Analysis of colony-based PCR 16s rRNA data
Chromatogram files in standard PDF format can be viewed and fasta files trimmed in a text editor. An alternative is to have students view the chromatograms and quality data in a viewer such as SnapGene Viewer (http://www.snapgene.com/products/snapgene_viewer/). Sequences can be trimmed in SnapGene Viewer and then exported as fasta files.
Although bacterial species (or more typically genera) can be identified using a BLAST search on Genbank, more accurate identification is possible using a curated database of 16s rRNA sequences, such as Silva (https://www.arb-silva.de/aligner/). The sequences for each individual colony can be submitted separately or the fasta files for each colony can be combined into a single fasta file first. For directions on how to combine fasta files (which are text files) in Windows, see https://www.computerhope.com/issues/ch001376.htm. To combine fasta files on a Mac, navigate to the folder with the files in the Terminal. Then, type “cat *.fasta > combined.fasta”. The extension for the sequence file might be .seq, .fasta, or .fa, and you will need to change the command accordingly.
Analysis of MiSeq Data
For analysis of MiSeq data, we suggest using QIIME2. Detailed instructions on installing QIIME2 are available at https://docs.qiime2.org/2017.12/install/. For a Mac or Linux computer, you can run QIIME2 natively. For a Windows computer, you will need to install it as a virtual machine. Just follow the directions on the installation website for your computer type. After installing QIIME2, work through the tutorials on their website. Eventually, we will post some bean beetle MiSeq data to use for practice as well.