Henricia perforata (O. F. Muller, 1776)

Knott, K Emily, Ringvold, Halldis & Blicher, Martin E, 2018, Morphological and molecular analysis of Henricia Gray, 1840 (Asteroidea: Echinodermata) from the Northern Atlantic Ocean, Zoological Journal of the Linnean Society 182 (4), pp. 791-807 : 792-793

‘ perforata group’

Dorsal spines with conspicuous distal thorns, thin integument, Dorsal spines stout and blunt, conspicuous thick integuadambulacral spines on outer part of plate in two to four rows ment, adambulacral spines on outer part of plate in one to two rows

Henricia hedingi Henricia perforata

Dense coverage of spines on dorsal pseudopaxillae Dorsal skeleton open reticulum of thin plates

Dorsal pseudopaxillae crescent-shaped Dorsal spines single or few, in one to two irregular rows Dorsal spines with short distal thorns Spines large with blunt, rough, distal end

Henricia lisa ingolfi Henricia eschrichti

Few spines (<10) on dorsal pseudopaxillae Dorsal spines usually cylindrical closely set in irregu- Dorsal spines with three to five unequally long distal thorns lar double row

Adambulacral spines in irregular double row Ventral skeleton not in distinct rows

Henricia sanguinolenta Henricia oculata

Sparse coverage of spines (10–15) on dorsal Dorsal plates crowded with up to 25 spines in multiple pseudopaxillae rows

Dorsal spines with three to seven short distal thorns Dorsal spines short and cylindrical

Adambulacral spines in irregular double row Ventral skeleton in distinct transverse and longitudinal rows

Henricia spongiosa

Dense coverage of spines (30–40) on dorsal pseudopaxillae

Dorsal pseudopaxillae oval or circular

Adambulacral spines in irregular triple row

Henricia pertusa

Sparse coverage of spines (10–15) on dorsal pseudopaxillae

Dorsal spines with three to five unequally long distal thorns

Adambulacral spines in three to four irregular rows

Henricia cylindrella

Few spines (<10) on dorsal pseudopaxillae

Dorsal spines with a single long distal thorn

Two furrow spines within each group overlap to some degree, and species identification based on morphology is still difficult, not only for those unfamiliar with the morphology of asteroid echinoderms, but also for specialists. Among the taxa revised by Madsen (1987), H. eschrichti , H. hedingi , H. lisa ingolfi and H. spongiosa are omitted from the later work by Clark & Downey (1992), who only focused on fauna collected as far north as Belle Isle, Canada in the west and Trondheim, Norway in the east. Moreover, Clark & Downey (1992) only mentioned H. perforata in their identification key. One reason for the omission of these taxa is that the two works were completed roughly simultaneously (despite the difference in publication date; see Clark & Downey, 1992). Consequently, Madsen (1987) is the most recent authority on species of Henricia in the north Atlantic.

An alternative approach used to simplify species diagnosis has been to use molecular data instead of, or in addition to, morphological characters. DNA barcoding with an appropriate species-specific genetic marker ( Hebert et al., 2003; Pečnikar & Boznan, 2014) has become a commonplace alternative to morphological species identification when correct species designation is difficult given variable or few, easily assessed diagnostic morphological characteristics. Typically for Metazoa, the gene coding for cytochrome c oxidase subunit I (COI) has been used as a species-specific marker, and, previously, COI has been shown to be effective in delineating echinoderm species ( Ward, Holmes & O’Hara, 2008). Even though it has been challenging to design primers that amplify COI consistently in asteroids, especially Henricia (KEK, personal observations; Hoareau & Boissin, 2010; Zulliger & Lessios, 2010), the DNA barcoding approach has been used successfully to assess species identification and phylogenetic relationships in some asteroid genera ( Linckia : Williams, 2000; Astropecten : Zulliger & Lessios, 2010; Luidia : Xiao et al., 2013; Echinaster : Lopes et al., 2016). Alongside the use of COI for DNA barcoding, some studies have also employed sequences of the 16S ribosomal subunit as species-specific markers ( Naughton & O’Hara, 2009; Mah & Foltz, 2011; Janosik & Halanych, 2013; Lopes et al., 2016). Molecular data (allele frequencies at the glucose-6-phosphate isomerase locus) have previously been shown to support the distinction of the ‘ pertusa group’ and the ‘ perforata group’ ( Ringvold & Stien, 2001), but the use of DNA barcoding for identification of Henricia species in the North Atlantic Ocean has not been explored.

The difficulty of identifying species in Henricia using only morphological characteristics also creates difficulty when attempting to use a DNA barcoding approach. This is because DNA barcoding requires a reference database of barcode sequences from known species for comparison and identification of unknowns ( Hebert et al., 2003; Hajibabaei et al., 2007). When known species cannot be identified with certainty, it is difficult to develop a reference database. Moreover, when there is no reference database from known species, the DNA sequence chosen as a barcode cannot be evaluated for its specificity and utility in species identification. Indeed, errors in public databases, including species misidentification, are not uncommon for DNA barcoding data sets and create problems for researchers hoping to use this method ( Bucklin, Steinke & Blanco-Bercial, 2011).

In this study, we evaluated whether (1) traditional classification was possible for Henricia collected from the North Atlantic Ocean, following Madsen’s (1987) key and morphological diagnostics; (2) our classifications based on morphology could be supported by phylogenetic analysis of DNA sequence data from COI and 16S genes and (3) clades identified in the molecular analysis were also supported by a re-evaluation of morphological features.

Our approach is cautious, but realistic, considering that both morphological and molecular data could be subject to misinterpretation. Importantly, following this approach allows us to evaluate how well the different data sets can be used to distinguish species and allows us to identify those cases for which additional study is needed.