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Published in final edited form as: Genomics. 2019 Oct 17;112(2):1686–1693. doi: 10.1016/j.ygeno.2019.10.007

The first complete mitochondrial genome of the sand dollar Sinaechinocyamus mai (Echinoidea: Clypeasteroida)

Jih-Pai Lin a,*, Mong-Hsun Tsai b, Andreas Kroh c, Aaron Trautman d, Denis Jacob Machado d,e, Lo-Yu Chang a, Robert Reid d, Kuan-Ting Lin b, Omri Bronstein g,h, Shyh-Jye Lee f,i, Daniel Janies d
PMCID: PMC7032948  EMSID: EMS85194  PMID: 31629878

Abstract

Morphologic and molecular data often lead to different hypotheses of phylogenetic relationships. Such incongruence has been found in the echinoderm class Echinoidea. In particular, the phylogenetic status of the order Clypeasteroida is not well resolved. Complete mitochondrial genomes are currently available for 29 echinoid species, but no clypeasteroid had been sequenced to date. DNA extracted from a single live individual of Sinaechinocyamus mai was sequenced with 10× Genomics technology. This first complete mitochondrial genome (mitogenome) for the order Clypeasteroida is 15,756 base pairs in length. Phylogenomic analysis based on 34 ingroup taxa belonging to nine orders of the class Echinoidea show congruence between our new genetic inference and published trees based on morphologic characters, but also includes some intriguing differences that imply the need for additional investigation.

Keywords: 10X Genomics, Mitogenome, Echinodermata, Clypeasteroida, Phylogeny

1. Introduction

Extant echinoids vary in size and shape, ranging from globose to flat to disk-shaped. Echinoid morphology reflects both their mode of life and feeding strategy [1]. A unique feature for echinoids among extant echinoderms is a pentaradial jaw apparatus internal to the peristome [2,3]. Based on the fossil record, the earliest crown group echinoid is a fossil cidaroid from the Permian of Texas [4]. The divergence of cidaroids and euechinoids is estimated at 268.8 Ma [4]. Hallmarks of the split between Cidaroidea and Euchinoidea are gene network variation in how micromeres and skeletogenic cells are specified (i.e., the presence in euechinoids and absence in cidaroids of the Pmar1 gene; [5]).

Current studies suggest that evolutionary rates for major echinoid clades are heterogeneous [6]. For example, evolutionary rates for irregular urchins, which are echinoids that lack a pentaradial symmetry due to repositioning of the periproct [7], are higher than those of “regular” urchins [6]. Also, within clypeasteroid families, mean molecular divergence rates differ strongly within individual clades (e.g., in the Mellitidae [8]). The origin of the Clypeasteroida is one of the major issues in echinoid phylogeny discussed by Mooi [9] and Kroh and Smith [10]. In particular, the lantern structure of clypeasteroids is highly modified compared to other echinoids. Mooi [9] stated that “modification of the lantern into a crushing mill, extreme flattening of the test, and proliferation of food-gathering tube feet have allowed clypeasteroids to become epifaunal inhabitants of environments characterized by fine, shifting substrates, a habitat previously inaccessible to most other irregular echinoids”.

The radiation of modern clypeasteroids has been rapid and complex [3,11]. For example, workers wielding genetic techniques have uncovered hidden diversification and cryptic speciation events of echinoids [7,12–15]. Bronstein et al. [16] argued that some specific regions in the mitochondrial genome are more suitable than others as phylogenetic markers. Several studies [17–21] have used complete echinoid mitogenomes to derive phylogenies, although their results were based on limited datasets both in terms of genetic and taxonomic sampling. The current study re-evaluates phylogenetic hypotheses for the Echinoidea based on the largest mitogenome dataset to date.

Among 11 extant clypeasteroids recorded from Taiwan [22], Sinaechinocyamus mai (Wang, 1984) is one of the most studied sand dollars. Modern investigation of the living populations of S. mai began in the early 1990s. Chen and Chen [23] noted that the growth of oral plates is age-dependent but development of plates on the aboral surface is size-dependent. Chen and Chen [23] suggested neoteny (retention of juvenile features into gonadal maturity) rather than progenesis (interruption of growth by the early onset of gonadal maturity) hypothesized by Mooi [24] for the development of Sinaechinocyamus with respect to its putative sister taxon Scaphechinus.

The systematic position of S. mai is also in need of revision. For example, in a recent review of irregular echinoids, Schultz [25] suggested a reevaluation of the placement of Sinaechinocyamus among echinoids. Although miniaturized, S. mai possesses new characters that do not fit any other clypeasteroid family. Therefore, Wang [26] proposed a new superfamily, Taiwanasteritida Wang, 1984, and a new family Taiwanasteridae Wang, 1984 to place S. mai within his new classification of clypeasteroids. This new classification received much attention from echinoderm specialists. Due to the miniaturization of Sinaechinocyamus, Wang [26] thought it was related to other microechinoids, such as Fibulariella acuta (Yoshiwara, 1898) [27] but their phylogenetic relationships remained unresolved. Mooi [24] pointed out two errors in Wang's [26] study. First, Taiwanaster Wang, 1984 is a junior synonym of Sinaechinocyamus Liao, 1979 [28], and second, the superfamily Taiwanasteritida Wang, 1984, containing Fibulariidae and Taiwanasteridae, is polyphyletic. Mooi [24] and Mooi and Chen [29] concluded that Sinaechinocyamus (=Taiwanaster) is a derived scutelline sand dollar. Kroh and Smith [10] found additional phylogenetic evidence for the hypothesis that Sinaechinocyamus is a derived scutelline, and placed the family Taiwanasteridae as incertae sedis within Scutelliformes. Ziegler et al. [30] interpreted this family as a sister group to all taxa that possess Gregory's diverticulum. The goal of this study is to provide a better understanding of the phylogenetic placement of the enigmatic Sinaechinocyamus within Clypeasteroida and provide novel data for echinoid mitogenomes, which shall improve our understanding on echinoid phylogenetics.

2. Materials and methods

2.1. Data acquisition

Live specimens were observed in their native habitat in Miaoli County, Taiwan (120°39′E; 24°29′N) and a dozen live specimens were collected in July of 2017 and May of 2018 by JPL. Presented data is based on genome extraction of a single individual. Genomic DNA was extracted with the RecoverEase DNA isolation kit (Agilent Technologies) and size-selected for molecules of 40 kb or larger using a BluePippin (Sage Science) device. DNA was quantified with Life Technologies Qubit and Agilent Technologies Tapestation 4200. For library preparation 0.625 ng size-selected genomic DNA was used. The barcoded library was prepared with the Chromium gel bead and library kit (10× Genomics), and sequencing was performed with an Illumina Novaseq 6000 sequencer with 151 bp paired-end reads. All read pairs contain a 16-base barcode.

2.2. Identification of sequences

We employed three different strategies to identify and filter the sequences. Filtering sequence reads for both poor quality and adapters were performed via Trim Galore (Babraham Bioinformatics). Trim Galore removes regions of low quality, presumed contaminants, from the pool of reads. In our case, Trim Galore found no contaminated reads. Next, we used Kraken Version 1 [31] to identify foreign reads. Kraken uses user-selected genomes from the NCBI repository to build a database of k-mers that are used to identify foreign reads. We selected a custom-built database from RefSeq bacterial, archaeal, viral, and human genomic libraries as specified in the Kraken manual. Since repetitive DNA can cause false positive matches when comparing two genomes or sequences [32], repeat masking has become a crucial step in many sequence analysis applications like de novo assembly or annotation. Hence, a third strategy included use of dustMasker [33] to remove low complexity regions before assembly.

2.3. Sequence assembly

We used the software Supernova from 10× Genomics for assembly of contigs. Supernova can output multiple types of assembly formats that can be used for different downstream applications. We generated two output formats, raw and pseudohap (Table 1) with Supernova. The raw output yields contigs without any modifications. The pseudohap output attempts to generate a single record per scaffold, which can provide useful information. We used QUAST to calculate assembly statistics prior to analyzing the generated assemblies and outputs. The statistics of the assemblies generated from the different filtering strategies are presented in Table 2. To compare the raw and pseudohap output types of the 10× Genomics de novo assembly pipeline, we used the two most effective filtering strategies: Trim Galore filtering method and Dusted Kraken filtering human only (B, F in Table 2).

Table 1.

Comparison of four output methods used in this study.

Assembly variables tGalore_raw tGalore_pseudohap kraken-dust_raw kraken-dust_pseudohap
No. of contigs (>=0 bp) 5,453,916 245,534 5,506,042 246,212
No. of contigs (>=1000 bp) 806,447 245,534 806,292 246,212
No. of contigs (>=5000 bp) 46,632 40,194 45,638 40,484
No. of contigs (>=10,000 bp) 2770 17,217 2676 17,07
No. of contigs (>=25,000 bp) 4 5715 0 5638
No. of contigs (>=50,000 bp) 0 1520 0 1541
Total length (>=0 bp) 2,884,049,227 1,055,538,852 2,885,237,547 1,054,940,619
Total length (>=1000 bp) 1,895,158,569 1,055,538,852 1,887,630,099 1,054,940,619
Total length (>=5000 bp) 313,956,964 589,921,234 306,460,919 588,310,047
Total length (>=10,000 bp) 33,566,538 436,845,399 32,511,574 432,239,794
Total length (>=25,000 bp) 135,872 256,922,013 0 254,357,835
Total length (>=50,000 bp) 0 112,142,064 0 113,023,271
No. of contigs (>=500 bp) 1,349,506 245,534 1,353,382 246,212
Largest contig 40,267 800,148 24,596 653,181
Total length 2,281,563,514 1,055,538,852 2,276,793,623 1,054,940,619
GC (%) 37 37 37 37
N50 2249 6261 2231 6185
N75 1269 2897 1262 2887
L50 305,44 28,987 307,195 29,468
L75 643,203 93,93 646,159 94,629
No. of N's per 100 kbp 0 5392 0 5338
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Table 2.

Comparison of different filtering strategies for contig assembly.

A B C D E F
# contigs >=0 bp) 5,535,720 5,453,916 5,319,124 5,399,869 5,506,042 5,533,328
# contigs >=1000 bp) 808,166 806,447 787,399 793,58 806,292 807,812
# contigs >=5000 bp) 44,61 46,632 35,758 36,454 45,638 44,522
# contigs >=10,000 bp) 2586 2770 1740 1798 2676 2572
# contigs >=25,000 bp) 4 4 2 0 0 4
# contigs >=50,000 bp) 0 0 0 0 0 0
Total length >=0 bp) 2,888,834,538 2,884,049,227 2,769,697,116 2,798,260,859 2,885,237,547 2,887,086,409
Total length >=1000 bp) 1,884,446,997 1,895,158,569 1,761,011,573 1,779,110,006 1,887,630,099 1,882,965,823
Total length >=5000 bp) 299,342,674 313,956,964 235,523,667 240,764,442 306,460,919 298,743,352
Total length >=10,000 bp) 31,400,084 33,566,538 20,697,858 21,740,546 32,511,574 31,237,488
Total length >=25,000 bp) 130,108 135,872 53,664 0 0 130,108
Total length >=50,000 bp) 0 0 0 0 0 0
No. of contigs >=500 bp 1,358,943 1,349,506 1,363,143 1,370,186 1,353,382 1,358,460
Largest contig 40,051 40,267 26,832 24,377 24,596 40,051
Total length 2,276,260,880 2,281,563,514 2,170,686,674 2,189,414,574 2,276,793,623 2,274,681,176
GC (%) 36.59 36.6 36.71 36.72 36.6 36.59
N50 2217 2249 2064 2073 2231 2216
N75 1257 1269 1184 1188 1262 1256
L50 309,406 305,44 318,069 319,171 307,195 309,4
L75 650,141 643,203 665,165 667,886 646,159 650,02
# N's per 100 kbp 0.00 0.00 0.00 0.00 0.00 0.00
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A, unfiltered raw output; B, Trim Galore filtering method; C, Kraken with all filtering options; D, Kraken filtering human only; E, Dusted Kraken with all filtering options; F, Dusted Kraken filtering human only

2.4. Identification, annotation and mapping of the mitogenome

We identified contigs representing mitochondrial sequences by blasting the assembly against known echinoid mitogenomes. For the mitogenome assembly and circularization test AWA (https://gitlab.com/MachadoDJ/awa), we used k-mers between 21 and 41 [34]. Most k-mers within this range resulted in identical putative mitogenomes except that a k-mer length of 21 provided the worst assembly among all of the selected k-mer sizes. The other k-mers, when analyzed by AWA, gave longer putative mitogenomes, identical to each other, with slightly better statistics: average coverage=8.64, average contiguity index=8.51, average quality=36.42, average alignment score=−2.03. The complete mitogenome sequence was verified and checked for circularity by mapping the raw reads back to the putative mitogenome sequence with Bowtie2 [35]. We annotated contigs by combining MITOS and GeSeq automatic annotation programs. Annotations were verified by manual searching of individual translated nucleotides with the program blastX. Annotation of S. mai's mitogenome is included in Table 3. The mitogenome map was created with the software BRIG [36] (Fig. 1).

Table 3.

Annotation of the mitogenome of Sinaechinocyamus mai based on the output from MITOS Server [48] and verification by amino acid translation and comparison to other complete echinoid mitogenomes.

Name Anticodon Start Stop Strand Length Dist. next feature (nc) Start/Stop Codons
trnF GAA 1 74 + 74 −1
12S 74 966 + 893 0
trnE TTC 967 1036 + 70 18
trnT TGT 1055 1125 + 71 0
Control Region 1126 1273 + 148 0
trnP TGG 1274 1343 + 70 14
trnQ TTG 1358 1428 − 71 8
trnN GTT 1437 1508 + 72 0
trnL1 TAG 1509 1580 + 72 −1
trnA TGC 1580 1649 − 70 4
trnW TCA 1654 1722 + 69 0
trnC GCA 1723 1790 + 68 0
trnV TAC 1791 1860 − 70 22
trnM CAT 1883 1956 + 74 1
trnD GTC 1958 2026 − 69 4
trnY GTA 2031 2101 + 71 0
trnG TCC 2102 2169 + 68 1
trnL2 TAA 2171 2243 + 73 4
ND1 2248 3219 + 972 4 ATG/TAA
trnI GAT 3224 3295 + 72 0
ND2 3296 4351 + 1056 3 ATG/TAA
16S 4355 5912 + 1558 −16
COX1 5897 7450 + 1554 6 ATG/TAG
trnR TCG 7457 7524 + 68 1
ND4L 7526 7819 + 294 6 ATT/TAG
COX2 7826 8515 + 690 4 ATG/TAA
trnK CTT 8520 8589 + 70 0
ATP8 8590 8757 + 168 −10 GTG/TAA
ATP6 8748 9437 + 690 3 ATG/TAG
COX3 9441 10,223 + 783 −1 ATG/TAA
trnS2 TGA 10,223 10,292 − 70 16
ND3 10,309 10,659 + 351 19 ATG/TAA
ND4 10,679 12,067 + 1389 −10 ATG/TAG
trnH GTG 12,058 12,125 + 68 1
trnS1 GCT 12,127 12,194 + 68 0
ND5 12,195 14,108 + 1914 1 ATG/TAA
ND6 14,11 14,598 − 489 16 ATG/TAA
CYTB 14,615 1 + 1143 −1 ATG/TAG
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Fig. 1.

Fig. 1

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The complete mitogenome map of the sand dollar Sinaechinocyamus mai (Wang, 1984) generated with BRIG [36]. Coverage (gray skyline plot) shows coverage (21× at CR to 819× near 5′ end of 12S); generated by mapping the reads on the mitogenome sequence with Bowtie2 [35].

2.5. Multiple sequence alignment for phylogenetic analysis

We assembled a nucleotide dataset for the mitogenome of S. mai, and 34 additional echinoid mitogenomes representing 16 families and nine orders. The mitogenome of the holothuroid Holothuria scabra (KP257577.1) was used as outgroup. We created a multiple sequence alignment with the program Einsi which is part of the MAFFT package [37], and trimmed ragged edges of the alignment and marked missing data with “?”. ModelGenerator [38] was used to select the best-fit model of nucleotide substitution for the phylogenetic analysis. Both the Akaike information criterion (AIC) and Bayesian information criterion (BIC) in ModelGenerator indicated GTR+G+I as the best-fitting substitution model for the dataset analyzed (Fig. 3). Under this model, we used the bootstrapping algorithm plus maximum likelihood tree search (commands –f a) with 1000 replicates using RAxML V. 8.2.12 [39]. Runs with standard bootstrap and tree search (commands –f b) were also performed but the results did not change.

Fig. 3.

Fig. 3

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Phylogenetic reconstruction based on nucleotid sequences of Echinoidea (34 echinoid species; Table 4) with RAxML using 1000 replications, rooted on the outgroup Holothuria scabra. The substitution model is GTR+G+I. Bootstrap values are shown at each node. Support values for the Bayesian analyses (Bayesian posterior probabilities with 10 million generations; discarding 25% as burnin) and Maximum Likelihood analyses (bootstrap support with 1000 replications) are shown next to nodes. Major monophyletic clades indicated by solid squares: A, Euechinoidea; B, Acroechinoidea; C, Irregularia; D, Echinacea. Branch lengths were produced with ML analyses.

In separate analyses, protein coding genes (PCGs) were converted into amino acid sequences and compared with 28 additional published echinoid sequences. For the amino acid translated analyses, all 13 PCGs from each taxon (3695 AA in total) were extracted, concatenated and analyzed using with both Maximum Likelihood and Bayesian Inference approaches following the methodologies in Bronstein and Kroh [17] (Fig. 4 and Table 4). Taxa included in the phylogenetic analysis are listed in Table 4.

Fig. 4.

Fig. 4

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ML phylogenetic tree based on amino acid sequences (3695 AA) translated from the concatenated PCGs rooted on all other echinoderm classes. Support values for the Bayesian analyses (Bayesian posterior probabilities with 10 million generations) and Maximum Likelihood analyses (bootstrap support with 1000 replications) are shown next to nodes. Branch lengths were produced with ML analyses.

Table 4.

Taxa used in the phylogenetic analysis: 34 ingroup species plus Holothuria scabra (indicated with an asterisk) as the outgroup. Key taxa reported with partial mitochondrial genomic information (indicated with two asterisks) were included in the analysis.

Taxon Order, Family Base pairs GenBank accession number PCGs dataset
Arbacia lixula Arbacioida, Arbaciidae 15,719 X80396.1 NC001770
Conolampas sigsbei** Echinolampadoia, Echinolampadidae 1286 AJ639902; AJ639800
Diadema setosum Diadematoida, Diadematidae 15,708 KX385835.1 NC033522
Echinocardium cordatum Spatangoida, Loveniidae 15,767 FN562581.1 NC013881
Echinolampas crassa** Echinolampadoia, Echinolampadidae 642 DQ073744
Echinometra mathaei Camarodonta, Echinometridae 15,699 KJ680291.1 NC034767
Echinoneus cyclostomus** Echinoneoida, Echinoneidae 1191 AJ639801; AJ639903
Echinothrix diadema Diadematoida, Diadematidae 15,712 KX385836.1 NC033523
Encope micropora borealis** Clypeasteroida, Mellitidae 2544 MF616991; MF617495; MF617327
Eucidaris tribuloides Cidaroida, Cidaridae 15,89 JZLH01S0471648.1
Glyptocidaris crenularis Stomopneustoida, Glyptocidaridae 15,76 KX638403.1 NC032365
Heliocidaris crassispina Camarodonta, Echinometridae 15,702 KC479025.1 NC023774
Hemicentrotus pulcherrimus Camarodonta, Strongylocentrotidae 15,705 KC490911.1 NC023771
Heterocentrotus mammillatus Camarodonta, Echinometridae 15,729 KJ680292.1 NC034768
Holothuria scabra* Holothuriida, Holothuriidae 15,779 KP257577.1
Loxechinus albus Camarodonta, Parechinidae 15,709 KC490910.1 NC023770
Lytechinus variegatus Camarodonta, Toxopneutidae 15,693 MG676468.1 MG676468
Mesocentrotus franciscanus Camarodonta, Strongylocentrotidae 15,713 MG676467.1 MG676467
Mesocentrotus nudus Camarodonta, Strongylocentrotidae 15,709 JX263663.1 NC020771
Mespilia globulus Camarodonta, Toxopneutidae 15,719 KJ680293.1 NC034769
Nacospatangus altus Spatangoida, Maretiidae 15,763 KC990834.1 NC023255
Paracentrotus lividus Camarodonta, Parechinidae 15,696 J04815.1 NC001572
Pseudocentrotus depressus Camarodonta, Strongylocentrotidae 15,729 KC490913.1 NC023773
Salmacis bicolor rarispina Camarodonta, Temnopleuridae 15,767 KU302104.1 KU302104
Salmacis sphaeroides Camarodonta, Temnopleuridae 15,762 KU302103.1 NC033528
Sinaechinocyamus mai Clypeasteroida, Taiwanasteridae 15,756 This study This study
Sterechinus neumayeri Camarodonta, Echinidae 15,707 KJ680295.1 KJ680295
Strongylocentrotus droebachiensis Camarodonta, Strongylocentrotidae 15,717 AM900391.1 EU054306
Strongylocentrotus intermedius Camarodonta, Strongylocentrotidae 15,7 KY964300
Strongylocentrotus intermedius Camarodonta, Strongylocentrotidae 15,7 KC490912.1 KY964299
Strongylocentrotus pallidus Camarodonta, Strongylocentrotidae 15,712 AM900392.1 NC009941
Strongylocentrotus purpuratus Camarodonta, Strongylocentrotidae 15,65 X12631.1 NC001453
Temnopleurus hardwickii Camarodonta, Temnopleuridae 15,696 KP070768.1 NC026200
Temnopleurus reevesii Camarodonta, Temnopleuridae 15,71 KU302106.1 NC033530
Temnopleurus toreumaticus Camarodonta, Temnopleuridae 15,722 KU302105.1 NC033529
Tripneustes gratilla Camarodonta, Toxopneutidae 15,725 KY268294.1 KY268294
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2.6. Data deposition

The assembled mitogenome of S. mai was deposited to the NCBI GenBank and is available under accession number MN103227.

3. Results and discussion

The Trim Galore strategy (B in Table 2) generated the highest number of long contigs (≥10,000 bp) although no potential human contamination had been removed at this stage. Comparing Kraken (C, D in Table 2) with the dusted Kraken (E, F in Table 2) outputs shows that Kraken alone eliminated too many reads and generated unsatisfactory results for all of the evaluation parameters except for the size of the largest contig. Approximately 85% of the raw output contigs produced by Kraken were smaller than 1000 base pairs.

In contrast, for each filtering strategy, none of the pseudohap contigs is smaller than 1000 base pairs. Also, approximately 5% of the pseudohap contigs are>10,000 base pairs. This demonstrates that the pseudohap output can generate larger and more useful contigs. However, the pseudohap algorithm cannot be used to create an entire mitochondrial genome assembly as it did not capture all of the DNA. The overall assembly size from pseudohap was smaller, about half the length of the raw output and far less than the expected mitogenome size of S. mai.

While Kraken is good at identifying sequence fragments that belong to other organisms, an additional metagenomic analysis was performed in order to check for contamination. Thus, Bracken, which is a Bayesian re-estimation of Kraken data, was used to determine per-species abundance. We found that approximately 9% of the total DNA reads were classified by Kraken as belonging to other organisms, either viral, bacterial, archaeal, or human. In addition, Bracken also provides an output of the estimated species abundance that can be used for any number of other metagenomic analyses. In this case, the main concern is human contamination. Bracken recognized that approximately 21% of the identified contamination reads as human in origin. Other types of contamination, including sequences identified as either bacterial, archaeal, or viral, are likely due to the fact that the samples were harvested from their natural environment.

From our multiple sequence alignment of S. mai and the other echinoid taxa, we observed a very conserved organization of mitogenomes across Echinoidea. As shown here (Fig. 2), there is no significant rearrangement nor translocation among six Echinoidea taxa belonging to five orders. The gene order among orders is remarkably consistent, and the relative size for each PCG is similar (Fig. 2). Orthologous protein coding genes (CDS) (n=13), tRNA genes (n=22), and rRNA (n=2) genes are found in all echinoid mitogenomes we considered.

Fig. 2.

Fig. 2

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Comparison of mitogenomes of S. mai with Echinocardium cordatum (FN562581), Nacospatangus alta (KC990834), Arbacia lixula (X80396), Strongylocentrotus purpuratus (X12631), and Diadema setosum (KX385835), based on the software AliTV [49]. The x-axis denotes the site of the feature on the mitochondrial genome. See text for further explanation.

The Bootstrap support values are stronger when analyzing the entirety of the mitogenome nucleotide data rather than the amino acid data derived from PCGs (Fig. 4). By increasing the level of genetic information (> 16,779 aligned positions) with improved mitochondrial assembly methods, the tree based on the nucleotide alignment shown here recovers most clades that were originally discovered by morphology and allows interpretations of ingroup relationships in detail (Fig. 3). Deep nodes higher than family level, including Acroechinoidea, Echinacea, and Irregularia, receive good support values (≥80%). In particular, bootstrap support for Irregularia is 98%. Increased resolution within the Echinacea clade is likely due to higher taxon sampling. The Camarodonta are very well-supported as a clade (100% bootstrap support). Within this order, relationships among six families, Temnopleuridae, Echinidae, Parechinidae, Echinometridae, Toxopneustidae, and Strongylocentrotidae, are also well-supported. The tree based on the amino acid alignment (Fig. 4) with Bayesian analyses shows similar phylogenetic relationships with high posterior probabilities, even though fewer ingroup taxa were used.

Incongruence between molecular and morphological data is common for many extant echinoderms [40,41]. Smith [42] reviewed the long-standing issue regarding the lack of molecular support for a monophyletic Clypeasteroida. By comparing the phylogenomic analyses based on nucleotide (Fig. 3) and amino acid data (Fig. 4), deep nodes in the tree are better supported with nucleotide data. Furthermore, even though the key clypeasteroid and echinolampadoid sister taxa of S. mai (i.e., C. sigsbei, E. crassa, E. cyclostomus, and E. micropora borealis) are represented by partial genetic information in our analysis, they form a clade and provide context, in addition to already published suggestions [9,29], inter alia], for the placement of S. mai (Fig. 3). The availability of a mitogenome for S. mai sets the stage for exploring the systematic position of this enigmatic taxon once a wider range of other clypeasteroid mitochondrial genomes become available.

The clades of Echinolampadoida and Clypeasteroida both receive 100% bootstrap support. Furthermore, the clade of Echinolampadoida + Clypeasteroida is supported at 90% bootstrap. Firmly supported ingroup taxa also reflect the good support values obtained in the deeper corresponding nodes (e.g., 100% for Camarodonta, 95% for Irregularia, 75% for Echinacea, 77% for Acroechinoidea, and 70% for Euechinoidea). The latter clades were also recovered by other molecular studies [42,43]. Recent molecular studies [43,44] highlighted the disagreements between molecular trees and morphological trees in certain areas of the tree (e.g. monophyly of the clypeasteroids and acroechinoids). The cause of the mismatch between phylogenetic interpretations based on morphological and molecular data currently remains unresolved [45]. Recent phylogenomic work shed new light on this question. The analyses of Mongiardino Koch and colleagues [43] based on a transcriptomic dataset confirmed the results of Smith and coworkers [44] in placing Conolampas sigsbei (a member of the Echinolampadoida) as sister-group to Scutellina. Mongiardino Koch and colleagues [43] argued that many of the features used to support the monophyly of clypeasteroids in fact show substantial differences in expression in clypeasterines vs. scutellines. While our results indicate a good corroboration of the echinoid phylogeny based on lantern evolution as outlined in Smith [46] (Fig. 5), they cannot shed light on the question of clypeasteroid and acroechinoid monophyly since no mitogenomes for taxa crucial to investigate these questions are yet available. The main difference between our tree and that of Smith [46] (Fig. 5) is that our phylogenomic analyses agree with the hypothesis proposed in Mooi [9] that the presence of lanterns in adults was suppressed first in the Irregularia, then the lantern re-appeared in adult clypeasteroids.

Fig. 5.

Fig. 5

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Comparison of the phylogenetic trees of nine major echinoid clades based on different data. From left to right: mitochondrial genomes (this study), lantern structure (Smith [46]), corona morphology (Kroh and Smith [10]), and transcriptomic data (Mongiardino Koch et al. [43]). Note that some clades are not represented in some of the analyses.

4. Conclusions

Due to advances in genetic research, the wealth of molecular information is thought by many to be superior to morphological data, and molecular analyses became the most commonly used method for phylogenetic studies among living organisms [47]. Our molecular analysis, based on>15,000 bp for most ingroup taxa, is only in part congruent with Smith's (1981) classification based on morphological data (e.g., Fig. 5). A major difference demonstrated by the present data in comparison to previous phylogenetic trees is the position of echinoneoids (Fig. 5). Whereas morphological data (lantern evolution: Smith [46]; corona, lantern and spine structure: Kroh and Smith [10]) identify Echinoneoida as sister to a clade containing Neognathostomata (cassidulids and clypeasteroids) and Atelostomata (spatangoids and holasteroids), the genetic data presented here support a more derived position, namely a sister-group relationship between Neognathostomata and Echinoneoida. Additional data will be needed to verify if this is a function of taxon sampling or truly a new topology.

Acknowledgements

Kwen-Shen Lee and Chang-Po Chen are acknowledged for providing background information about S. mai. R. Swisher commented on an earlier draft of this work. This work is supported by Taiwan-ROC Ministry of Science and Technology grants (MOST 105-2116-M-002- 012; MOST 106-2116-M-002-018; and MOST 107-2116-M-002-007). AK's and OB's research was funded by the Austrian Science Fund (FWF): project P29508-B25. We acknowledge the support of Department of Bioinformatics and Genomics, College of Computing and Informatics, and Graduate School of the University of North Carolina at Charlotte.

Footnotes

The authors declare that there are no conflicts of interest.

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