Characterization and Application of EST-SSR Markers Developed From the Transcriptome of Amentotaxus argotaenia (Taxaceae), a Relict Vulnerable Conifer

Abstract

Amentotaxus argotaenia (Taxaceae) is a vulnerable coniferous species with preference for shade and moist environment. Accurate estimation of genetic variation is crucial for its conservation, especially in the context of global warming. In this study, we acquired a transcriptome from A. argotaenia leaves using Illumina sequencing and de novo assembled 62,896 unigenes, of which 5510 EST-SSRs were detected. Twenty-two polymorphic EST-SSRs were successfully developed and further used to investigate genetic variation, linkage disequilibrium, and bottleneck signatures of A. argotaenia. The results showed that A. argotaenia had moderate genetic variation and high genetic differentiation, which may provide raw material to protect against climatic changes and accelerate local adaptation, respectively. No bottlenecks were found to occur in A. argotaenia. Our study not only showed that these EST markers are very effective in population genetic analysis but also lay a solid foundation for further investigating adaptive evolution and conservation strategies of A. argotaenia.

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Edited by:
Jacob A. Tennessen,
Harvard University,
United States
Reviewed by:
Jian-Feng Mao,
Beijing Forestry University,
China
Linkai Huang,
Sichuan Agricultural University,
China
*Correspondence:
Ting Wang
tingwang@scau.edu.cn
Yingjuan Su
suyj@mail.sysu.edu.cn
†These authors have contributed
equally to this work
Specialty section:
This article was submitted to
Evolutionary and
PopulationGenetics,
a section of the journal
Frontiers in Genetics
Received: 31 March 2019
Accepted: 24 September 2019
Published: 18 October 2019
Citation:
RuanX, WangZ, WangT and
SuY (2019) Characterization and
Application of EST-SSR Markers
Developed From the Transcriptome of
Amentotaxus argotaenia (Taxaceae),
a Relict VulnerableConifer.
Front. Genet. 10:1014.
doi: 10.3389/fgene.2019.01014
Characterization and Application of
EST-SSR Markers Developed From
the Transcriptome of Amentotaxus
argotaenia (Taxaceae), a Relict
Vulnerable Conifer
Xiaoxian Ruan 1†, Zhen Wang 1†, Ting Wang 2* and Yingjuan Su 1,3*
1 School of Life Sciences, Sun Yat-sen University, Guangzhou, China, 2 College of Life Sciences, South China Agricultural
University, Guangzhou, China, 3 Research Institute of Sun Yat-sen University, Shenzhen, China
Amentotaxus argotaenia (Taxaceae) is a vulnerable coniferous species with preference
for shade and moist environment. Accurate estimation of genetic variation is crucial for
its conservation, especially in the context of global warming. In this study, we acquired a
transcriptome from A. argotaenia leaves using Illumina sequencing and de novo assembled
62,896 unigenes, of which 5510 EST-SSRs were detected. Twenty-two polymorphic
EST-SSRs were successfully developed and further used to investigate genetic variation,
linkage disequilibrium, and bottleneck signatures of A. argotaenia. The results showed
that A. argotaenia had moderate genetic variation and high genetic differentiation, which
may provide raw material to protect against climatic changes and accelerate local
adaptation, respectively. No bottlenecks were found to occur in A. argotaenia. Our study
not only showed that these EST markers are very effective in population genetic analysis
but also lay a solid foundation for further investigating adaptive evolution and conservation
strategies of A. argotaenia.
Keywords: Amentotaxus argotaenia, transcriptome, EST-SSR, genetic variation, population structure
INTRODUCTION
e genus Amentotaxus Pilger (Taxaceae) has six species, and ve of them have been listed as
endangered, vulnerable, or near threatened (Fu et al., 1999a; Farjon and Filer, 2013; Hilton-Taylor
et al., 2013). Among all Amentotaxus species, Amentotaxus argotaenia (Hance) Pilger has the widest
distribution but with small isolated populations occurring in southern and central China, northern
Vietnam, and Laos (Farjon and Filer, 2013). Its preferred environments are limestone mountains,
forests, ravines, and shady and damp stream banks, at altitudes of 300–1100 m (Fu et al., 1999a;
Lin et al., 2007). e natural regeneration of the plant is infrequent due to slow growth rate and
poorly dispersed seeds. Moreover, forest clearing and habitat loss have also been severely reducing
its population size. A. argotaenia is listed as vulnerable in China and as near threatened in the
International Union for Conservation of Nature Red List of reatened Species (Hilton-Taylor et al.,
2013). Since knowledge of population genetics is essential for the conservation and sustainable use
of wild resources (Wayne and Morin, 2004; Hoban et al., 2013), we aim to examine the population
genetic variation of A. argotaenia using novel molecular markers.
Frontiers in Genetics | www.frontiersin.org October 2019 | Volume 10 | Article 1014
ORIGINAL RESEARCH
doi: 10.3389/fgene.2019.01014
published: 18 October 2019

Transcriptome of Amentotaxus argotaeniaRuan et al.
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In comparison to genomic SSRs, expressed sequence tag
(EST)-SSRs represent functional markers that may linked with
functional genes inducing phenotypic eects (Ranade et al.,
2014; Zhou et al., 2018a). ey hence provide opportunities to
examine functional diversity in relation to adaptive variation.
Moreover, EST-SSRs are reported to be more reliable because
they present lower frequencies of null alleles than do genomic
SSRs (Yu and Li, 2008). With the advances in next-generation
sequencing technology, EST-SSRs are becoming amenable to be
identied by sequencing the transcriptomes (Zhou et al., 2018b).
Next-generation sequencing is faster and more cost-eective than
traditional approach, e.g., cDNA library construction method
(Huang et al., 2015). However, currently, there is a shortage of
EST-SSRs developed from A. argotaenia, although EST-SSRs
have been identied for its congeneric species, Amentotaxus
formosana (Li et al., 2016). Excavation and characterization
of EST-SSRs for A. argotaenia may contribute to enhance our
understanding of its population genetic diversity, structure, and
the genetic basis of adaptive divergence. In addition, it will also
provide resources to assess the association between transposable
elements and SSR distribution as well as their roles in genome
organization (La Rota et al., 2005; Wang et al., 2018a).
In this study, we constructed a leaf transcriptome of A.
argotaenia using the Illumina sequencing platform. Based
on the transcriptome sequencing data, we developed a set of
EST-SSR markers and examined their polymorphisms. We
then assessed the genetic variation of four populations of A.
argotaenia using the novel EST-SSR markers. is work provides
essential information for the conservation and management of A.
argotaenia in the future.
MATERIALS AND METHODS
Plant Materials and DNA Extraction
A total of 56 A. argotaenia individuals were sampled from four
of its natural populations Jiuqushui (JQS; n = 15), Chuanping
(CP; n = 13), Qiniangshan (QNS; n = 12), and Wugongshan
(WGS; n = 16) located in China (Supplementary Table 1).
Fresh leaves were collected and desiccated in sealed plastic bags
with silica gel. Genomic DNA was isolated using the modied
cetyltrimethylammonium bromide method (Su et al., 2005). DNA
quality was evaluated using gel electrophoresis on 0.8% agarose gel.
RNA Extraction, cDNA Library
Construction, and Transcriptome
Sequencing
Fresh young leaves of one A. argotaenia individual from
population CP, which is planted in a greenhouse at Sun Yat-sen
University, were used to extract total RNAs using the method
described by Fu et al. (2004). RNA integrity was evaluated on
agarose gels followed by quantication on an Agilent 2100
Bioanalyzer (Agilent Technologies, Santa Clara, California,
USA). e mRNAs were isolated from the total RNAs by using
a Dynabeads mRNA DIRECT Kit (Invitrogen Life Technologies,
Carlsbad, California, USA) and randomly fragmented. e
fragmented mRNAs were converted into double-stranded cDNA
by using random primers and reverse transcriptase. Aer end-
repairing and tailing A, the cDNA fragments were ligated to
Illumina paired-end adapters. e cDNA library was sequenced
on an Illumina Hiseq2500 platform (Illumina, San Diego,
California, USA) with insertion size of 400–500 bp.
Transcriptome Assembly, Functional
Annotation, and Classification
We obtained a total of 25,257,542 paired-end reads from A.
argotaenia. e reads were ltered by removing primer or adaptor
sequences, and reads that contain unknown (“N”) or poor-
quality bases (the mean quality per base < 15 with a 4-base wide
sliding window) using the Trimmomatic soware version 0.32
(Bolger et al., 2014). e resulting clean data were deposited in
Sequence Read Archive of the National Center for Biotechnology
Information (NCBI) (Bioproject no. PRJNA413732; Biosample
no. SAMN07764634; https://www.ncbi.nlm.nih.gov/bioproject/
PRJNA413732). e clean reads longer than 90 nt were de novo
assembled into contigs and transcripts using the TRINITY
soware (https://github.com/trinityrnaseq/trinityrnaseq/releases)
with default settings. e transcripts that cannot be prolonged at
either end were dened as unigenes.
All unigenes were searched against Nt (NCBI nucleotide
sequences), Nr (NCBI non-redundant database), and Swiss-
Prot (a manually annotated and reviewed protein sequence
database) through blast 2.2.30+ (p://p.ncbi.nlm.nih.gov/blast/
executables/blast+/2.2.30/) with a cut-o E-value of 10−5. Protein
domains of open reading frame within unigenes was identied
by using HMMER hmmscan (hmmer-3.1b2-linux-intel-x86_64)
and Pfam (the protein families database). Blast2GO version 3.0
was used to perform Gene Ontology (GO) annotations dened by
molecular function, cellular component, and biological process
ontologies (http://www.blast2go.com/b2ghome). We further used
the Kyoto Encyclopedia of Genes and Genomes (KEGG) database
to performed pathways annotation and euKaryotic Ortholog
Groups (KOG) database to predict possible functions.
Development of EST-SSRs
EST-SSRs were searched in the assembled unigenes using
MIcroSAtellite (http://pgrc.ipk-gatersleben.de/misa/misa.html).
e SSRs were assumed to contain mono-, di-, tri-, tetra-, penta-,
and hexa-nucleotides with minimum repeat numbers of 10, 6, 5, 5,
5, and 5, respectively. Primer premier 5.0 (Clarke and Gorley, 2001)
was used to design primers. Only those SSRs containing two to six
repeat motifs were considered. Major parameters for primer design
included the following: (1) primer length ranging from 16 to 27
bp, (2) GC content of 30%–70%, (3) melting temperature between
50 and 63°C, and (4) PCR product size ranging from 100 to 400
bp. PCR reactions were performed in 20 μl mixture containing 2
μl 10 × PCR buer (Mg2+), 0.4 μl 10 mM dNTPs, 0.5 μl 10 mM
each of primers, 1.25 U Taq polymerase, and 20 ng DNA template.
e PCR protocol was as follows: 94°C for 5 min, followed by 30
cycles of 40 s at 94°C, 40 s at optimal annealing temperature and
30 s at 72°C, and a nal elongation at 72°C for 10 min. Amplified
products were screened on a 6.0% denaturing polyacrylamide gel,
and fragment size was determined with 50-bp marker.
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Transcriptome of Amentotaxus argotaeniaRuan et al.
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Evaluation of Polymorphic EST-SSRs and
Population Genetic Analysis
GenAlex software (Peakall and Smouse, 2006) was used
to calculate the EST-SSR genetic parameters, including
the number of observed alleles (Na), the effective number
of alleles (Ne), observed heterozygosities (Ho), expected
heterozygosities (He), and probability of the deviation from
the Hardy–Weinberg equilibrium. The polymorphism
information content (PIC) value and null alleles were
evaluated using CERVUS 3.0 (Kalinowski et al., 2007) and
Micro-Checker (Van Oosterhout et al., 2004), respectively.
Linkage disequilibrium across loci was determined using
TASSEL version 3.0 (Bradbury et al., 2007) with squared
correlation coefficient (r2 > 0.3) and the threshold of p values
(< 0.001) based on Fisher’s exact test.
Arlequin version 3.5 (Excoer and Lischer, 2010) was used to
perform a Mantel test with 10,000 permutations to examine the
pattern of isolation by distance. Using the same soware, analysis
of molecular variance was conducted to determine the amount of
genetic variation at dierent levels.
Using EST-SSR data, we applied a Bayesian model-based
clustering algorithm implemented in STRUCTURE 2.2 to infer
population structure. We used the admixture model, setting
the parameters as follows: burn-in periods = 10,000, MCMC
replicates = 10,000, K = 1 to 8, and iterations = 10. e optimum
number of clusters (K) was determined by calculating ΔK
(Evanno et al., 2005).
We conducted the Wilcoxon’s sign-rank test and the mode-
shi test to detect signatures of genetic bottleneck by running
BOTTLENECK version 1.2.02 (Piry et al., 1999). e two-phase
mutation model was selected because it is more suitable for
microsatellite data than the other two models (Piry et al., 1999;
Zhang and Zhou, 2013). We performed 1000 simulations under
the two-phase mutation model with 70% single-step mutations
and 30% multi-step mutations.
RESULTS
Transcriptome Sequencing and
DeNovoAssembly
Approximately 23.5 million clean reads were obtained
from the transcriptome of A. argotaenia with the length of
90–125 bp and GC content of 47%. The percentages of Q20
(base sequencing error probability < 1%) and Q30 (base
sequencing error probability < 0.1%) bases were 100% and
97%, respectively. These clean reads were assembled into
80674 transcripts by using Trinity with an average length of
756 bp and an N50 of 1018 bp. The total length of transcripts
reached 60,999,479 bp. After further assembly, a total of
62,896 unigenes were identified with an average length of
721 bp, a minimal length of 301 bp, and an N50 value of 947
bp. The sum of the length of the unigenes was 45,357,136 bp
(Table 1). The length of 37.473% (23569) of the unigenes
ranged from 301 to 400 bp, 61.956% (38,968) varied from
401 to 3000 bp, while 0.571% (359) was longer than 3000 bp
(SupplementaryFigure 1).
Functional Annotation and Categorization
We conducted the annotation of 62,896 unigenes in the seven
public databases (Nr, Nt, KOG, Swiss-Prot, Pfam, KEGG, and
GO), of which 36,671 were successfully annotated (Table 1). Of
them, 13,140 (20.89%) were annotated in Nt, 32,183 (51.17%)
in Nr, 26,309 (41.83%) in Swiss-Prot, 21,595 (34.33%) in Pfam,
31,283 (49.74%) in GO, 32,953 (52.39%) in KOG, and 15,072
(23.96%) in KEGG. A total of 490 unigene were identied in all
seven databases (Tabl e 1).
First, 31,283 unigenes were classied into three main GO
categories: biological process, cellular component, and molecular
function, including 44 functional groups. In the biological process
category, there were 7313 unigenes assigned to “cellular process,”
5973 to “single-organism process,” 5808 to “metabolic process,”
and 1 to “biological regulation.” In the cellular component
category, “cell part” and “organelle” component-related functions
were predominant, with 4835 unigenes assigned to the former and
2060 to the latter. In the molecular function category, “binding”
and “catalytic activity” were the most enriched, comprising 2520
and 2358 unigenes, respectively (Figure 1).
Second, 32,953 unigenes were assigned to 25 KOG classications.
Among them, the largest group was “general function prediction only”
(4286), followed by “function unknown” (3218), “signal transduction
mechanisms” (2521), and “posttranslational modication, protein
turnover, chaperones” (2442) (Supplementary Figure 2).
ird, a total of 15,072 unigenes were mapped to 38 KEGG
pathways corresponding to six categories (Supplementary Figure
3). Most of them involved in “translation” (3007 unigenes; 19.95%),
“carbohydrate metabolism” (2815; 18.68%), and “folding” (2425;
16.09%) pathways. e 38 KEGG pathways were related to such
categories as metabolism, cellular processes, genetic information
processing, environmental information processing, and others.
TABLE 1 | Sequencing, assembly, and annotation results of Amentotaxus
argotaenia transcriptome.
Total raw reads 25,257,542
Total clean reads 23,553,846
% Q20 100
% Q30 97
% GC 47
Number of transcripts 80,674
Average length of transcripts (bp) 756
N50 of transcripts (bp) 1018
Number of unigenes 62,896
Minimum length of unigenes (bp) 301
Average length of unigenes (bp) 721
N50 of unigenes (bp) 947
Number of unigenes annotated at least one databases 36,671
Number of unigenes with Nt annotations 13,140
Number of unigenes with Nr annotations 32,183
Number of unigenes with KOG annotations 32,953
Number of unigenes assigned to GO terms 31,283
Number of unigenes with Swiss-Prot annotations 26,309
Number of unigenes with Pfam annotations 21,595
Number of unigenes with KEGG pathways 15,072
Number of unigenes annotated to seven public databases 490
Nt, NCBI nucleotide sequences; Nr, NCBI non-redundant database; KOG,
euKaryotic Ortholog Groups; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of
Genes and Genomes.
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Transcriptome of Amentotaxus argotaeniaRuan et al.
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Characterization of EST-SSRs
We identied 5510 EST-SSRs from 4830 SSR-containing unigene
sequences, of which 362 were compound SSRs. With the
exception of mononucleotide repeats (64.50%), trinucleotide
repeats were the most common type with a frequency of 22.25%,
followed by di- (9.18%), tetra- (1.82%), penta- (1.00%), and
hexanucleotide (1.25%) repeats (Table 2). EST-SSRs with 10
tandem repeats (1719, 31.19%) were the most common, followed
by >11 tandem repeats (1134; 20.58%) and 9 tandem repeats
(42; 0.76%) (Table 2). Motif A/T (98.11%) was dominant in
TABLE 2 | The distribution of repeat unit number and motif length of EST-SSRs.
SSR motif length Repeat unit number
5 6 7 8 9 10 11 > 11 Total Percentage (%)
Mono 1682 787 1085 3554 64.50
Di 255 89 60 32 20 16 34 506 9.18
Tri 747 266 112 61 8 15 5 12 1226 22.25
Tetra 65 27 1 4 1 2 100 1.82
Penta 42 3 3 3 2 2 55 1.00
Hexa 34 18 5 8 1 2 1 69 1.25
Total 888 569 210 136 42 1719 812 1134 5510
Percentage (%) 16.12 10.33 3.81 2.47 0.76 31.19 14.74 20.58
Mono, mono-nucleotide; Di, di-nucleotide; Tri, tri-nucleotide; Tetra, tetra-nucleotide; Penta, penta-nucleotide; Hexa, hexa-nucleotide.
FIGURE 1 | Functional classification of Gene Ontology for Amentotaxus argotaenia unigenes.
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Transcriptome of Amentotaxus argotaeniaRuan et al.
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mononucleotide repeats, whereas AT/TA (50.79%) was the most
abundant in dinucleotide repeats, followed by AG/CT (35.18%)
and AC/GT (14.03%). Trinucleotide motifs AAG/CTT, AGG/
CCT, AGC/CTG, AAT/ATT, and ACT/AGT had frequencies of
21.21%, 17.94%, 15.42%, 14.68%, and 0.33%, respectively.
We also examined the linkage of the 22 EST-SSR loci. Of 231
combinations, four pairs of loci (SHS-1306 vs SHS-26840, SHS-
1306 vs SHS-38297, SHS-28717 vs SHS-32587, and SHS-34629 vs
SHS-38297) were found to be linked with r2 > 0.3 and p < 0.001.
Polymorphic EST-SSRs Identification and
Estimation of Genetic Diversity
We randomly selected 60 EST-SSR primers to evaluate their
application and the polymorphism across 12 A. argotaenia
individuals from four populations. Twenty-two of the
microsatellite loci exhibited allelic polymorphism, whereas 16
were identied as monomorphic (Tabl e 3). We then used the 22
polymorphic EST-SSR markers to perform population genetic
analysis (Supplementary Figure 5).
e number of observed alleles and the eective number of
alleles varied from 1 to 7 and from 1 to 4.694 per locus, respectively.
e observed heterozygosity ranged from 0 to 1.000 (average =
0.250), while the expected heterozygosity ranged from 0.000 to
0.787 (average = 0.390). e mean value of PIC was 0.455, with
the minimum of 0.084 and the maximum of 0.707. Fourteen loci
were identied as null allele. Six, 9, 14, and 16 EST-SSRs showed
signicant deviations from the Hardy–Weinberg equilibrium in
populations JQS, CP, QNS, and WGS, respectively (Table 4).
Population Genetic Structure
andDifferentiation
Genetic dierentiation (Fst) based on EST-SSRs was 0.28198.
Analysis of molecular variance revealed that 71.80% of the genetic
variation occurred within populations, while 10.37% and 17.83%
were attributed to among populations within groups and among
groups, respectively (Supplementary Table 2). In addition, the
result of Mantel test showed that there was no signicant correlation
between genetic and geographical distances (p = 0.3306).
ΔK demonstrated that the uppermost K equaled 3
(Supplementary Figure 4). Amentataxus argotaenia populations
were assigned to three groups. Group I contained populations
JQS and CP, group II contained population WGS, and group III
contained population QNS (Figure 2).
Bottleneck Signature
At species level, both Wilcoxon’s sign-rank test and mode-shi
analysis indicated that A. argotaenia had not experienced a
recent bottleneck (Supplementary Table 3).
DISCUSSION
Characterization of Transcriptome
In this study, we sequenced, assembled, and annotated the
transcriptome of A. argotaenia using the next-generation
sequencing approach. A total of 62,896 unigenes were de novo
assembled with the unigene mean and N50 length of 721 and 947
bp, respectively (Table 1). More than half of the unigenes can be
successfully annotated through seven databases (Nr, Nt, KOG,
Swiss-Prot, Pfam, KO, and GO), of which 490 were simultaneously
identied (Tab le 1 ). Most of the annotated unigenes were unique in
A. argotaenia compared to its closely related conifer Torreya grandis
(Zeng et al., 2018). Moreover, the annotated results of NR database
indicated that A. argotaenia exhibited only 27.5% unigene identity
to another conifer Picea sitchensis. ese unique unigenes may
represent the species-specic genetic signature of A. argotaenia
potentially underlying its speciation process or evolution (Frech
and Chen, 2011). Similar results have been found in the case of
Picea abies (Nystedt et al., 2013). In addition, 31,283, 32,953, and
15,072 unigenes of A. argotaenia were assigned into 44 functional
groups in GO, 25 classications in KOG, and 38 pathways in KEGG,
respectively. ese results indicate that the identied A. argotaenia
unigenes have wide-ranging functions and will be valuable for
analyzing the functional diversity of A. argotaenia.
Frequency and Distribution of EST-SSRs
e mean length of unigenes (721 bp) of A. argotaenia was
considerably longer than that of other conifers, including Pinus
pinaster (495 bp) (Canales et al., 2014), Platycladus orientalis (686
bp) (Hu et al., 2016), and P. a bie s (472 bp) (Chen et al., 2012).
Zalapa et al. (2012) pointed out that longer sequences will increase
the probability to properly design EST-SSR primers. In accordance
with this, we developed 5510 EST-SSRs from the transcriptome
of A. argotaenia, which was signicantly greater than those of A.
formosana (4955) (Li et al., 2016) and Pinus densiora (1953) (Liu et
al., 2015). e most common motif for dinucleotides in A. argotaenia
was found to be AT/TA. e same result was obtained in Picea
spp. (Rungis et al., 2004), Pinus dabeshanensis (Xiang et al., 2015),
and Pseudolarix amabilis (Geng et al., 2015). Ranade et al. (2014)
emphasized that AT/TA was oen ranked as the most abundant
dimer motif in gymnosperms (especially in the 3′ untranslated
regions). A factor related to this phenomenon may be increased A +
T contents. In addition, the most common trinucleotide motif in A.
argotaenia was AAG/CTT, which is similar to that in Cryptomeria
japonica (Ueno et al., 2012), Pinus taeda (Wegrzyn et al., 2014), and
Pinus halepensis (Pinosio et al., 2014), but unlike in P. dabeshanensis
(AGC) (Xiang et al., 2015). It has been noted that AAG/CTT is the
target for methylation in plants (Law and Jacobsen, 2010).
Validation and Polymorphism of EST-SSRs
and Population Genetic Variation
irty-eight of the 60 EST-SSR primers designed for A. argotaenia
enabled to amplify expected products with a success rate of 63.33%,
which is relatively high in comparison to previous studies (Dantas
et al., 2015; Ueno et al., 2015). en 22 polymorphic EST-SSRs
were used to investigate standard genetic diversity and population
genetic structure of four A. argotaenia populations. Only four pairs
of them were tightly linked among each other. Moderate genetic
variation was observed based on the EST-SSRs (PIC = 0.455)
according to the evaluation criteria of polymorphism (moderate:
0.25 < PIC < 0.5) (Botstein et al., 1980). is judgment was also
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Transcriptome of Amentotaxus argotaeniaRuan et al.
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TABLE 3 | Characterization of 38 EST-SSR primer pairs for A. argotaenia.
Locus Primer sequences (5′–3′)Repeat
motif
Allele
size(bp)
Ta(°C) GenBank
accession no.
Putative function
[Organism]
E-value
SHS-1306 F: ACCTCGGGTCCTGTTGAAR:
GGTTGTGGCGAATGCTG
(TAC)6(TAT)5249 54 MG209531 Unknown [Picea sitchensis] 3e-53
SHS-1845 F: TCTGAGATAAGGTGCTTGGGTGR:
ATTTGAGGGCTACAGCGGTT
(GTC)7126 55 MG209532 Unknown [P. sitchensis] 3e-48
SHS-2019 F: AGAGACCACCAACGACGAACR:
CAGCGGCAGCATACCATT
(TCC)7298 55 MG209533 hypothetical protein AMTR_
s00032p00067030 [Amborella
trichopoda]
3e-25
SHS-2589 F: CTAACCCTATCCCTAACCTCTTTCR:
GTTTCATTCCAGGCACTCTCA
(GAA)5159 57 MG209534 Unknown [P. sitchensis] 2e-121
SHS-5811 F: TAGATTTAGTTCCCAGCGGTGR:
GATTGATTTCGGCTCGTGTAT
(AG)8279 53 MG209535 Not found —
SHS-6181 F: TTCTACTTCTGCTGCTGGTGTR:
GCATTGGTCTTCCTCCTTTAC
(TTC)7214 54 MG209536 hypothetical protein
AMTR_s00003p00222410 [A.
trichopoda]
0
SHS-17706 F: CTCTTTGGGAGAAGTATTAGCR:
TGGTCACTCGTGGACATTA
(AAGA)5134 53 MG209537 PREDICTED: uncharacterized
protein LOC103491482
isoform X2 [Cucumis melo]
5e-45
SHS-18170 F: GAGAGCCCACGGTCCTGTR:
AGTCCCATCATCCACCTATCA
(GAA)6300 53 MG209538 PREDICTED: zinc finger
protein 43-like [Pyrus x
bretschneideri]
1e-10
SHS-18213 F: AAAGTCGGGTGATTACAGAGCR:
TCCTTCGTGGAATGTTTATGA
(GA)7397 54 MG209539 Not found —
SHS-18563 F: ACCTCCTACACCCCCTTCTR:
AACTCCACCATACGCATCTTA
(GAA)6236 54 MG209540 Unknown [P. sitchensis] 6e-97
SHS-19735 F: CCCAAAGAAAGGGCAAGAR:
CGGCGGATGGTAATGTG
(CGC)7278 53 MG209541 Unknown [P. sitchensis] 3e-64
SHS-20137 F: CTGTCAGGCATTTCTGGGTCTR:
CGATTTTCATTTTGTTTGGTCTG
(CTT)7257 58 MG209542 Not found —
SHS-20198 F: CATTCTCACACCCTTGTATTGCTR:
CATCTTCACCATTTCTCTGTAGTCTT
(TA)8259 58 MG209543 transcription factor AP2 [Taxus
cuspidata]
8e-117
SHS-21264 F: CTCGTCCAAGAAGAACCATACR:
CATCATAAACCACTTAGCAAATAC
(GAG)6400 56 MG209544 PREDICTED: uncharacterized
protein LOC104240103
[Nicotiana sylvestris]
7e-41
SHS-21490 F: GAGGAAGAGGGTTTTGGTCATR:
AGTAGGCGTCTTTGGCGTT
(TAA)6190 58 MG209545 hypothetical protein PRUPE_
ppa010075mg [Prunus
persica]
1e-59
SHS-22515 F: CACATCCTCCGCCGACTR:
TTGCTGTTTTACCGAGAAGAAG
(TAC)6(TAT)5266 57 MG209546 Unknown [P. sitchensis] 2e-53
SHS-23191 F: ACCCAGTTGTGGTAGGAGCATR:
AAAGTGTGAAACATCCCAAAGC
(GAG)6161 57 MG209547 Not found —
SHS-23195 F: TGACAACGAGAACGAAGAACATAACR:
GTCTGTAAGCCAACGCTGAGG
(AGA)6115 57 MG209548 hypothetical protein
SELMODRAFT_451322
[Selaginella moellendorffii]
2e-41
SHS-24187 F: CCTAATGGTGAATAACTTGTGCTCR:
GCGAGTTTCTTGCTAAATGCTT
(TCTT)5330 58 MG209549 Not found —
SHS-24301 F: TACCTGACTGGACTGCTGAATR:
ATGTTAGAGGAATACGATAGGCT
(CCG)6377 57 MG209550 Unknown [P. sitchensis] 1e-32
SHS-26622 F: AGATACTCTTGTTTCAGGAGCATTR:
CAACCCAGGACATCACCATAG
(AAG)7228 57 MG209551 Not found —
SHS-26840 F: GGGCGGAGGAGAATGGTCR:
TGGGCTGCTGAAATAGGAAAC
(GGA)6250 57 MG209552 PREDICTED: uncharacterized
protein LOC104602979,
partial [Nelumbo nucifera]
1e-65
SHS-28207 F: CAATCGGATAAGGTGTTTCTR:
CGAATAGTGGTAATCAAATAGG
(GA)16 379 52 MG209553 Unknown [P. sitchensis] 0
SHS-28326 F: GTATGGAAGGGAGGCGAAATR:
GCCGCTGTGGTTGTGAAG
(ATA)6143 57 MG209554 Unknown [P. sitchensis] 4e-29
SHS-28474 F: AATAAGAATAGGAGGGGTGAAGACR:
GAGACAGAGGATTTGTAACGGAG
(CGG)6218 57 MG209555 PREDICTED: mediator of RNA
polymerase II transcription
subunit 30-like isoform X1 [N.
nucifera]
1e-16
SHS-28717 F: CGTATCCCTGTTGATTCATTTTCR:
GGTTGTATCATTCAGTCCCATTG
(GAAA)6240 57 MG209556 Not found —
(Continued)
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Transcriptome of Amentotaxus argotaeniaRuan et al.
7
TABLE 4 | Genetic diversity statistics for four A. argotaenia populations based on 22 polymorphic EST-SSR primers.
JQS (N = 15) CP (N = 13) QNS (N = 12) WGS (N = 16)
Locus NaNeHoHeNaNeHoHeNaNeHoHeNaNeHoHePIC
SHS-1306 2 1.923 0.000*‡0.480 2 1.166 0.000* 0.142 2 1.180 0.000* 0.153 2 1.600 0.000*‡0.375 0.395
SHS-2019 2 1.301 0.267 0.231 3 1.807 0.462 0.447 2 1.180 0.000* 0.153 2 1.133 0.000* 0.117 0.429
SHS-6181 1 1.000 0.000 0.000 1 1.000 0.000 0.000 2 1.087 0.083 0.080 3 2.327 0.000*‡0.570 0.225
SHS-17706 3 1.822 0.600 0.451 4 1.931 0.231‡0.482 3 2.880 0.500* 0.653 3 2.667 0.500* 0.625 0.605
SHS-18213 4 1.531 0.000*‡0.347 2 1.742 0.000*‡0.426 4 1.714 0.000*‡0.417 3 1.910 0.000*‡0.477 0.402
SHS-18563 1 1.000 0.000 0.000 1 1.000 0.000 0.000 2 1.800 0.000*‡0.444 3 2.844 0.000*‡0.648 0.371
SHS-19735 4 2.217 0.600 0.549 2 1.352 0.000*‡0.260 2 1.385 0.000*‡0.278 3 1.684 0.250* 0.406 0.393
SHS-20198 2 1.923 0.000*‡0.480 3 1.610 0.000*‡0.379 4 3.236 0.250*‡0.691 3 2.032 0.000*‡0.508 0.560
SHS-24187 4 2.284 0.467 0.562 3 2.048 0.692 0.512 3 2.667 0.667 0.625 4 2.090 0.375* 0.521 0.528
SHS-26622 6 4.091 0.800 0.756 7 4.694 1.000 0.787 4 2.743 1.000 0.635 4 2.498 1.000 0.600 0.707
SHS-26840 4 2.761 0.867 0.638 4 2.467 0.462 0.595 3 2.268 0.583 0.559 2 2.000 1.000* 0.500 0.514
SHS-28207 4 2.663 1.000 0.624 5 3.282 1.000 0.695 5 3.840 0.917* 0.740 3 1.684 0.500 0.406 0.701
SHS-28474 4 1.772 0.000*‡0.436 3 1.610 0.000*‡0.379 3 2.323 0.000*‡0.569 4 1.707 0.000*‡0.414 0.456
SHS-28717 2 1.471 0.000*‡0.320 2 1.742 0.000*‡0.426 3 2.323 0.000*‡0.569 2 1.280 0.000*‡0.219 0.581
SHS-31463 1 1.000 0.000 0.000 2 1.257 0.231 0.204 1 1.000 0.000 0.000 2 1.133 0.125 0.117 0.084
SHS-31908 1 1.000 0.000 0.000 3 1.857 0.000*‡0.462 2 1.800 0.000*‡0.444 3 1.293 0.000*‡0.227 0.297
SHS-32587 2 1.471 0.000*‡0.320 3 1.610 0.000*‡0.379 4 2.595 0.083*‡0.615 3 2.612 0.000*‡0.617 0.534
SHS-32686 2 1.800 0.267 0.444 2 1.352 0.308 0.260 2 1.180 0.000* 0.153 2 1.969 0.125‡0.492 0.399
SHS-32939 3 1.495 0.400 0.331 2 1.451 0.385 0.311 2 1.180 0.167 0.153 2 1.992 0.563 0.498 0.393
SHS-34629 2 1.301 0.267 0.231 2 1.649 0.538 0.393 2 1.385 0.000*‡0.278 2 1.600 0.000*‡0.375 0.473
SHS-35453 2 1.800 0.667 0.444 2 1.988 0.000*‡0.497 2 1.882 0.583 0.469 3 2.667 0.500* 0.625 0.579
SHS-38297 2 1.301 0.267 0.231 2 1.451 0.385 0.311 2 1.087 0.083 0.080 1 1.000 0.000 0.000 0.384
N, number of individuals of each populations; Na, number of alleles per locus; Ne, number of effective alleles per locus; Ho, observed heterozygosity; He, expected
heterozygosity; PIC, polymorphism information content; *significant deviation from the Hardy–Weinberg equilibrium (p < 0.001); ‡significant possibility of the presence
ofnull alleles detected by MICRO-CHECKER.
TABLE 3 | Continued
Locus Primer sequences (5′–3′)Repeat
motif
Allele
size(bp)
Ta(°C) GenBank
accession no.
Putative function
[Organism]
E-value
SHS-30422 F: TTCCTTCTACTCCCTCTTCTATGTCR:
AACTGCTTACCTAAATGGTGCTG
(CTT)6163 57 MG209557 PREDICTED: probable
cellulose synthase A catalytic
subunit 5 [Phoenix dactylifera]
0
SHS-31463 F: ATGGATGGCAGGATTGGATR:
AACAAATAAGGAAGAAGGTGGTAGT
(TTG)6182 57 MG209558 Not found —
SHS-31820 F: TTTGGTTCCATACCTGCTCCTR:
TTCGTGGTCACTCTTTTCCCT
(GAT)6149 57 MG209559 Unknown [P. sitchensis] 5e-172
SHS-31908 F: CCAGACTTGCCACATCAGCR:
AACCCACAACCCACCAGAG
(ATG)5(AGG)7395 57 MG209560 Unknown [P. sitchensis] 4e-11
SHS-32587 F: AAATGAGGAATAAGTAGGTGAAGTTR:
GCACATTAGGGTTCCTGATTAC
(AGA)6254 57 MG209561 Not found —
SHS-32686 F: CAACCCGTCCCTTGCTTTAGR:
CCTCTGCGTCCTTGTTGTTATC
(GGCAG)5302 57 MG209562 Unknown [P. sitchensis] 6e-176
SHS-32939 F: TGGAAAAAACCACAGACGACTCR:
GCCCTCAAACACAAAAGCAG
(ATA)7143 56 MG209563 Unknown [P. sitchensis] 1e-94
SHS-34629 F: CTGGACAAAGAGAGCAACGGTR:
AATGGCGACACAAGTGAGAAGT
(CTC)7222 56 MG209564 Hypothetical protein
AMTR_s00032p00067030 [A.
trichopoda]
2e-19
SHS-35222 F: TGCTGCCTAAACACAATGTCTCTR:
CACAAGTCTTCCTTTTCCCTAATG
(TG)9121 56 MG209565 Not found —
SHS-35453 F: GTTGAGCATTGATTTAGATGTTCGR:
TTTCCCCTCCTCTTTCTTTGAC
(TGA)8189 55 MG209566 PREDICTED: uncharacterized
protein LOC104596414
isoform X2 [N. nucifera]
2e-68
SHS-38297 F: TTACCAACGCCAAATGCTGR:
ACCCTACTCCCACTCCCTTCT
(GAGATG)7154 55 MG209567 hypothetical protein
AMTR_s00099p00142540 [A.
trichopoda]
1e-24
SHS-39519 F: TTGTGCCTCTTCAAGGAGTAGTR:
GAGAATCTTCCCTGTCGGTC
(CTC)6261 55 MG209568 ACC synthase-like [Picea
glauca]
0
Ta, annealing temperature; bold font, polymorphic loci.
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Transcriptome of Amentotaxus argotaeniaRuan et al.
8
lent support by such genetic parameters as the average of observed
alleles, observed heterozygosity, expected heterozygosity, and the
percentage of polymorphic band. In contrast, previous researches
detected low levels of genetic diversity in A. argotaenia by using
ISSRs and genomic SSRs (Ge et al., 2005; Ge et al., 2015). ese
inconsistencies highlighted the importance to investigate genetic
variation of A. argotaenia using multiple markers.
Accurate estimate of genetic diversity is very useful for
conservation and management of genetic resources (Cardoso et al.,
1998; Wang et al., 2018b). Compared to other conifers, we observed
a moderate EST-SSR variation in A. argotaenia (Supplementary
Tabl e 4). Similar levels of the EST-SSR variation were found in its
closely related species A. formosana as well (Li et al., 2016). e
moderate level of functional diversity, together with the nding
that A. argotaenia did not experience a recent bottleneck, implies
that the species still has essential evolutionary potential to adapt to
the changing environment (Frankham, 2010).
We detected a marked genetic dierentiation among
A. argotaenia populations in comparison to other conifers
(Supplementary Table 4). Similar ndings were obtained by
using chloroplast intergenic spacer, mitochondrial intron, and
genomic microsatellite data (Ge et al., 2015). e dispersal
distance of pollen and seed in conifers is generally less than 2 and
20 km, respectively (Fu et al., 1999b; Cain et al., 2000; Sima, 2004;
Zhang et al., 2005; Lu, 2006). As for A. argotaenia, its pollen and
seed exchanges may be further hindered because of preferring
to grow under forest canopies (Ge et al., 2015). It is thus
reasonable to speculate that the genetic dierentiation pattern of
A. argotaenia is highly linked to restricted between-population
gene ow (genetic exchange via pollen and seed). Moreover, the
establishment of climate- or habitat-linked genotypes should
also be considered, since we used functional markers to perform
studies (Jump and Peñuelas, 2005; Ortego et al., 2012).
CONCLUSION
We generated the leaf transcriptome of A. argotaenia by using
Illumina sequencing technology. A total of 62,896 unigenes were
assembled, annotated, and classied. Based on the transcriptome
data, 5510 EST-SSRs were identied from 4830 SSR-containing
unigene sequences. Among them, 60 were randomly selected for
the development of potential functional markers. Consequently,
22 polymorphic EST-SSR markers were developed and used
to reveal a moderate level of functional diversity, along with
marked genetic structure and the lack of genetic bottleneck, in A.
argotaenia. is study has provided eective EST-SSR markers for
measuring the evolutionary potential of A. argotaenia in response
to environmental changes.
DATA AVAILABILITY STATEMENT
All Illumina clean data generated for this study was deposited
at the Sequence Read Archive (SRA) of the National Center for
Biotechnology Information (https://www.ncbi.nlm.nih.gov/sra/
SRX3296043[accn]). e Bioproject number and Biosample
number for clean data are PRJNA413732 and SAMN07764634,
respectively. irty-eight EST-SSR sequences generated for
this study were deposited at GenBank with accession numbers
MG209531-MG209568.
AUTHOR CONTRIBUTIONS
e author XR conducted the experiments and ZW completed
the data analysis. e two authors contributed equally to this
work. YS designed the experiments and wrote the manuscript,
and TW corrected the manuscript.
FUNDING
is work was supported by the National Natural Science
Foundation of China (31370364, 31570652, 31670200, 31770587,
and 31872670); the Natural Science Foundation of Guangdong
Province, China (2016A030313320 and 2017A030313122);
Science and Technology Planning Project of Guangdong
Province, China (2017A030303007); Project of Department
of Science and Technology of Shenzhen City, Guangdong,
China (JCYJ20160425165447211, JCYJ20170413155402977,
and JCYJ20170818155249053); and Science and Technology
Planning Project of Guangzhou City, China (201804010389).
ACKNOWLEDGMENTS
The authors thank Dr. Q. Fan of the School of Life Sciences,
Sun Yat-sen University, for assistance with the collection of
plant materials.
SUPPLEMENTARY MATERIAL
e Supplementary Material for this article can be found online at:
https://www.frontiersin.org/articles/10.3389/fgene.2019.01014/
full#supplementary-material
SUPPLEMENTARY FIGURE 1 | Length distribution of assembled unigenes
generated from A. argotaenia transcriptome.
FIGURE 2 | Population genetic structure analysis of A. argotaenia based on
EST-SSRs. JQS, Population Jiuqushui; CP, Population Chuanping; WGS,
Population Wugongshan; QNS, Population Qiniangshan.
Frontiers in Genetics | www.frontiersin.org October 2019 | Volume 10 | Article 1014

Transcriptome of Amentotaxus argotaeniaRuan et al.
9
SUPPLEMENTARY FIGURE 2 | Functional classification of A. argotaenia
unigenes based on KOG annotation.
SUPPLEMENTARY FIGURE 3 | Functional classification of A. argotaenia
unigenes based on KEGG annotation.
SUPPLEMENTARY FIGURE 4 | The optimum number of clusters (K) estimated
with STRUCTURE analysis based on LnP(D) (A) and hoc statistic ΔK (B).
SUPPLEMENTARY FIGURE 5 | Amplification products generated using
EST-SSR primer pair, SHS-26622, were separated by electrophoresis in 6%
denaturing polyacrylamide gel. The expected allele size was 228 bp and the
annealing temperature was 57°C. Lanes 1-15, 16-28, 29-40, and 41-56 were
products of A. argotaenia individuals from populations JQS (Jiuqushui), CP
(Chuanping), QNS (Qiniangshan), and WGS (Wugongshan), respectively; Lane M:
50 bp ladder.
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Conict of Interest: e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could be construed as a
potential conict of interest.
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Frontiers in Genetics | www.frontiersin.org October 2019 | Volume 10 | Article 1014