We conducted a double digest restriction associated DNA study on Mimulus guttatus
The first step was collecting samples which we did on two field trips which are described in these entries.
Next, we extracted DNA from the samples we collected as well as previously collected samples (by Alec J).
- Gel electrophoresis : https://usfblogs.usfca.edu/orieney/2019/11/03/october-29-gel-e…oresis-m-gutatus/
- PCR : https://usfblogs.usfca.edu/orieney/2019/11/12/november-5-pcr-r…-mimulus-gutatus/
Next, we double digested our DNA using two restriction enzymes. These enzymes cut up the genome into many pieces and we ligated unique DNA barcodes onto each of our individuals.
The next step was to use PCR to (1) add a second unique barcode [table based] and to (2) test if our library construction was successful.
Our PCR was successful (picture documented by Prof. Paul). We threw this away
After the test PCR, we did a larger reaction (25 mL) that was identical and used for the following steps.
- This was the last step we were able to do together as a class. In a perfect world we would do the following other steps (Prof. Paul will do these over break)
- Size selection – select DNA of specific sizes, specifically, we would target approximately 400-600 base pair fragments [good size for Illumina]. Size selection can be done in 3 different ways using an automated system called Pippen Prep of which we have in the Suni J …… #Suni
- A second way is to use gel extraction (probably will use this method). Use a ladder to cut out base pairs
- Third way- magnetic beads to isolate DNA fragments
- After size selection, we would then normalize our DNA samples- bring all our DNA samples to approximately the same concentration. Having equal concentrations àincreased likelihood of equal number of DNA fragments to be ultimately sequenced from individuals
- Final step is to combine all of the size selected, normalized, PCR products into one vessel
- Then, we would run these samples on any Illumina sequencer. For our class, we would run it in our in-house Wall-E [iSeq 1000]
- Sequencing would take approximately 16 hours. If successful, it would generate tens of millions reads. These data would be run through a bioinformatics pipeline
- Ultimately, we would align these sequence data with the published Mimulus gutatus genome and call SNPs.
- Finally, we would use these SNPs to infer population differentiation using a metric like Fst and assess population genetic diversity looking at things like the number of alleles, allelic diversity, etc.
Based on what I know about Mimulus gutatus, I might expect populations that are genetically divergent
This week we ran two PCR reactions. One was a test to see if it would work and the other was the final one for our DNA samples we have been working with.
I. PCR I (performed with inexpensive non-high-fidelity Taq)
|NEB One- Taq 2x Master Mix
|Forward Primer (10mM) 1-X
|Reverse Primer (10mM) 2-6
|Master Mix Total
PCR was run using PCR1 on BIORAD #1/2
- 94 degrees Celsius (30 sec)
- 60 degrees Celsius (30 sec)
- 68 degrees Celsius (45 sec)
Then it was put on a 4-10 degree Celsius infinite hold. The products were run on a 1.5% agarose gel with a 100 bp ladder at 130V for 40 minutes
[Successful amplification results in a. smear of fragments typically ranging from 50-700 base pairs] Ours was successful and was documented by Prof. Paul
Since the test was successful, we moved on to the final PCR reaction
II. Final PCR
Next we ran the final PCR. We made a different master mix for this part.
|Phusion DNA Polymerase
|5X Phusion HF buffer
||68.75 microliters à 69
|Forward Primer (10mM)
||17.16 microliters à 17.2
|Reverse Primer (10mM)
||17.16 microliters à 17.2
||10.34 microliters à 10.3
||118.25 microliters à 118
|Master Mix Total
NOTE: We were assigned the PCR 2_1 for our master mix (assigned by Paul). For some reason we ran out of master mix when we were putting it in the samples so I (mistakingly) suggested that we use the next table’s master mix. They gave it to us and we used it BUT they had a different reverse primer :/ [they had 2_7]. The wrong master mix was used in reaction 21 and 22.
We ran this the same way and under the same conditions as the test PCR run (written above)
In this lab, we digested and ligated our DNA samples.
I. DOUBLE DIGEST
For this part of the lab, we first double digested 100-1000 ng of high quality genomic DNA with restriction enzymes then used a digestion buffer appropriate for the two enzymes. We placed 6 microliter of each sample’s DNA in a PCR plate/tube and stored it on ice.
Then, we made a master mix for around 10-11 samples to make sure we had enough for our 8 reactions. We mixed it well and then stored it on ice.
|CutSmart Buffer 10x
|Master Mix total
Next, we added 3 microliter of master mix into each sample.
- the total reaction volume at this point was 9 microliter. We sealed the samples, vortexes them, centrifuged, and finally incubated them at 37 degrees Celsius for 8 hours on a thermocycler with a heated lid set to 50 degrees.
Our samples names and numbers from Alec (grad student who collected these samples) are shown below-
II. ADAPTER LIGATION
The next part of this lab was the adapter ligation. We thawed the working stock EcoRI and Maple adapters made previously in the Paul Lab. The P1 EcoRI adapters are as follows.
|PAUL LAB ID
Our table was assigned 17-24 as our sample ID’s so we used Eco Adapters 2-9 respectively- those are shown below as well.
We added one microliter of each respective EcoRI adapter to the digested DNA, then made the master mix. Again, we made 11 reactions worth of master mix (130%).
|CutSmart buffer 10x
|Universal P2 MspI adapter
|Master Mix Total
We added three microliters of this second master mix to the digested DNA
- The total reaction volume is now 13 microliter. Samples were sealed, vortexed, centrifuged, and incubated at 16 degrees Celsius for 6 hours on a thermocycler with a heated lid set to 50 degrees Celsius.
This week we ran the PCR reactions for our Mimulus guttatus project – materials shown below. We made enough Mastermix for 18 reactions even though we only had 12- just to make sure we had enough.
||.72 àRounded to .80 (for pipette)
We labeled our tubes as shown below:
|QS 1 MM
|QS 2 MM
|QS 3 MM
|QS 4 OY
|QS 5 OY
|QS 6 OY
We added 19 microliter of Mastermix to each of the 12 reactions, mixed them on the vortex then Prof. Paul ran the PCR reaction for us.
First part of lab: Mimulus guttatus scientific paper presentations
Second part of lab: Gel electrophoresis / Lecture
This week we ran the samples from last week (Oct 22) on gel electrophoresis. We used 300 mL of dye and 200 mL of each of our samples.
This week marked the beginning of our next main project on Mimulus gutatus plant samples. For this lab we focused on DNA extraction. Prof Paul gave us the samples we collected in the field whenever we went to Mount Tamalpais with the class + Alec along with two other samples from other sites.
- The first step was to label 3 2mL tubes with our sample codes – which are shown below.
Tube Numbers / Sample Name / Sample ID Code
Tube 1: CATB- OY / OY01
Tube 2: MONO- 008 / OY02
Tube 3: DIRA- 001 / OY03
- Next, we added three sterile 3.2 mm stainless steel beads to each tube along with a small amount of leaf tissue to each tube, wiping off the tweezers between each sample. The steel beads were used to break up the leaf samples.
- The tubes were loaded onto a tube rack in the modified reciprocating saw rack and the rack was mounted to the saw. Prof Paul reciprocated the samples for about 40 seconds on speed setting 3.
- The tubes were then spun in the centrifuge to pull the plant dust from the lids for about 20 seconds.
- Next, we added 434 microliters of preheated grind buffer that was heated in the water bath.
- After adding the buffer we put our samples into the water bath that the grinder was in (65 degrees) for ten minutes, investing them every 3 minutes (3 times in the 10 min)
- 130 microliters of 2M pH4.7 potassium acetate was then added. The tubes were inverted several times and incubated on ice for 5 minutes
- Samples were then centrifuged on max force for 20 minutes. Centrifuge was balanced
- Next, we labeled new 1.5 mL tubes with the sample codes. Supernatant was transferred to the new tubes, while avoiding transfer of any precipitant that was at the bottom.
- We then added 1.5 volumes of binding bugger. (600 microliters)
- After this we put 650 microliters of the mixture to Epoch spin column tubes and centrifuged for 10 minutes at 15,000 rpm in a centrifuge, then discarded the flow-through in a hazardous waste container (Erlenmeyer flask in our case)
- Then we did this again with the remaining volume.
- Next we washed the DNA found to the silica membrane by adding 500 mL of 7-% EtOH to the Columbus and centrifuged it at 15,000 rpm until all the liquid passed to the collection tube (8min) and discarded the flow through
- Then we did this again ^
- Following that, we centrifuged the columns at 15,000 rpm for another 5 min to remove any residual ethanol
- Collection tubes were discarded and we put the columns in sterile 1.5 mL micro centrifuge tubes which were labeled with sample codes and the date
- NOTE: I put the columns in the wrong tube (the one containing our old DNA) and put the 100 microliters of preheated pure sterile H20 in those tubes… After noticing my mistake Prof Paul said to put it in the new sterile tubes and we ran 70 microliters of the pure sterile water through that into the tubes with the date on them and let that stand for 5 min
- These new tubes were centrifuged for 2 min to elute the DNA
- The tubes that I accidentally used first were labeled with a STAR
- Kept all the tubes in case
This week is the last part of the Sushi Test barcoding project. The first step was to clean up our alignments, which I did by editing the beginnings and the ends of the sequences to make them all line up. After this was done I looked through my alignment to spot the polymorphisms. Out of the first 20 column, 9 were polymorphic.
Next, we chose a model of molecular evolutionary using a program called jModelTest2. To use this we had to go to Geneious and export our alignment in relaxed Phylip format which ensures that if sequence names are truncated and identical then the full length names would be shown followed by a single space. After this I went back to jModelTest2 and opened the exported alignment. I went to ‘Analysis > Compute likelihood scores’ and clicked ‘Compute likelihood’. this calculated likelihoods for 88 models of molecular evolution.
** It didn’t work for my computer so Prof. Paul told me to use Mikayla’s
AIC chose GTR + I + G
BIC chose GTR + I + G
After this we started with our Bayesian Inference to create our phylogenetic trees. We ran it with a substitution model- GTR (because its what jModelTest2 chose for us), and chose the outgroup to be the shark species that we incorporated in our data. Since the best model showed the +I+G, I chose invgamma for my Rate Variation. Since this was just for lab to learn about the program we only ran it for a short time
- Chain length: 1,100,000
- Subsampling frequency: 200
- Heated chains: 4
- Burn- in length: 100,000
- Heated Chain Temp: 0.2
Once it ran, I opened a parameter estimates tab. It showed a pretty empty graph which was expected since we ran the analysis for such a short time. Then I clicked on the Trace tab. This was also a bad graph, showing an upward curving line (again, expected). Lastly, I looked at the tree. I saw that it was probably missing clades. Once I ran the analysis again with a longer chain length and burn in some clades were recovered and there were new support values.
The next thing to do was look at maximum likelihood. To infer a phylogenetic tree using maximum likelihood, we installed a Plug In called RaxML which does a very fast maximum likelihood inference. We did a ‘Rapid bootstrap with rapid hill climbing’ run and made ‘RAxML bootstrapping tree’ then a ‘consensus tree using those.
Then, we used a different program using maximum likelihood called ‘PHYML’. I used HKY85 model and made my best tree with bootstrap support.
AT HOME –> I ran this again with the HKY85 model but ran it with 3 million generations with a subsample frequency of 500. Burn in was 300,000 and outgroup was the shark species.
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.
This week we drove back to Mount Tamalpais and continued to look at different variations of Mimulus gutatus. We left campus around 1pm and we met at a spot on the mountain where there were streams of fresh water coming from pipes on the side of a cliff. The weather was nice – very sunny and hot at the first location, then shady but warm at the second one (Around 85 F).
You can tell from these pictures that the most abundant areas with the plants were in the wet areas from the water coming from the pipes. Last time we went to Mount Tam Prof. Paul told us that Mimulus like to “keep their feet wet” and this was proof of that.
After we looked around at this spot we drove over to a little hiking area that leads to Muir Woods. There weren’t a lot of Mimulus plants here but we did see a couple individuals.
The picture on the right shows an individual that may not survive to the next generation because they seem like they wouldn’t be hit by water that comes from the creek so it may not have the chance to flower. When we were over here we talked a bit about sink populations and census sizes / effective population sizes – (topics we had touched on in class).
Sink populations –> death rates exceed birth rates (leads to eventual loss and maybe extinction)
Census size / effective population size –> number of individuals needed to have a quantity of interest that is the same in the idealized population as in the real population
After hiking and discussing, we went back to campus around 4:30 pm.
This week we ran our DNA samples from the Sushi Test on gel electrophoresis and ‘cleaned up’ the PCR reaction using an ExoSap master mix. To begin, I took my samples from the ice that they were previously stored in and thawed it at room temperature. While they were thawing, we (Mikayla) dotted out 19 loading dye dots on a sheet of parafilm- each dot was about one microliter. The protocol said to put 16 dots but since we had a negative control and a ladder on each row we had three more. After prepping the parafilm, each person at my lab bench pipetted three microliters of their PCR product onto each dot, and Prof Paul put in the ladders on the parafilm for us before running the gel. I then pipetted all of our samples into the gel lanes. Tips were switched on the pipet between samples every time to avoid contamination. [The lanes and sample ID’s are shown below]. Finally, we ran the gel at 130V for 30 minutes.
|LANE # (L à R)
||SAMPLE ID #
The next step was to clean up our PCR products for future sequencing. At each table two partners shared a row of 8 0.2 microliter PCR tubes (4 each). We label them with our sample codes on the top, front and back to ensure that our sample would not be lost. Next, we made the master mix. Since we had 16 samples of fish DNA we made enough master mix for 18 reactions. [Recipe is shown below]. All the reagents were put on ice and we only took them off ice when we needed to use them. We pipetted 7.5 microliters of each of our PCR products into our new PCR tubes and then pipetted 12.5 microliter of the Master Mix we made into each of our little tubes. We them put them in the thermocycler and started the EXOSAP program.
(Prof. Paul did the last step: After 45 minutes of the program, PCR tubes were placed in a labeled tube rack and placed in the freezer)
|10x buffer (Sap 10x)
|Master Mix Total