Development of a DNA Barcoding System for Seagrasses: Successful but Not Simple

Seagrasses, a unique group of submerged flowering plants, profoundly influence the physical, chemical and biological environments of coastal waters through their high primary productivity and nutrient recycling ability. They provide habitat for aquatic life, alter water flow, stabilize the ground and mitigate the impact of nutrient pollution. at the coast region. Although on a global scale seagrasses represent less than 0.1% of the angiosperm taxa, the taxonomical ambiguity in delineating seagrass species is high. Thus, the taxonomy of several genera is unsolved. While seagrasses are capable of performing both, sexual and asexual reproduction, vegetative reproduction is common and sexual progenies are always short lived and epimeral in nature. This makes species differentiation often difficult, especially for non-taxonomists since the flower as a distinct morphological trait is missing. Our goal is to develop a DNA barcoding system assisting also non-taxonomists to identify regional seagrass species. The results will be corroborated by publicly available sequence data. The main focus is on the 14 described seagrass species of India, supplemented with seagrasses from temperate regions. According to the recommendations of the Consortium for the Barcoding of Life (CBOL) rbcL and matK were used in this study. After optimization of the DNA extraction method from preserved seagrass material, the respective sequences were amplified from all species analyzed. Tree- and character-based approaches demonstrate that the rbcL sequence fragment is capable of resolving up to family and genus level. Only matK sequences were reliable in resolving species and partially the ecotype level. Additionally, a plastidic gene spacer was included in the analysis to confirm the identification level. Although the analysis of these three loci solved several nodes, a few complexes remained unsolved, even when constructing a combined tree for all three loci. Our approaches contribute to the understanding of the morphological plasticity of seagrasses versus genetic differentiation

Observed frequency of uncorrected intra- and intergeneric <i>p</i>-distance.

<p>The frequency of the uncorrected <i>p</i>-distance was analyzed to visualize the “barcoding gap”. Frequency was logged on a scale from 0 to 20% distance, indicating that <i>trnH-psbA</i> is out performing with an average inter-specific <i>p</i>-distance of more than 20%. Inter-generic <i>p-</i>distance shown in darker color and intra-generic <i>p</i>-distance lighter color, blue for <i>trnH-psbA</i> spacer, violet for <i>matK</i> and green for <i>rbcL</i>, respectively.</p

Meta tree of all taxa using <i>matK/rbcL</i>.

<p>Combined tree of <i>matK/rbcL</i> loci, branch support values are given in percent. Support values highlighted by the method used: Maximum Likelihood (black), Maximum Parsimony (violet), Neighbor Joining (green) and Bayesian Analysis (turquoise). Taxa that differed in topology along the different methods are shaded in violet.</p

Average branch support analysis across different loci and phylogenetic methods.

<p>Data of single- and combined-loci was analyzed using Bayesian analysis (Bayes), Maximum Likelihood (ML), Neighbor Joining (NJ) and Maximum Parsimony (MP). The average branch support was calculated for well resolved clades (above 50%), resulting from all methods used. Error bars indicate standard error of support values. The average support varied significantly using different methods for single locus analysis, but decreased with the combination of loci.</p

Higher content of parsimony informative characters (PIC) is not related to high species resolution.

<p>The percentage of PIC was plotted across the average species resolution calculated over all methods used for single or combined datasets. Error bars show standard error of species resolution among different methods used. <i>trnH-psbA</i> spacer performed poorly compared to <i>matK</i> and <i>rbcL</i> in single locus analysis, while <i>rbcL/matK</i> nearly reach the same resolution percentage as the three-loci combination.</p