AlignmentBNEAF

Sequence alignment of 860 fish DNA barcode

GS FLX sequences generated for each aliquot.

<p>GS FLX sequences generated for each aliquot.</p

GERFWF_Alignment_1056

This alignment comprises 1056 DNA barcodes belonging to 93 species of freshwater fishes and lampreys from Germany

A) Species composition of North Sea metazoa from four aliquots of pooled, known DNA samples (ALLDNA, ZPDNA) and two aliquots of one field-collected zooplankton sample (ZPHTS), as assigned by 454 sequencing of the 18S rDNA: V1-V2 region.

<p>The tree, based on consensus sequences of the Sanger-generated reference library, was generated by the Neighbor-Joining algorithm / p-distance model. Clustering against the reference library was performed at 99% sequence similarity threshold using the program cd-hit-est-2d. Percentage of pyrosequencing reads for each species detected in each sample is shown by color-coded rectangles. Black asterisks denote species included in the artificially prepared ZPDNA sample. Red asterisks denote species not included, but detected in the ZPDNA sample. <b>B) Figure 3A continued. C) Figure 3B continued</b>.</p

Cluster analysis conducted on modified reference libraries (characterized by 5-mer, 4-mer, 3-mer and 2-mer homopolymers, respectively) using different similarity thresholds (97–100%, at 1% intervals).

<p>Cluster analysis conducted on modified reference libraries (characterized by 5-mer, 4-mer, 3-mer and 2-mer homopolymers, respectively) using different similarity thresholds (97–100%, at 1% intervals).</p

Higher taxa composition and number of different species per taxa analyzed for the Sanger-sequence reference library used in the pooled DNA samples.

<p>Higher taxa composition and number of different species per taxa analyzed for the Sanger-sequence reference library used in the pooled DNA samples.</p

Supporting_Information_Table_S1

Supporting Information Table S1. Table of all specimens used in this study, including individual codes, GenBank accession numbers (left) and haplotype numbers (right) of both mitochondrial gene fragments, collection sites with coordinates and dates, gender and status of Wolbachia infection of the analysed isopod specimens. Specimens are marked with asterisks when nuclear V7 regions were additionally analysed (accession number JQ814405)

Species delineation results for the Sanger-generated reference library at a 98% similarity threshold.

<p>For each cluster comprising more than one sequence a representative sequence* is presented.</p

Bayes_phylogram_Ligia_oceanica_CO1

Bayesian tree by MrBayes 3.2.1 (Ronquist et al., 2012) for the 61 CO1 haplotypes of Ligia oceanica. The most appropriate model was determined beforehand using the Bayesian information criterion (BIC) as implemented in jModeltest 2.1.1 (Darriba et al., 2012), indicating TPM1uf+I+G to be the optimal nucleotide substitution model with the following parameters: nucleotide frequencies A: 0.27, C: 0.19, G: 0.17, T: 0.37; substitution rates RAC: 1, RAG: 13.33, RAT: 4.63, RCG: 4.63, RCT: 13.33, RGT: 1; gamma distribution shape = 0.48; and proportion of invariable sites = 0.38. The Bayesian analysis employed 10,000,000 Markov chain Monte Carlo (MCMC) generations in two parallel runs, each with three cold chains and one hot chain. Trees were sampled every 500th generation, with the number of burn-in generations being determined using the likelihood scores over all generations in Tracer 1.5 (Rambaut & Drummond, 2007). The determination of the split frequencies in both independent runs (< 0.01) with 2 x 20,001 tree samples showed good convergence after 5,000 sampled trees (split frequency < 0.01), which was therefore set as the burn-in

High-Throughput Sequencing—The Key to Rapid Biodiversity Assessment of Marine Metazoa?

<div><p>The applications of traditional morphological and molecular methods for species identification are greatly restricted by processing speed and on a regional or greater scale are generally considered unfeasible. In this context, high-throughput sequencing, or metagenetics, has been proposed as an efficient tool to document biodiversity. Here we evaluated the effectiveness of 454 pyrosequencing in marine metazoan community analysis using the 18S rDNA: V1-V2 region. Multiplex pyrosequencing of the V1-V2 region was used to analyze two pooled samples of DNA, one comprising 118 and the other 37 morphologically identified species, and one natural sample taken directly from a North Sea zooplankton community. A DNA reference library comprising all species represented in the pooled samples was created by Sanger sequencing, and this was then used to determine the optimal similarity threshold for species delineation. The optimal threshold was found at 99% species similarity, with 85% identification success. Pyrosequencing was able to identify between fewer species: 67% and 78% of the species in the two pooled samples. Also, a large number of sequences for three species that were not included in the pooled samples were amplified by pyrosequencing, suggesting preferential amplification of some genotypes and the sensitivity of this approach to even low levels of contamination. Conversely, metagenetic analysis of the natural zooplankton sample identified many more species (particularly gelatinous zooplankton and meroplankton) than morphological analysis of a formalin-fixed sample from the same sampling site, suggesting an increased level of taxonomic resolution with pyrosequencing. The study demonstrated that, based on the V1-V2 region, 454 sequencing does not provide accurate species differentiation and reliable taxonomic classification, as it is required in most biodiversity monitoring. The analysis of artificially prepared samples indicated that species detection in pyrosequencing datasets is complicated by potential PCR-based biases and that the V1-V2 marker is poorly resolved for some taxa.</p></div