15″ 3155
696                                  植 物 分 类 与 资 源 学 报                            第 37卷
Table 1 continued
Species name Sample ID Locality Latitude Longitude Atitude / m
L􀆰 lankongensis PG100931 Wachang Streetꎬ Muliꎬ Sichuan N28°02′19″ E100°45′58″ 3810
L􀆰 lankongensis PG100955 Wenhaiꎬ Lijiangꎬ Yunnan N26°57′01″ E100°10′51″ 3030
L􀆰 kanaitzensis var.
kanaitzensis PG100939 Lugu Lakeꎬ Ninglangꎬ Yunnan N27°41′37″ E100°45′08″ 2700
L􀆰 kanaitzensis var.
kanaitzensis PG100957 Heqingꎬ Yunnan N26°31′56″ E100°02′51″ 3080
L􀆰 kanaitzensis var.
kanaitzensis PG100964 Cangshanꎬ Daliꎬ Yunnan N25°42′11″ E100°07′28″ 2420
L􀆰 kanaitzensis var.
subnudicaulis PG090902 Shangri ̄Laꎬ Yunnan N27°40′32″ E100°01′32″ 3560
L􀆰 kanaitzensis var.
subnudicaulis PG090983 Laojun Mountainꎬ Yulongꎬ Yunnan N26°38′31″ E99°46′03″ 3487
L􀆰 kanaitzensis var.
subnudicaulis PG090986 Cangshanꎬ Daliꎬ Yunnan — — 2900
L􀆰 kanaitzensis var.
subnudicaulis PG100701 Lidipingꎬ Weixiꎬ Yunnan N27°09′38″ E99°25′02″ 3207
L􀆰 kanaitzensis var.
subnudicaulis PG100952 Xuesongcunꎬ Lijiangꎬ Yunnan — — —
L􀆰 kanaitzensis var.
subnudicaulis PG110818 Danba Countyꎬ Sichuan N30°35′31″ E101°39′37″ 3100
L􀆰 tsangchanensis PG090907 Haba Snow Mountainꎬ Yunnan N27°38′53″ E99°47′53″ 3717
L􀆰 tsangchanensis PG100938 Maoniushanꎬ Ninglangꎬ Yunnan N27°40′01″ E100°36′40″ 3963
L􀆰 tsangchanensis PG110871 Tianchiꎬ Shangri ̄Laꎬ Yunnan — — 3890
L􀆰 botryodes PG100814 Zhegushanꎬ Hongyuanꎬ Sichuan N31°52′40″ E102°40′14″ 3984
L􀆰 botryodes PG110836 Ganzi Countyꎬ Sichuan N31°02′40″ E99°17′12″ 3500
L􀆰 sagitta PG090948 Litangꎬ Sichuan N29°47′51″ E100°21′02″ 3815
L􀆰 sagitta PG100826 Qiongxi Townꎬ Hongyuanꎬ Sichuan N32°49′37″ E102°30′33″ 3691
L􀆰 sagitta PG100834 Gemoxiangꎬ Abaꎬ Sichuan N33°03′20″ E101°32′11″ 3460
L􀆰 sagitta PG100844 Tangkexiangꎬ Ruoergaiꎬ Sichuan N33°24′42″ E102°32′45″ 3556
L􀆰 sagitta PG100849 Ruoergaiꎬ Sichuan N33°04′35″ E103°21′23″ 3752
L􀆰 sagitta PG100864 Luqu Countyꎬ Gansu N34°31′33″ E102°23′23″ 3363
L􀆰 sagitta PG100866 Lintanꎬ Gansu N34°45′04″ E103°15′09″ 3130
L􀆰 melanocephala PG090916 Zagexiangꎬ Shangri ̄Laꎬ Yunnan N28°07′49″ E99°50′37″ 3796
L􀆰 melanocephala PG100925 Wachang Streetꎬ Muliꎬ Sichuan N28°03′12″ E100°46′08″ 3950
L􀆰 dictyoneura PG090922 Pachahaiꎬ Shangri ̄Laꎬ Yunnan N27°58′03″ E99°43′15″ 3164
L􀆰 dictyoneura PG090947 Chituxiangꎬ Daochengꎬ Sichuan N28°38′34″ E100°14′55″ 3398
L􀆰 dictyoneura PG090968 Xiangchengꎬ Sichuan N29°00′33″ E99°43′34″ 3920
L􀆰 dictyoneura PG100709 Sanbaxiangꎬ Shangri ̄Laꎬ Yunnan — — —
L􀆰 dictyoneura PG100905 Gesalaxiangꎬ Yanbianꎬ Sichuan N27°08′01″ E101°17′28″ 2580
L􀆰 dictyoneura PG100921 Keerxiangꎬ Muliꎬ Sichuan N28°07′00″ E101°05′58″ 2800
L􀆰 dictyoneura PG100954 Wenhaiꎬ Lijiangꎬ Yunnan N26°58′10″ E100°10′53″ 3120
L􀆰 brassicoides PG090953 Litangꎬ Sichuan N29°50′30″ E100°20′58″ 4020
L􀆰 brassicoides PG100811 Zhegushanꎬ Hongyuanꎬ Sichuan N31°53′13″ E102°40′07″ 3900
L􀆰 brassicoides PG100836 Abaꎬ Sichuan N33°10′47″ E101°27′53″ 3644
L􀆰 brassicoides PG100853 Songfanꎬ Sichuan N32°55′34″ E103°20′59″ 3672
L􀆰 brassicoides PG110813 Balangshanꎬ Wenchuanꎬ Sichuan N30°55′33″ E102°53′26″ 4280
L􀆰 brassicoides PG110826 Ganziꎬ Sichuan N31°36′56″ E100°12′48″ 3930
L􀆰 lingiana PG110821 Gedaliangziꎬ Daofuꎬ Sichuan N30°32′13″ E101°35′17″ 3820
L􀆰 lingiana PG110848 Xinlong Countyꎬ Sichuan N30°14′50″ E100°15′31″ 4060
L􀆰 pleurocaulis PG090940 Wumingshanꎬ Xiangchengꎬ Sichuan N29°07′14″ E100°01′23″ 4201
L􀆰 pleurocaulis PG090958 Haizishanꎬ Daochengꎬ Sichuan N29°21′16″ E100°07′12″ 4400
L􀆰 pleurocaulis PG100818 Hongyuanꎬ Sichuan N31°52′27″ E102°43′58″ 3756
L􀆰 pleurocaulis PG110804 Jiajinshanꎬ Baoxingꎬ Sichuan N30°49′35″ E102°42′43″ 3300
L􀆰 virgaurea PG090939 Wumingshanꎬ Xiangchengꎬ Sichuan N29°07′14″ E100°01′23″ 4201
L􀆰 virgaurea PG090954 Litangꎬ Sichuan N29°50′30″ E100°20′58″ 4020
L􀆰 virgaurea PG090960 Wumingshanꎬ Daochengꎬ Sichuan N29°20′46″ E100°06′01″ 4352
L􀆰 virgaurea PG090966 Xiangchengꎬ Sichuan N29°00′08″ E99°44′26″ 4026
L􀆰 virgaurea PG100819 Hongyuanꎬ Sichuan N32°17′12″ E102°29′27″ 3609
L􀆰 virgaurea PG100837 Jiuzhiꎬ Qinghai N33°24′25″ E101°25′39″ 3708
L􀆰 virgaurea PG100840 Abaꎬ Sichuan N33°05′16″ E102°02′44″ 3554
L􀆰 virgaurea PG100845 Tangkexiangꎬ Ruoergaiꎬ Sichuan N33°24′42″ E102°32′45″ 3556
L􀆰 virgaurea PG100865 Luqu Countyꎬ Gansu N34°31′33″ E102°23′23″ 3363
7966期              HE and PAN: Study on the DNA Barcoding of Genus Ligularia Cass. (Asteraceae)              
Table 2  The primer informations used in this study
DNA region Primer pairs Primer sequence (5′-3′) Source
ITS ITS4ITS5
TCC TCC GCT TAT TGA TAT GC
GGA AGT AAA AGT CGT AAC AAG G White et al.ꎬ 1990
matK 1F ̄KIM1R ̄KIM
AAT ATC CAA ATA CCA AAT CC
ACC CAG TCC ATC TGG AAA TCT TGG TTC Kim (unpublished)
psbA ̄trnH psbAFtrnH2
GTT ATG CAT GAA CGT AAT GCT C
CGC GCA TGG TGG ATT CAC AAT CC Sang at al.ꎬ 1997ꎻ Tate and Simpsonꎬ 2003
rbcL 1F724R
ATG TCA CCA CAA ACA GAA AC
TCG CAT GTA CCT GCA GTA GC Fay et al.ꎬ 1997
1􀆰 3  Data analysis
The raw DNA sequences were assembled and
edited with SeqMan (DNA Star packageꎻ DNA Star
Inc.ꎬ Madisonꎬ WIꎬ USA)ꎬ and then were aligned
with BioEdit V􀆰 7 (Hallꎬ 1999) and adjusted manu ̄
ally. MEGA 5􀆰 0 (Tamura et al.ꎬ 2007) was used to
search the variable sites and calculate the intra ̄ and
inter ̄specific genetic distance. The neighbour ̄joining
(NJ) tree was constructed under the Kimura ̄2 ̄pa ̄
rameter (K2P) distance model recommended for spe ̄
cies ̄level barcoding analysis (Hebert et al.ꎬ 2003)ꎬ
and bootstrap values were calculated with 1000 repli ̄
cations in MEGA 5􀆰 0. It is generally believed that
when all the individuals of a species get together into
a monophyletic clade with support rate ≥50%ꎬ this
species is identified successfully (Tripathi et al.ꎬ 2013).
2  Results
Using selected primer pair listed in Table 2ꎬ the
four loci used in this study were all successfully am ̄
plified and sequenced in 144 samplesꎬ which showed
high universality. The sequence length / variable sites
(bp) of ITSꎬ matKꎬ psbA ̄trnH and rbcL were 689 /
191ꎬ 938 / 23ꎬ 586 / 42 and 633 / 5ꎬ respectively. The
distributions of pair ̄wise K2P genetic distances were
shown in Figure 1ꎬ indicating that a weaker barcod ̄
ing gap existed in ITSꎬ while the three chloroplast
segments lacked this kind of barcoding gap.
Fig􀆰 1  Comparisons of frequency distribution of intra ̄ and inter ̄specific pairwise distances among four core
barcoding segments (x ̄axis: occurrenceꎻ y ̄axis: K2P distance)
896                                  植 物 分 类 与 资 源 学 报                            第 37卷
  The NJ trees ( not shown) indicated that the
three chloroplast sequences had extremely low spe ̄
cies identification abilityꎬ of which psbA ̄trnH could
identify one species (L􀆰 lankongensis) and the other
two loci failed to identify any species. The forth lociꎬ
ITSꎬ had the highest species discriminatory power
for Ligularia. Of the 35 species analyzedꎬ 21 were
successfully identified using ITS with species identi ̄
fication rate reached 60% (Fig􀆰 2). In additionꎬ ITS
sequence data alone or combined with psbA ̄trnH
could separate Section Corymbosae from other Sec ̄
tions (Fig􀆰 2ꎬ 3).
The analysis of any combination of the four re ̄
gions showed that ITS + rbcL possessed the highest
species discriminatory power with 21 species (60%)
could be identifiedꎬ which was the same as the resol ̄
ving ability of single ITS region. Although the base
mutation rates of psbA ̄trnH region was highest among
the three cpDNA sequences (42 / 586)ꎬ the combina ̄
tion of psbA ̄trnH+ITS could only discriminated 20
species (Fig􀆰 3). The combination of all four regions
also failed to improve the ability of species identifi ̄
cationꎬ and just 19 species were discriminated.
3  Discussion
An ideal barcode should possess sufficient vari ̄
ations among sequences of different species so as to
discriminate species and should be sufficiently con ̄
served in the sequences of the same species so that
there is less variability intraspecific than interspecific
(Kress et al.ꎬ 2005ꎻ Lahaye et al.ꎬ 2008ꎻ CBOL
Plant Working Groupꎬ 2009). PCR and sequencing
success rates are important criteria for DNA barcod ̄
ing as well ( Chase et al.ꎬ 2007ꎻ Kress and Erick ̄
sonꎬ 2007ꎻ Hollingsworth et al.ꎬ 2009). In the pres ̄
ent researchꎬ four regions tested here showed a PCR
and sequencing success rate of 100% in 144 individu ̄
als belonging to 35 species of Ligularia. which mean ̄
ing that they had highly universal primer pairꎬ and
could generate high ̄quality bidirectional sequences.
Howeverꎬ of the four core barcodesꎬ only ITS gener ̄
ated a weak DNA barcoding gap and provided rela ̄
tively the highest species resolutionꎬ and the three
chloroplast regions did not exist any barcoding gap
and had nearly no species discrimination power. This
conclusion is consistent with that revealed by Gao et
al. (2010) in the Asteraceae family.
rbcL variation mainly exists above the species
level and the interspecific variation is usually lowꎬ
while the evolution rates of matK and psbA ̄trnH per ̄
form relatively fast in the chloroplast genome (Chase
et al.ꎬ 1993ꎻ Shaw et al.ꎬ 2005). Previous studies
on numerous land plants showed that single or com ̄
bination of these three regions had high rate of spe ̄
cies identification (Kress et al.ꎬ 2005ꎬ 2009ꎻ Kress
and Ericksonꎬ 2007ꎻ Fazekas et al.ꎬ 2008ꎻ Lahaye
et al.ꎬ 2008ꎻ Newmaster et al.ꎬ 2006ꎬ 2008ꎻ Holl ̄
ingsworth et al.ꎬ 2009ꎻ Jiao and Shuiꎬ 2013ꎻ Liu et
al.ꎬ 2013ꎻ Enan and Ahmedꎬ 2014). Howeverꎬ the
three chloroplast regions had lower nucleotide substi ̄
tution rates than ITS and did not performed well in i ̄
dentifying Ligularia. For exampleꎬ psbA ̄trnH could
identify only one speciesꎬ even if it was one of the
chloroplast markers with fastest evolving rate and
had high level of species discrimination in many
plant groups. Furthermoreꎬ when ITS was combined
with psbA ̄trnHꎬ the species discriminatory power
failed to improve. Congruence between the datasets
of nuclear DNA marker (ITS) and chloroplast DNA
markers (matKꎬ rbcL and psbA ̄trnH) were evalua ̄
ted by the incongruence ̄length ̄difference ( ILD )
test showing that there was gene conflict between
them. This kind of gene conflict probably is the
cause for the decrease in species identification power
of ITS when combined with psbA ̄trnH. Genus Ligu ̄
laria was proposed to originated as a consequence of
an explosive radiation within the last 20 million years
(Liu et al.ꎬ 2006) and probably existed incomplete
lineage sorting. Furtherꎬ multiple hybridization and
gene introgression occurred frequently among the
congeneric species ( Pan et al.ꎬ 2008ꎻ Yu et al.ꎬ
2011ꎬ 2014aꎬ b). These phenomena could be the
major causes of low species identification rate of
DNA sequence. Anywayꎬ we can’t rely on a single
9966期              HE and PAN: Study on the DNA Barcoding of Genus Ligularia Cass. (Asteraceae)              
Fig􀆰 2  The NJ tree inferring from the ITS sequence. Bootstrap values (>50%) are shown above the relevant branches. The blod black
font shows species successfully identified. A: a clade with palmate veinsꎻ B: a clade with pinnate veins
007                                  植 物 分 类 与 资 源 学 报                            第 37卷
Fig. 3  The NJ tree inferring from the ITS+psbA ̄trnH sequence. Bootstrap values (>50%) are shown above the relevant branches.
The blod black font shows species successfully identified. A: a clade with palmate veinsꎻ B: a clade with pinnate veins
1076期              HE and PAN: Study on the DNA Barcoding of Genus Ligularia Cass. (Asteraceae)              
nucleotide fragment ( especially the uniparental in ̄
herited plastid markers) to provide reliable identifi ̄
cation of hybrids from parental species (Newmaster
et al.ꎬ 2006).
In Ligulariaꎬ section Corymbosae was consid ̄
ered as the most primitive group with the palmate or
pinnate veins ( Liu et al.ꎬ 1994). In the present
studyꎬ NJ trees conduced from single ITS and com ̄
bined ITS + psbA ̄trnH data showed that section
Corymbosae was separated from the other sections of
Ligulariaꎬ and the taxa with palmate veins ( except
L􀆰 stenoglossa) and ones with pinnate veins formed a
cladeꎬ respectively. Howeverꎬ the DNA barcodes
used in the present study could not identify other
sections or series. Thereforeꎬ we need to search new
chloroplast loci with faster evolution rate and higher
interspecific variationꎬ so as to be combined with ITS
and serve as the “super ̄barcode” (Li et al.ꎬ 2015)
for identifying Ligularia species.
Acknowledgements: We thank ZHAN Qing ̄qingꎬ JIA Jingꎬ
ZHAO Yu ̄juanꎬ YANG Zhi ̄yunꎬ YU Jiao ̄junꎬ ZHOU Jingꎬ
WANG Jin ̄fengꎬ ZENG Liang ̄qingꎬ WU Haoꎬ WANG Wen ̄
caiꎬ WANG Chao ̄boꎬ YIN Gen ̄shenꎬ FENG Xiu ̄yanꎬ
GUAN Meng ̄mengꎬ and ZHOU Wei for their contributions in
the experiments.
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