
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39245775
71887
10.1038/s41598-024-71887-1
Article
Mining expressed sequence tag (EST) microsatellite markers to assess the genetic differentiation of five Hynobius species endemic to Taiwan
http://orcid.org/0009-0000-2408-4411
Chen Jou-An 1
Yu Pei-Ju 1
Jheng Sheng-Wun 1
Lin You-Zhu 1
http://orcid.org/0000-0002-4130-310X
Sun Pei-Wei 2
http://orcid.org/0000-0003-1932-8703
Ko Wen-Ya 3
Lin Chun-Fu spring@tbri.gov.tw

4
http://orcid.org/0000-0002-5120-6960
Ju Yu-Ten ytju@ntu.edu.tw

1
1 https://ror.org/05bqach95 grid.19188.39 0000 0004 0546 0241 Department of Animal Science and Technology, National Taiwan University, No. 50, Ln. 155, Sec. 3, Keelung Rd., Da’an Dist., Taipei City, 106 Taiwan
2 https://ror.org/059dkdx38 grid.412090.e 0000 0001 2158 7670 School of Life Science, National Taiwan Normal University, Taipei, 116 Taiwan
3 https://ror.org/00se2k293 grid.260539.b 0000 0001 2059 7017 Faculty of Life Sciences and Institute of Genome Sciences, National Yang Ming Chiao Tung University, Taipei, 112 Taiwan
4 Zoology Division, Taiwan Biodiversity Research Institute, No. 1 Minsheng East Road, Jiji, Nantou, 552 Taiwan
8 9 2024
8 9 2024
2024
14 2089811 7 2024
2 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Taiwan harbors five endemic species of salamanders (Hynobius spp.) that inhabit distinct alpine regions, contributing to population fragmentation across isolated “sky islands”. With an evolutionary history spanning multiple glacial-interglacial cycles, these species represent an exceptional paradigm for exploring biogeography and speciation. However, a lack of suitable genetic markers applicable across species has limited research efforts. Thus, developing cross-amplifying markers is imperative. Expressed sequence-tag simple-sequence repeats (EST-SSRs) that amplify across divergent lineages are ideal for species identification in instances where phenotypic differentiation is challenging. Here, we report a suite of cross-amplifying EST-SSRs from the transcriptomes of the five Hynobius species that exhibit an interspecies transferability rate of 67.67%. To identify individual markers exhibiting cross-species polymorphism and to assess interspecies genetic diversity, we assayed 140 individuals from the five species across 84 sampling sites. A set of EST-SSRs with a high interspecies polymorphic information content (PIC = 0.63) effectively classified these individuals into five distinct clusters, as supported by discriminant analysis of principal components (DAPC), STRUCTURE assignment tests, and Neighbor-joining trees. Moreover, pair-wise FST values > 0.15 indicate notable between-cluster genetic divergence. Our set of 20 polymorphic EST-SSRs is suitable for assessing population structure within and among Hynobius species, as well as for long-term monitoring of their genetic composition.

Keywords

Hynobius
EST-SSRs
Transcriptome
Taiwanese salamander
Microsatellite
Subject terms

Evolutionary genetics
Phylogenetics
Population genetics
issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Taiwan represents the southernmost limit of the distribution of salamanders belonging to Family Hynobiidae1, and harbors five species: Hynobius fucus, H. sonani, H. glacialis, H. formosanus, and H. arisanensis2. These five species form a monophyletic group in Genus Hynobius3, and they are designated as Vulnerable, Endangered, or Critically Endangered in their natural habitats by the International Union for the Conservation of Nature4. Amphibian habitats face challenges due to global warming5 and intensified droughts6. These environmental stressors may impede their adaptive capacity within microhabitats, potentially resulting in reduced effective population sizes, genetic differentiation, and bottleneck effects7. Previous research has reported fragmented and restricted distributions for the five species, which have been described as "sky island" alpine species2,8. Therefore, it is crucial to devise effective strategies for assessing fine-scale population structures across these species and to comprehensively determine their genetic composition, which necessitates robust cross-species genetic markers.

Microsatellite sequences, also known as simple sequence repeats (SSRs), consist of short tandem repeats found in both coding and non-coding regions of nuclear and organellar DNA9. Due to their high mutation rate of 103 to 106 events per locus per generation, microsatellite markers exhibit significant evolutionary instability10,11. This inherent instability enables detection of potential divergence events among species and populations based on differing repeat numbers12. The rapid advancement of next-generation sequencing (NGS) technologies has facilitated efficient acquisition of SSRs from genomic DNA or transcriptome cDNA. SSRs obtained directly from whole-genome sequencing analyses predominantly represent anonymous DNA sequences. However, due to the large genomes and abundant non-functional repetitive sequences in amphibians, direct utilization of genomic SSRs often results in issues of a stochastic nature and low cross-amplification13,14. Expressed Sequence Tag Simple Sequence Repeats (EST-SSRs), also known as transcriptome-derived SSRs, are microsatellite markers extracted from expressed sequence tags (ESTs) of transcriptome RNA sequences located explicitly in the exons of cDNA sequences. Compared to microsatellite sequences located in introns, EST-SSRs tend to be more conserved than anonymous intron or non-transcript markers, resulting in superior cross-species transferability. This characteristic has proved especially beneficial when studying large-genome species, such as salamanders, and it reduces the sequencing effort required in restriction site-associated DNA (RAD)-based sequencing13. Furthermore, since EST-SSRs are directly scanned from a given species' coding DNA, they may exhibit associations with phenotypic traits and thus prove useful in analyzing hybrid zones15,16. They can also be used to better interpret differences in gene expression and the effects of spatial, environmental, or temporal factors on selection processes17. These characteristics facilitate studies on species that can be challenging to distinguish based on phenotypic traits and to investigate genetic structure and introgression from populations in contact zones18.

Abundant genomic SSRs have been developed for Order Caudata and been applied to species conservation, policy management, determination of evolutionary histories, and detection of hybridization and genetic introgression19–22. EST-SSRs have been instrumental in studies and long-term monitoring of amphibian population genetics, which significantly contributes to their conservation and evolutionary research15.

Genetic research on Taiwanese salamanders began in 199723, with Maki24 presenting the first description of three hynobiid salamanders from the island. Before the mid-twentieth century, most research on salamanders in Taiwan relied on morphological traits such as color patterns or skeletal features25–29. Lue and Lai23 used 25 allozyme loci to detect genetic divergence among Taiwanese salamanders and confirmed the validity of the species H. arisanensis. Lai and Lue2 later identified two new Hynobius species in Taiwan, i.e., H. glacialis and H. fucus, using morphology and mitochondrial DNA. However, information on genetic differentiation and structure of nuclear DNA between and within the five Taiwanese species remains limited. Therefore, the development of cross-species nuclear genetic markers is essential since, given the threatened status of all five species, population genetic analyses could inform deeper insights into the genetic structure of these five species, including potential interspecies hybridization or introgressions.

We had three specific aims for this study: (1) to develop cross-species transcriptome-derived EST-SSR markers for the five Hynobius species in Taiwan; (2) to understand interspecies and intraspecies genetic differentiation and diversity of all five species; and (3) to construct an EST-SSR-based phylogeny and compare it to one developed using mitochondrial DNA.

Materials and methods

Sample collection, RNA extraction, and DNA purification

Fresh tail tissue was collected from one individual of each of the five salamander species in Taiwan (H. fucus, H. sonani, H. glacialis, H. formosanus, and H. arisanensis) for RNA extraction and transcriptome sequencing. Due to the limited tissue available, these individuals were not included in the 140 samples used for DNA sequencing. Instead, other individuals from the same populations were selected for DNA analysis to ensure consistent population representation. Tail tissues were immediately subjected to RNA purification upon excision. Total RNA (18,032, 30,240, 19.14, 23,350, and 8120 ng) was extracted using TRIzol (Invitrogen, CA) following the manufacturer’s instructions for cDNA library construction.

A total of 140 samples, comprising 20 individuals of H. glacialis and 30 individuals of each of the other four species, were collected for subsequent DNA extraction/purification and population genetic analysis. Sampling information is presented in Table 1 and Fig. 1. The specimens were anesthetized by bathing them in 0.2% MS222 (ethyl3-aminobenzoate methanesulfonate) for 5 min. Approximately 30 µg of tail tissue was collected and stored in 95% ethanol. Genomic DNA was extracted from the tail tissue using a Wizard Genomic Extraction and Purification Kit (Promega, WI) according to the manufacturer’s procedure.Table 1 Hynobius species, distribution, numbers of sampled individuals (N), and elevation range.

Taxonomic assignment	Mountain ranges	N	Locality number1	Elevation range (m)	
H. fucus	Mt. Xue	28	1–8	1273–2290	
Northern Central Mountain Ridge	2	9	1810–1899	
H. sonani	Mt. Xue	13	10–20	2410–3260	
Northern Central Mountain Ridge	17	21–33	2211–2685	
H. glacialis	Middle Central Mountain Ridge	20	34–39	2593–3408	
H. formosanus	Middle Central Mountain Ridge	30	40–55	2518–3111	
H. arisanensis	Sourthern Central Mountain Ridge	24	55–67, 73–84	2024–3221	
Mt. Jade	5	56, 68–71	2487–3625	
Mt. Alishan	1	72	2140	
1Locality numbers are shown in Fig. 1

Fig. 1 Sampling sites for the five species of Taiwanese salamanders. The gray scale represents altitude in meters. Numbers represent locality numbers.

Species identification and phylogeny construction using mitochondrial sequences

H. glacialis, H. fucus, and H. arisanensis were assigned as species based on morphological data2, whereas H. formosanus and H. sonani were first identified by Nishikawa, et al.30. All experimental individuals used in the current study were identified based on morphological characteristics. Due to taxonomic confusion stemming from the original descriptions in Maki24, discrepancies have existed for more than a century in the classification of H. formosanus and H. sonani across Taiwan and Japan. Herein, we adopted the scientific names defined by Nishikawa, et al.30.

We sequenced the mitochondrial cytochrome b (cytb, 1141 basepairs (bp)) gene to investigate genetic divergence among target species. All 140 specimens (Table 1; Fig. 1) were subjected to cytb sequence amplification using the primer pair HT-cytb-L 14014 (5ʹ-ACAAACAGCCGCCAACACTAA-3ʹ) and HT-cytb-H 15444 (5ʹ-GAGAGGCCTGGAAGAAATGGA-3ʹ) or, for H. fucus, HF-ND6-L13994 (5ʹ-ACAAACAGCCGCCAATACTAA-3ʹ) and HF-tRNA-H15424 (5ʹ-AAGGCCTGGAAAAAATAGA-3ʹ). Thermocycling conditions for the polymerase chain reaction (PCR) were: initial denaturation (94 °C, 2 min); 36 cycles of denaturation (94 °C, 30 s), annealing (61 °C, 30 s), and extension (72 °C, 1 min and 40 s); and a final extension (72 °C, 10 min). Each PCR was performed in a 25-µL volume containing 100 ng of template DNA, 10 µM of each primer, 10X PCR buffer for Blend Taq (TOYOBO, Japan), 2 mM each dNTP Mix, and 2.5U Blend Taq Plus (TOYOBO, Japan). PCR products were analyzed using a 1% agarose gel to verify amplification and rule out possible contamination based on comparison to negative controls. PCR products were then purified using a GenepHlow™ Gel/PCR Kit (DFH300) (Geneaid, Taiwan), before being sequenced using an ABI PRISM 3730 capillary sequencer (Applied Biosystems, USA). The resulting DNA sequences were assembled in EditSeq (DNASTAR Inc.) and aligned using Megalign31. The haplotype of each specimen was determined using DnaSP 632. A maximum likelihood (ML) phylogenetic tree was constructed from the sequences in MEGA X (Molecular Evolutionary Genetics Analysis)33, with 1000 bootstrap replicates under the Hasegawa-Kishino-Yano model34. The cytb sequences of Hynobius boulengeri, H. retardatus, and H. kimurae (GenBank accession numbers AB266675, AB363609, and AB266674) were used as outgroups. A bootstrap value of > 70% for a clade corresponds to a probability of 95% confidence35. A Bayesian inference (BI) phylogenetic tree was constructed using BEAST version 2.6.636–38, with four independent Markov Chain Monte Carlo (MCMC) runs for 108 generations and tree sampling every 1,000 generations. Effective sample size (ESS) was evaluated using TRACER 1.7.139, with the first 10% of trees discarded as burn-in. A maximum clade credibility tree was constructed using TreeAnnotator version 2.6.6., and it was visualized using FigTree 1.4.439.

Transcriptome sequencing, EST-SSR identification, and primer design

Sequencing data were generated using an Illumina NovaSeq platform, and adapter sequences were removed using Cutadapt version 1.4.240. Quality trimming of the sequencing reads, based on Phred quality scores and error probabilities, was performed using the Seqtk program41, with a minimum length of 35 bp and an error probability < 0.05. Next, de novo assembly was conducted using Trinity version 2.142 to align and group overlapping transcript subsequences from the original reads into clusters based on shared sequence content. Finally, the trimmed reads were pooled and used for transcript assembly. MIcroSAtellite (MISA)43 and CD-hit44 were then used to identify microsatellite sequences in these transcripts. To obtain highly polymorphic EST-SSRs that would be applicable across species, we selected contigs according to the following criteria: (1) mononucleotides and short SSRs (total length < 15 bp) were excluded to enhance potential cross-species polymorphism; (2) a total length of between 18 and 30 bp (with at least three, four, or five hexanucleotide repeats); (3) cross-species similarity > 90% (based on MISA and cd-hit data).

To avoid potential linkage disequilibrium and considering the difficulty of designing primers in flanking regions, we excluded SSRs allocated at the beginning or end of a unigene or those from the same unigenes (with > 70% sequence identity or from the same clusters). After screening based on these criteria, we designed primer pairs using Primer3 Input version 0.4.045. Each pair of primers was designed according to: primer length of between 18 and 27 bp; annealing temperature of between 50 and 70 °C; and GC content of between 20 and 80%. The optimum size range for resulting PCR products was 100–300 bp.

Amplification and cross-species transferability assessment of EST-SSRs

Optimal annealing temperatures for the candiated EST-SSRs were assessed by means of temperature gradient PCR, and those demonstrating clear and specific results following 1.8% agarose gel electrophoresis were selected. Subsequently, selected primer pairs were employed to amplify the EST-SSRs from the 140 specimens to assess interspecies transferability and polymorphism. The transferability rate, defined as the proportion of EST-SSRs amplified specifically within all five species using the designed primer pairs, was determined.

PCR amplification was conducted using the Blend Taq Plus system (TOYOBO, Japan). We adopted a modified protocol involving reaction mixtures of 10 µL containing 6.5 µL of ddH2O, 1.0 µL of 10X PCR buffer for Blend Taq, 1.0 µL of each dNTP (2.0 mM), 0.5 µL of the forward and reverse primers (10 µM), 1.0 µL of the DNA template (50 ng/µL), and 0.25 µL of Blend Taq Plus (2.5 U/µL). Reactions were conducted in an ABI PCR machine under the following conditions: 5 min at 94 °C; followed by 35 cycles of 30 s at 94 °C, 30 s at 57–61 °C, 30 s at 72 °C; and a final elongation step of 10 min at 72 °C. PCR amplicon size was measured by means of ABI 3730 capillary electrophoresis (Applied Biosystems, CA) at the National Center for Genome Medicine (NCGM), Taiwan. The ABI 3730 outputs were read using Peak Scanner version 1.0 (Applied Biosystems, CA). To detect genotyping errors in EST-SSRs loci, allele dropout was tested in MICRO-CHECKER version 2.2.346.

Cross-species polymorphism and genetic structure analysis

Cross-species polymorphism was evaluated according to the number of alleles (k), observed heterozygosity (Ho), expected heterozygosity (He), and polymorphic information content (PIC), all calculated in Cervus version 3.0.347. To streamline species identification and phylogenetic analyses, we opted for loci with a PIC value > 0.25, ensuring moderate to high informativeness (0.25 < PIC < 0.5). Allelic richness (AR) was estimated using FSTAT version 2.9.448. Hardy Weinberg equilibrium (HW) was assessed using Genepop version 4.7.549, and linkage disequilibrium (LD) was estimated in Arlequin version 3.5.250.

To infer interspecies and intraspecies genetic differentiation, the pairwise fixation index (FST) and corresponding P value were computed using Arlequin version 3.5.250. Discriminant Analysis of Principal Components (DAPC) was conducted in the R package adegenet51, retaining the first 50 principal components (PCs) that explained 50% of genetic variability. Population structure was further examined using STRUCTURE 2.3.452, with 10 iterations for genetic clusters (K) from 1 to 10 and running the Markov Chain Monte Carlo (MCMC) algorithm for 1,000,000 generations with an initial burn-in of 100,000 generations, followed by delta K estimation using Structure Harvester53.

Furthermore, admixture proportions were estimated using CLUMPP54, providing insights into the probability of individual assignment to population clusters and facilitating assessment of genetic differentiation among or within species according to admixture proportions (referred to as Q values). Finally, we constructed a Neighbor-Joining tree in Populations version 1.2.3255, and calculated the dissimilarity matrix from 1,000 bootstraps.

Results

De novo assembly, EST-SSR mining, and marker development

In this study, we conducted transcriptome sequencing of five Taiwanese salamander species, generating a total of approximately 43 million to 102 million raw reads from each species (Table S1). Following adaptor trimming and removal of low-quality reads, we obtained 102,318,304, 98,661,924, 82,969,159, 100,536,634, and 42,857,286 clean reads for these species, respectively (Table S1). Total nucleotide numbers after quality trimming (QT) exceeded 10 Gb for each species, except for H. arisanensis (Table S1). Using the Trinity program, we assembled the clean reads from each species into 170,727, 209,217, 217,222, 240,877, and 119,546 transcripts, respectively, allowing us to identify 43,035, 54,571, 58,808, 61,019, and 35,557 mRNA unigenes containing microsatellites for the five species.

After excluding primer pairs amplifying mononucleotides, short SSRs, and displaying cross-species similarity of < 90%, we identified 133 EST-SSR loci (Table S2) for subsequent PCR. Ultimately, 89 of the EST-SSRs (Table S2) exhibited cross-species transferability, representing a transferability rate of 67.67%. These loci were labeled with different fluorescent dyes to assess their genotyping efficiency, length of PCR products, and cross-species polymorphism.

Mitochondrial DNA-based phylogeny of the five Hynobius species

The specimens of the five Taiwanese salamander species selected for this study were gathered from geographically distinct regions with minimal overlap, spanning various altitudes. These species display notable phenotypic dissimilarities (Fig. 2). For initial species classification and phylogenetic assessment, cytb haplotyping was performed on the 140 individuals, revealing 89 distinct haplotypes (Table S3) including 17 for H. fucus, 19 for H. sonani, 5 for H. glacialis, 23 for H. formosanus, and 25 for H. arisanensis.Fig. 2 Maximum Likelihood (A) and Bayesian Inference (B) phylogenetic trees of Hynobius spp. H. fucus (orange), H. sonani (green), H. glacialis (yellow), H. formosanus (blue), and H. arisanensis (red). H. retardatus, H. boulengeri, and H. kimurae are outgroups. Numbers on tree branches represent ML bootstrap values (A) or Bayesian posterior probabilities (B).

The phylogenetic trees generated from the BI and ML methods based on these 89 cytb haplotypes presented similar topologies (Fig. 2). Both methods supported monophyly of the Taiwanese salamander species. Clustering of the five species was highly supported (ML bootstrap value > 70, Bayesian posterior probability (BPP) > 0.95), indicating significant differentiation among the cytb sequences among species.

A set of 20 EST-SSR loci uncovers high cross-species polymorphism and genetic diversity in five Taiwanese Hynobius species

We applied the 89 genetic markers to detect interspecies polymorphism across five Taiwanese Hynobius species collected from 84 sampling sites. Of the 89 candidate genetic markers, 20 exhibited cross-species polymorphism (Table 2), resulting in the identification of 184 genotypes across these loci, with allele counts ranging from 3 to 21 (average 9.2) per locus (Table 3). Notably, H. fucus exhibited the lowest average number of alleles (average k = 3.95, range 1–17), whereas H. sonani displayed the highest (average k = 5.9, range 3–15) (refer to Tables S4–S8). Locus 13, Locus 87, and Locus 108 emerged as the most variable in interspecies comparisons, characterized by the highest observed heterozygosities (ranging from 0.157 to 0.563, average Ho = 0.316), PIC value (ranging from 0.298 to 0.883, average PIC = 0.633), and allele richness (ranging from 2.444 to 12.892, average AR = 6.362) (Table 3). Regarding intraspecies genetic diversity, the set of 20 EST-SSR loci exhibited moderate polymorphism in H. fucus, H. formosanus, and H. arisanensis, with PIC values ranging from 0.25 to 0.5, and high polymorphism in H. sonani and H. glacialis, with PIC values > 0.5 (refer to Tables S4–S8). We found no evidence of allelic dropout for any of the 20 loci, but 45% of the EST-SSRs exhibited null alleles, likely stemming from a higher rate of homozygotes, which is indicative of a long evolutionary history, or potentially influenced by sampling biases between populations (Table 3). Departures from Hardy–Weinberg equilibrium (HWE) were observed for certain loci in intraspecies analysis due to heterozygote deficiencies: 12 loci in H. fucus; 18 loci in H. sonani; 17 loci in H. glacialis; 9 loci in H. formosanus; and 14 loci in H. arisanensis (refer to Tables S4–S8). Additionally, some linkage disequilibrium was detected for certain loci in an intraspecies test: 4 loci exhibited > 25% linkage rates in H. fucus; 5 loci displayed rates > 25% in H. sonani and H. glacialis; 3 loci displayed < 15% linkage rates in H. formosanus; and 2 displayed < 15% linkage rates in H. arisanensis (refer to Tables S4–S8).Table 2 Primer sequences, repeat motifs, PCR product sizes, annealing temperatures, and fluorescent dye labels of the 20 EST-SSR loci utilized in this study.

Locus		Primer sequence (5ʹ–3ʹ)	Repeat type	Size range (bp)	Annealing temperature	Fluorescent dye	
Locus13	F	ACACTCCGGCAATACACACC	ATAC	244–318	57	VIC	
R	TCGTGCACTGACTGAACAGG	
Locus26	F	AAGACAGCGCTATATAAGACTTGC	ATT	245–274	61	VIC	
R	AGTCTGGCATCAACGTCTCC	
Locus30	F	CCCCAAATCTGATATTATTATTGGTAA	TCT	195–228	59	VIC	
R	GAGCAGTAGTGGCCTGGAAC	
Locus52	F	GGCAGGTGGCAACAAAGG	GTG	233–257	61	VIC	
R	CGTCACTCTCATTGGCTTCC	
Locus58	F	TGAAAAGGAAGCCAGTGAGG	AGG	188–206	59	6-FAM	
R	CTCTCATCGTCGTCGCTACC	
Locus60	F	GTGCCACAAACTTGGAAACC	GTG	179–185	57	PET	
R	TTATTAAGCGGGCCAAACAC	
Locus76	F	TACAACATTCTGACCAGGAG	GAG	190–288	57	VIC	
R	CGGCTTCTCATCACCTGAG	
Locus79	F	TTGCAGTTGCATGCTTTAGTG	TGGA	218–238	59	VIC	
R	CCGTCTGGTCTTCATTAGCAG	
Locus87	F	CTGCCACAGCACTTAGATTACC	GAT	209–238	59	6-FAM	
R	TGACAACATCGTATCGGAAGG	
Locus88	F	TCTTATGGTCCTGGGATTGC	TCAA	174–209	59	6-FAM	
R	TGCACTGATAGAGATGGATGC	
Locus89	F	GGAGCAAATAAACAGCACACC	CACT	138–159	57	PET	
R	AACAGACGTGGGATACATAGG	
Locus91	F	CCCTCCCCCTCATATTTCC	GTG	186–215	59	6-FAM	
R	GAGCTACTTGGCATCACTTGC	
Locus94	F	CCGGTTCTCCTGTTAGTTGC	GTTGA	192–228	61	6-FAM	
R	GACCGCGCTATACAAAGTCC	
Locus96	F	ACCGTCTCAGCAGCTAAACC	GCA	198–234	57	6-FAM	
R	TTTGTGCTCCTCTGAATGG	
Locus104	F	TGAGCCCAGAGGGTATAAAGC	AC	197–223	61	6-FAM	
R	TGGTGACCTAAGTGCTGTGC	
Locus105	F	AGACTCGGAGCCCTAAATGC	AT	181–205	61	VIC	
R	TATTGCGAATATGGCCAAGC	
Locus108	F	TGTCCAACCTGCAGACTCC	GT	215–257	57	6-FAM	
R	GGCAAGCCTACACCTGTGC	
Locus114	F	GCTCCCATAACGGTTCCTTAG	AT	225–237	61	VIC	
R	CGATCACAAATTCCCAAAGAC	
Locus123	F	CTTAAATCGCTTGCATGACC	AT	228–236	61	6-FAM	
R	AGCTATGTCAACACGCAACC	
Locus131	F	ACCAAAGGACATCGTTCC	CT	160–192	61	VIC	
R	AAGACAGAGACAGCCAACC	

Table 3 Genetic diversity and polymorphic information of the set of 20 EST-SSR loci.

Locus	k	Ho	He	PIC	AR	Allele	Null	
Dropout	Allele	
Locus13	20	0.564	0.895	0.883	12.892	N	N	
Locus26	11	0.219	0.773	0.740	7.472	N	N	
Locus30	11	0.393	0.785	0.760	8.256	N	Y	
Locus52	7	0.259	0.632	0.595	5.118	N	Y	
Locus58	7	0.336	0.807	0.775	6.249	N	Y	
Locus60	3	0.164	0.436	0.351	2.444	N	N	
Locus76	13	0.193	0.697	0.674	8.219	N	Y	
Locus79	5	0.321	0.548	0.496	4.140	N	Y	
Locus87	10	0.521	0.819	0.793	7.639	N	N	
Locus88	10	0.436	0.748	0.719	7.243	N	N	
Locus89	6	0.243	0.588	0.530	4.403	N	N	
Locus91	7	0.271	0.617	0.550	4.186	N	Y	
Locus94	9	0.421	0.752	0.714	6.109	N	N	
Locus96	9	0.329	0.551	0.516	5.191	N	Y	
Locus104	9	0.236	0.720	0.673	6.720	N	Y	
Locus105	7	0.288	0.664	0.606	4.945	N	N	
Locus108	21	0.543	0.814	0.796	11.887	N	N	
Locus114	3	0.157	0.352	0.298	2.444	N	Y	
Locus123	5	0.250	0.655	0.606	4.712	N	N	
Locus131	11	0.173	0.616	0.589	6.966	N	N	
Mean	9.2	0.316	0.673	0.633	6.362	–	–	
k number of alleles, Ho observed heterozygosity, He expected heterozygosity, AR allele richness; HW: *p < 0.05, **p < 0.01, NS; Y represents the presence of allele dropout or null alleles, while N represents the absence of allele dropout or null alleles.

PIC polymorphic information content.

Evaluation of genetic differentiation among the five Hynobius species in Taiwan

To assess if the set of 20 EST-SSRs we had developed could significantly differentiate the five Hynobius species occurring in Taiwan genetically, and to assess intraspecies genetic divergence, we determined pair-wise FST values using 10,000 permutations of the respective allele frequencies (Table 4). We uncovered significant genetic differentiation among the five species (P value < 0.001). The greatest genetic differentiation was observed between H. fucus and the other four species, whereas H. arisanensis and H. formosanus presented the closest genetic relationship, which is consistent with the phylogenetic analysis based on cytb sequences.Table 4 Pairwise FST values (above the diagonal) and associated p-values (below the diagonal) for a set of 20 EST-SSR loci among five Hynobius species.

Species	H. fucus	H. sonani	H. glacialis	H. formosanus	H. arisanensis	
Subpopulation	Mt. Xue	Northern CMR	Mt. Xue	Northern CMR	Middle CMR	Northern group	Southern group	Southern CMR	Mt. Jade, Mt. Alishan	
H. fucus	Mt. Xue	−	0.329	0.361	0.410	0.434	0.376	0.333	0.349	0.415	
Northern CMR	+	−	0.447	0.481	0.502	0.501	0.404	0.448	0.591	
H. sonani	Mt. Xue	+	+	−	0.242	0.350	0.357	0.306	0.386	0.431	
Northern CMR	+	+	+	−	0.319	0.333	0.275	0.362	0.389	
H. glacialis	Middle CMR	+	+	+	+	−	0.359	0.288	0.328	0.388	
H. formosanus	Northern group	+	+	+	+	+	−	0.131	0.241	0.284	
South group	+	+	+	+	+	+	−	0.187	0.216	
H. arisanensis	Sourthern CMR	+	+	+	+	+	+	+	−	0.052	
Mt. Jade, Mt. Alishan	+	+	+	+	+	+	+	NS	−	
N	28	2	12	18	20	18	12	24	6	
+: The significance values after Bonferroni corrections at the 5% nominal level.

NS non-significant after Bonferroni corrections.

*The last row shows the sample size (N) for each subpopulation.

DAPC unveiled a reduction and stabilization of the Bayesian Information Criterion (BIC) value upon partitioning the data into five clusters (Fig. S1). Additionally, distinct clusters were discernible in a scatter plot (Fig. 3). H. fucus and H. sonani were significantly differentiated genetically from the other three species by our EST-SSRs, recapitulating the differentiation observed in our mitochondrial analysis of the five species. In contrast, the set of EST-SSR loci revealed a higher degree of genetic similarity for H. glacialis and H. formosanus than determined from cytb sequences. Next, we constructed a NJ phylogenetic tree, which showed that the five different species of Taiwanese salamanders could be distinguished, with some subclades observed within each species (Fig. 4). Notably, H. fucus was further subdivided into two subclades, i.e., one comprising the Guanwu group (sampling sites 1 to 4) and another encompassing populations across the Central Mountain Ridge (CMR) and northern Mt. Xue (sampling sites 5 to 9). Similarly, our H. sonani samples formed two clades, with one identified as the Mt. Xue population (sampling sites 10 to 19) and the other as the CMR group (sampling sites 20 to 32). In H. glacialis, two major clades were identified. One clade is associated with population 39, comprising individuals 61 and 62. The second clade spans populations 34 to 38, including individuals 63 to 80. Within this second clade, two subclades were detected: one consisting of individuals 70 and 72 to 75, and the other of individuals 64 to 69, 71, and 76 to 80. These findings suggest a structured intraspecies divergence within H. glacialis. Furthermore, a group of H. formosanus specimens from the CMR and in close proximity to a H. glacialis contact zone displayed a close genetic distance to H. glacialis, as corroborated by our DAPC analysis.Fig. 3 Discriminant Analysis of Principal Components (DAPC) scatterplot based on 140 Taiwanese salamanders. Each dot on the plot represents an individual. Colors correspond to Fig. 1. The DAPC plot includes 95% inertia ellipses.

Fig. 4 Neighbor-joining phylogenetic tree based on 140 Taiwanese salamanders. Each line on the plot represents an individual, and colors correspond to Fig. 1. Numbers at the nodes indicate bootstrap values.

The assignment test yielded the highest delta K value when the data were categorized into five clusters (Fig. S2), supporting the DAPC showing interspecies genetic divergence and clearly delineating the five Taiwanese salamander species (Fig. 5). Analyses across higher K values resulted in consistent patterns, with cluster boundaries largely corresponding to species sampling sites (Fig. 5). At K = 6, H. sonani samples were further assigned into two clusters, consistent with the topography of our NJ tree. Similarly, at K = 7, H. fucus also formed two subclusters, mirroring the NJ tree, potentially due to geographic isolation across different mountain ranges.Fig. 5 Population structure among 140 Taiwanese salamanders. Each line on the plot represents an individual, and colors correspond to Fig. 1. Individual numbers are indicated.

Discussion

Transferability of the selected set of 20 EST-SSRs

In the current study, we analyzed the transcriptome sequences of five species of salamander in Taiwan, selecting 133 microsatellite loci based on interspecies sequence similarities of > 90%. Then, we developed PCR primer pairs matching the flanking DNA sequences and assayed PCR product specificity and cross-species amplification to determine EST-SSR transferability. We achieved a cross-amplification rate of ~ 67.67%. Based on a previous mitochondrial sequence analysis3, the common ancestor of the five Taiwanese species of salamanders appeared ~ 20 million years ago, with the common ancestor with Hynobius in Japan appearing approximately 30 million years ago. Dufresne, et al.9 employed three hylid frog species as a model to study EST-SSR transferability, reporting a divergence time of between 10 and 30 million years and EST-SSR transferability between different lineages of 60–80%. These results indicate that the set of 20 EST-SSRs we have developed display a success rate in PCR amplification similar to those of Dufresne, et al.9. Various studies have revealed that the success rate of SSR amplification across species and locus polymorphism are negatively correlated with the genetic distance between the species examined in those studies, including birds56–58, mammals59, fishes60, reptiles61, and salamanders and frogs15,58,62,63. Dufresne, et al.9 compared cross-amplification of 18 anonymous microsatellites and 17 EST-SSRs in nine different species of tree frogs, reporting that EST-SSRs are more suitable for multispecies genetic surveys. In addition, they also confirmed that microsatellite cross-amplification is particularly highly variable among amphibians, suggesting that it should be assessed independently within target lineages. Given that the five species of Taiwanese salamanders we assessed herein are monophyletic according to the phylogenetic tree of cytb sequences, it is reasonable that the EST-SSRs we deployed have high transferability.

Characteristics of the set of 20 EST-SSRs

Here, we sequenced the transcriptomes of five species of Taiwanese salamanders, which uncovered 133 loci (30 di-, 87 tri-, 10 tera-, 3 penta-, and 3 hexa-nucleotide repeats) dislaying cross-species transferability. According to previous studies by Che, et al.64 and Huang, et al.65 on the transcriptomes of Hynobius chinensis and Andrias davidianus, after di-nucleotide repeats, tri-nucleotide microsatellite sequences are the second-most abundant motif type in the transcriptomes of both species. However, although di-nucleotide repeats are more frequent66, adjacent allele pairs are prone to separation, rendering them susceptible to sequence insertions or deletions67. In contrast, we found that tri-nucleotide repeats accounted for the largest proportion of EST-SSR loci in Taiwanese Hynobius.

Genetic information content of the set of 20 EST-SSR loci

Among the 20 EST-SSR loci we ultimately selected for further analysis, 1 is a pentanucleotide, 4 are tetranucleotides, 9 are trinucleotides, and 6 are dinucleotides. All 20 loci exhibited moderate to high information content (PIC values > 0.25) for the 140 specimens we assayed, with expected heterozygosity (He) ranging from 0.330 to 0.883 and observed heterozygosity (Ho) ranging from 0.157 to 0.564, indicating that the informativeness of these loci is sufficient to analyze genetic structure among the five salamander species. Only three loci had PIC values of < 0.5, including the tri-nucleotide Locus 60 (PIC = 0.351), tetra-nucleotide Locus 79 (PIC = 0.496), and dinucleotide Locus 114 (PIC = 0.298). This result indicates that EST-SSR-based assessments of diversity among the five salamander species would not be altered by employing larger nucleotide repeat types. Santibáñez-Koref, et al.68 analyzed CA and CAG tandem repeats motifs in mouse and rat genomes extracted from GenBank (release 99.0) or EMBL (release 49.0), which revealed that the longer CAG microsatellite displayed higher polymorphism68.

We also used our set of 20 EST-SSRs to detect population genetic structure for Hynobius species intraspecies genetic divergence detection. We found that H. sonani populations and H. glacialis populations had relatively high mean PIC values (0.561 and 0.537, respectively), but H. fucus populations had a relatively low mean PIC value (0.369). We further analyzed the PIC value for each of the 20 loci within each species, which uncovered that Locus60 and Locus108 are fixed (one allele, PIC = 0) in H. fucus, and Locus94 and Locus104 in the same species had a PIC value of < 0.2. In our H. sonani, H. glacialis and H. formosanus populations, only Locus30, Locus123 and Locus123, respectively, had PIC values of < 0.2. Four loci in the H. arisanensis populations had PIC values of < 0.2, namely Locus79, Locus87, Locus123 and Locus131. Together, these results indicate that further testing is necessary if this set of 20 EST-SSRs is to be applied to intraspecies population genetic structure in the future.

We detected deviations from Hardy–Weinberg equilibrium in a few loci, with some loci also showing potential linkage disequilibrium. Linkage may arise from selection or inbreeding in different populations69. Alternatively, such as in the case of a Wahlund effect, particular loci in certain populations can exhibit characteristics resembling linkage disequilibrium, leading to seemingly linked genetic traits between independently evolving subpopulations70–73. This phenomenon has been observed in numerous amphibians, reptiles, and birds that have experienced geographical barriers in their evolutionary history, such as Rana uenoi in Korea74, Sceloporus grammicus in Mexico75, and Gyps coprotheres in South Africa76. Additionally, environmental selection can explain why subpopulations exhibit patterns similar to linkage disequilibrium. For instance, when a heritable trait enhances the environmental fitness of a species, it may be preserved and indirectly restrict the genetic diversity typically formed by population genetic recombination, leading to genetic features similar to linkage disequilibrium77, as observed for the phenotypic diversity of Uta stansburiana78.

Inter- and intra-specific genetic diversity among Taiwanese salamanders

We analyzed 140 Taiwanese Hynobius specimens of 5 species from 84 sampling sites and used DAPC, NJ phylogenetics, and STRUCTURE analyses to determine if the set of 20 EST-SSRs could be deployed to determine interspecific genetic structure. Our results show that indeed they clearly distinguish the five species, and also demonstrated that the five species exhibit distinct genetic compositions. This finding is consistent with the nuclear DNA-based phylogeny and is similar to the patterns observed with mitochondrial cytb sequences. This nuclear DNA-based phylogeny is similar to that derived from mitochondrial cytb sequences. When multiple EST-SSRs are employed in concert as a tool for genetic analysis, they can detect more detailed genetic structure and evolutionary history than cytb. In our study, we observed some discordance between the mitochondrial and nuclear phylogeny trees, particularly from contact zones between species. This discordance suggests the potential for gene flow or other processes in these regions, warranting further investigation. Using a K value of 6 in STRUCTURE, H. sonani could be divided into two clades representing Mt. Xue and the Central Mountain Range, respectively. When a K value of 7 was applied, H. fucus was also divided into two clades, representing the north and south of Mt. Xue. These results show that our set of EST-SSRs can uncover intraspecific genetic structure and also imply that latitude and Taiwan's mountainous topography may contribute to species divergence among Taiwan’s salamanders. Previous studies have shown that geographic isolation is a key factor driving species diversity and reinforcing intraspecific differentiation79–81. When species experience geographic isolation, which limits opportunities for gene flow and results in so-called “sky island” distribution patterns, genetic drift may promote genetic differentiation among populations82. The ability to mitigate linkage disequilibrium may be reduced for populations with small effective sizes, ultimately leading to divergent genetic expression in similar yet isolated habitats. Consequently, deviations from Hardy–Weinberg equilibrium and the occurrence of linkage disequilibrium may arise for the populations of a species on differing evolutionary trajectories83.

Comparative analyses across our pairwise FST, DAPC, NJ tree, and structure assignment tests revealed similar subpopulation differentiations associated with the occurrence of species on different mountain ranges. Interspecies divergence inferred from nuclear markers mirrored the findings from mitochondrial cytb sequences, with H. fucus exhibiting deep divergence from the other four species, whereas H. formosanus and H. arisanensis revealed a close genetic relationship. Furthermore, the clear differentiation among species we uncovered using our set of 20 EST-SSRs highlights their interspecies and intraspecies applicability for analyzing the population genetics of these five species.

In interpreting the genetic diversity observed in our study, it is important to acknowledge the ongoing debates surrounding the neutral theory of evolution. Recent research84, has highlighted the limitations of the neutral theory, particularly in the context of short tandem repeats (STRs), which were once assumed to be neutral but are now understood to play functional roles in gene regulation. Furthermore, new theories, such as the maximum genetic diversity theory, have been proposed to better explain the patterns of genetic diversity observed in nature. Given these developments, our conclusions regarding the genetic structure and diversity of Hynobius salamanders must be considered tentative. While our methodologies are grounded in the neutral theory, we recognize that alternative explanations and newer theoretical frameworks may offer additional insights. Future research that incorporates these emerging perspectives will be necessary to fully understand the genetic diversity of this group.

Conclusions

We have developed a set of 20 EST-SSR markers from the transcriptomes of five species of Taiwanese salamanders, which can be successfully applied to analyze the genetic structure at the species and population levels. These markers can be used in future conservation research of these five species, providing the relevant authorities with the means to examine the genetic composition of these threatened species and for the delineation of conservation units.

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71887-1.

Acknowledgements

We are thankful to those who provided samples and assistance during our field collections, including Hsiang Fang, Ssu-Tsung Wu, and Kai-Ju Wu, and a lot of friends whose names are not listed here because of space limitations. We are grateful to Chen Hsiao, Wei-Ling Hsu, and Ting-Hsuan Kuo, for their great help with laboratory work. We thank the National Center for Genome Medicine for technical support with genotyping. We also thank Dr. John O’Brien for their valuable comments on the manuscript editing. This paper was dedicated to Professor Emeritus Dr. Kuang-Yang Lue and Dr. June-Shiang Lai of NTNU, for their long-term contribution to salamander research in Taiwan.

Author contributions

J.-A. C. conceived the study. S.-W. J. and Y.-Z. L. conducted fieldwork. J.-A. C. and P.-J. Y. performed the laboratory work. J.-A. C., P.-J. Y., and P.-W. S. carried out data analysis. J.-A. C. wrote the first draft of the manuscript, and J.-A. C., W.-Y. K., C.-F. L., and Y.-T. J completed the final manuscript.

Data availability

All data needed to evaluate the conclusions in the paper are presented in the article and the supplementary information. The mitochondrial cytb sequence and microsatellite dataset are deposited in GenBank (accession nos. PQ141849–PQ141988 and PQ240580-PQ240599), and also available from the corresponding author upon reasonable request.

Competing interests

The authors declare no competing interests.

Ethical approval

The sample collection was approved by and strict followed the guidelines on experimental animals of the Institutional Animal Care and Use Committee, National Taiwan University (IACCU) with permit number: NTU109-EL-00040. The guideline for the care and use of laboratory animals is provided in the permits and conforms to the Council of Agriculture, Executive Tuan, Taiwan. This study was carried out in compliance with the ARRIVE guidelines (Animal Research: Reporting in Vivo Experiments) for how to report animal research in scientific publications.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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