Objective:

The objective of this lab was to open the Emp folder that contains fastq files and barcode files, walkthrough Qiime2 with the code for analyzing the sequencing data, collect metadata containing sample IDs and barcodes, and compare it to the Silva database of other 18S sequences.

Purpose:

The purpose of this lab was to review the skills and knowledge of Qiime2 earned through repeating the process of past labs but using our Soil eDNA instead. It was also to gather qzv files in order to visualize our data.

Procedure:

1. Redownload Miniconda and Qiime2 onto the Mac being used.
2. Download the folder
3. Change directory to downloaded file in terminal
4. Activate qiime2-2019.1.
5. Open the file found in the powerpoint listed under Modules.
6. Work through the file’s steps listed.
7. View the qzv files that were created.

-File Steps-

Importing sequences as QIIME2 artifact:

qiime tools import \

–type EMPPairedEndSequences \

–input-path emp-paired-end-sequences \

–output-path emp-paired-end-sequences.qza

Demultiplexing sequences:

qiime demux emp-paired \

–m-barcodes-file sample-metadata.tsv \

–m-barcodes-column BarcodeSequence \

–i-seqs emp-paired-end-sequences.qza \

–o-per-sample-sequences demux.qza \

qiime demux summarize \

–i-data demux.qza \

–o-visualization demux.qzv

Denoising using DADA2 and creating a feature table with Representative sequences:

qiime dada2 denoise-paired \

–i-demultiplexed-seqs demux.qza \

–p-trunc-len-f 220 \

–p-trunc-len-r 220 \

–o-table table.qza \

–o-representative-sequences rep-seqs.qza \

–o-denoising-stats denoising-stats.qza

qiime feature-table summarize \

–i-table table.qza \

–o-visualization table.qzv \

–m-sample-metadata-file sample-metadata.tsv

qiime feature-table tabulate-seqs \

–i-data rep-seqs.qza \

–o-visualization rep-seqs.qzv

qiime metadata tabulate \

–m-input-file denoising-stats.qza \

–o-visualization denoising-stats.qzv

Creating a phylogenetic tree:

qiime phylogeny align-to-tree-mafft-fasttree \

–i-sequences rep-seqs.qza \

–o-alignment aligned-rep-seqs.qza \

–o-masked-alignment masked-aligned-rep-seqs.qza \

–o-tree unrooted-tree.qza \

–o-rooted-tree rooted-tree.qza

Taxonomic classification:

qiime feature-classifier classify-sklearn –i-classifier silva-132-99-515-806-nb-classifier.qza –i-reads rep-seqs.qza –o-classification taxonomy.qza

qiime metadata tabulate \

–m-input-file taxonomy.qza \

–o-visualization taxonomy.qzv

qiime taxa barplot \

–i-table table.qza \

–i-taxonomy taxonomy.qza \

–m-metadata-file sample-metadata.tsv \

–o-visualization taxa-bar-plots.qzv

Data/Observations:

Here are the graphs found throughout the Qiime2 process fo analyzing our data. The first graph shows the Quality Plot of the forward and reserve reads. The second shows the diversity of DNA found in our soil sample and the abundance of each.

Conclusion:

In conclusion, this lab proved to be very encouraging and fruitful. We finally were able to analyze the DNA from our soil and to view the diversity of organisms and ciliates found within. For example, ryegrass was the most common DNA found; however, DNA of the Cooloola monster was also found. It also showed our retention of knowledge and skills of using Qiime2.

Storage:

No storage was needed during this lab. Computers were logged off, and our desk was cleaned in order to ensure it was left as it was found.

Future Goals:

In the future, I hope to better understand our soil and to learn else lurks within the rhizosphere of Baylor’s campus. I also plan to deliver a prresentation over the process of extracting DNA in class and at the CURES symposium.