A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Seeking to speed up species discovery in the MEGA diverse tropics, this protocol aims to generate species clustering hypothesis in aquatic and riparian beetles using a concoction of computer-based analysis.

This concoction pipeline, which utilized COI DNA sequence, has led to greater evidence for a species delimitation for rafted beetle from the genus Anisostena, which is previously erected only using morphological data.

This protocol seeks to address the taxonomic impediment that species discovery through morphology-based taxonomy, which is considered the gold standard in insect systematics is often time-consuming and confusing for understudied, yet MEGA diverse and highly inconspicuous aquatic beetles.

[Emmanuel] This pipeline generates molecular accessory hypotheses called MOTUs, regardless of whether the sequence has correspond the known species per referenced sequences, or whether the species are undiscovered or undescribed.

With this, rather than dissecting and comparing hundreds of beetle genital structures all at once, the pipeline provides preliminary clustering on which specimens can be scrutinized for conspecificity.

[Narrator] To begin, launch MEGA X and load the DNA sequences for alignment. Open the alignment interface by selecting a line, then clicking on edit or build alignment, and choosing create a new alignment. Click okay to confirm the selection and select DNA as the data type. Hover the mouse over the edit tab. Click on insert sequence from file. Navigate to the appropriate directory and select the sequence files to load into MEGA. Now, click on alignment, then select align by ClustalW to align the sequences using default settings and click okay to proceed. For manual editing of the sequences, delete any insertions by clicking on the inserted bases or positions and pressing the delete key on the keyboard. Next, correct deletions by clicking on the dash that represents a missing base, removing it, and typing the intended base. Then, find the earliest position where all sequences contain a character. Click on the blank box in the row header immediately to the left of this position and drag to select all excess starting positions. Press delete to trim them. Then, find the last aligned position and click on the box to the right of this point. Press delete again to trim the end. Now, select all sequences and click on the translated protein sequences tab. When prompted, verify the genetic code as invertebrate mitochondrial. If the genetic code is different, click no and a menu will appear, allowing one to tick the box for invertebrate mitochondrial genetic code. If stop codons marked by asterisk in the alignment appear across an entire column, click on DNA sequences and delete the first position for all sequences. Again, click on DNA sequences, then save the alignment in .mos or .mosx format. To start the delimitation using the TaxonDNA module, open the TaxonDNA software. Click on import, then select FASTA and upload the alignment file in FASTA format. Now, click on modules, then select cluster. Set the threshold value to 3% and check the box labeled generate individual information on every cluster. Click on make clusters now to start clustering and save the results by taking a screenshot. For delimitation using the Kimura 2-Parameter method, open MEGA and click on file, then select open a file or session. Click on distance. Select compute pairwise distances and confirm the .meg file for delimitation. Hover over the box next to model or method and click the arrow to expand the dropdown menu. Select the Kimura 2-Parameter model and click okay to run the program. Open the data output window to view the results. Click on file, then select export and print distances to save the result. Open the assemble species by automatic partitioning or ASAP web server. Click on the orange box labeled choose a file and upload the .fasta file. Scroll down and click go. To download the clustering result, click on list for the row with the lowest ASAP score and the highest P-value rank. Next, to start the tree estimation, open MEGA and click on data. Then select open a file or session to load the .meg file. Click on models, then select find best DNA and protein models or ml to determine the best fit substitution model. Click okay on the analysis preferences menu. Now, to generate the tree, click on phylogeny, then select construct and test maximum likelihood tree. Use the best fit substitution model by clicking on the box beside model or method and selecting the appropriate model from the dropdown menu. Under phylogeny test, click on the box beside test of phylogeny, then choose bootstrap method from the dropdown menu. Click on the box beside number of bootstrap replications. Type 1,000 and click okay to run the analysis. Once the window containing the resulting tree opens, save the session as a .mts or .mtsx file. Also save the output as a .newick file and export the tree as a .png image. For the PTP-based delimitation, visit the PTP web server. Click on choose file and upload the tree in Newick format. Under my tree is select rooted. In the box under outgroup taxa names, input the outgroup by typing the name of the Taxon tip. Next, under maximum likelihood solution, click on download delimitation results to save the PTP ML output. Similarly, under highest bayesian supported solution, click on download delimitation results to save the PTP BI output. For the MPTP-based limitation by MPTP, visit the MPTP web server. Upload the Newick file by dragging it onto the gray square or by clicking on the square. Once the data is loaded, click on proceed to outgroup selection. On the outgroup specification page, select the outgroup by clicking the checkbox next to the taxa labels of outgroup specimens. Then, click on model selection, select MPTP, and click on visualization options. On the visualization options page, accept the default settings. Click on submit. Right click the files under downloadable files and choose save as to save the results. Now to generate the molecular operational taxonomic units or MOTU, open the tree using a photo editing program or PowerPoint. Create a bar to represent the results of each molecular species delimitation approach. If all the approaches yield identical results for a given molecular cluster, designate the cluster as a MOTU by consensus. This figure presents the maximum likelihood gene tree and molecular clustering results for boranus beetles based on COI 3-prime sequences and six delimitation methods. All methods consistently identified four MOTUS, Byrrhinus negrosensis, Byrrhinus villarini Byrrhinus A, and Byrrhinus B with identical clustering across methods. Byrrhinus negrosensis and Byrrhinus villarini were clearly separated, despite originating from the same locations. Sequences from four provinces were grouped into Byrrhinus A, showing no strong geographic structuring. This figure shows clustering of Anisostena beetles into four MOTUS, including Anisostena angatbuhay, Anisostena auxilium, Anisostena A, and Anisostena B with full agreement across methods. Anisostena auxilium overlapped geographically with Anisostena A and Anisostena B, indicating that geography alone did not explain molecular divergence.