October 1 – Introduction to Genieous


This week we went through an introduction of Genieous – a commercial program that performs many functions on DNA and protein sequences. We downloaded the program and made an account [free 2 week trial] and started learning how to use the program.

Two of my reverse reactions from the Sushi Test worked but none of the forward ones did so Prof. Paul assigned extra reactions that I could work with instead to learn about the program. I first downloaded all the fish barcode sequences we would need – “Fish_Barcode_Forward.geneious,” “Fish_Barcode_Reverse.geneious,” “Fish_Barcode_Forward_EXTRA.geneious,” and “Fish_Barcode_Reverse_EXTRA.geneious.” I drag and dropped these files into my Fish Barcode folder that I titled “fish barcodes – yu.”

I already knew my forward reactions did not work so the next step was to look at the two (out of four) reverse reactions to see how well they worked. I looked at the various automatically generated column in the reverse reads folder and saw that the HQ% score was only 9.3% for OY-02 and 2.4% for OY-04. Prof. Paul wrote in the handout that HQ scores of 80% or higher are excellent and 10% may still be usable so I tried to look at them but they were mostly unreadable (oops). The peaks ere unevenly spaced and not very even in height like a good read would be.

The sequences from my two reverse runs were not that short but they were pretty messy and uneven so I decided to continue in the tutorial with the extras titled “KJ03_FbcF_H06” for the forward reaction and “KJ03_FbfR_E11” for the reverse reaction. The forward had an HQ% of 92.9% and the reverse was 96.3%.

After looking at some of the features in the Geneious program, the next setp was to actually assemble forward and reverse sequence reads of the same sample so I highlighted the two KJ03 reads (F and R) and selected ‘De novo assembly.’ This created a new file which held the actual assembly. This showed a consensus sequence, sequence traces for each reads (one of which was the reverse compliment of the original sequence. The next thing I did was edit the two strands (like post transcriptional modification?). I did this by deleting any regions of ‘junk,’ making sure to highlight both the strands and the consensus sequence to avoid any frameshift mutations in the sequence. I also deleted any ambiguities along the sequence (N,Y,etc). If I was able to choose the base based off the complimentary strand I did but most of the time it just showed a dash. Finally, I used the Basic Local Alignment Search Tool (BLAST) to see which organisms had the highest matching sequence to mine.

I found that Thunnus alalunga was the most similar to my sequence and Googled it to find the common name – Albacore.

To find polymorphisms, I went back to the BLAST search results and selected 5 different species and made a nucleotide alignment. There were 7 polymorphisms.





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