For the taxonomic identification, the nuclear rDNA ITS region was amplified with the primers BD1and BD2 [23], and to examine the phylogenetic interrelationships among eucotylid genera, D1–D3 region of the large subunit (LSU) of rDNA (28S rDNA) was amplified utilizing the primers LSU5 (forward) and 1500R (reverse) [9, 24] as described in our previous studies [25, 26]. To determine intraspecific differences, DNA of three specimens from each species was used separately for the amplification of each marker. All resultant positive PCR amplicons were purified using EZNA Gel Extraction Kit (OMEGA Bio-tek Inc., Doraville, GA, USA) and sent to Genewiz Company (Beijing, China) for sequencing. The obtained nucleotide sequences for each marker were assembled using DNAstar v7.1 [27] and Clustal X 1.83 [28] software. Sequence identity (%) across the ITS rDNA region among newly obtained sequences and another eucotylid, T. valida, the only presently available ITS rDNA of eucotylid in NCBI GenBank, was calculated using BioEdit 7.0.9.0 [29]. Similarly, prior to phylogenetic analysis, sequence identity across the D1–D3 region of LSU among newly sequenced and four other eucotylids, presently available in GenBank, was also determined.

To assess the phylogenetic interrelationships of our specimens within the family Eucotylidae, the newly obtained 28S rDNA sequences were aligned with available sequences of other eucotylid species, using MEGA X [30]. Renicola sp. was used as the outgroup based on the results of previous studies suggesting the close relationships of Eucotylidae and Renicolidae [8, 9]. The resulting alignment, trimmed to the length of the shortest sequence, was 910 bp long, including a few small gaps due to indels.

Phylogenetic analyses were conducted using Bayesian inference (BI) as implemented in MrBayes version 3.2.6 software [31, 32]. The GTR+G+F model was identified as the best fitting nucleotide substitution model using jmodeltest 2 software [33]. BI analysis was performed using MrBayes software as follows: two parallel Markov chain Monte Carlo (MCMC) chains were run for 10,000,000 generations. The initial 25% of sampled data generated was treated as “burn-in”, and the final 75% of trees was used for calculating Bayesian posterior probabilities (BPP). The phylograms were visualized in FigTree version 1.4 software [34] and annotated in Adobe Illustrator®.

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