Phylogenetic Inference

Once we had the our consensus sequences from our 2 samples that worked through the PCR, we were able to determine the best model of molecular evolution. In order to do this, we used jModelTest2 to figure the best model. I downloaded jModel2 from the site given and opened a folder with a program that uses JAVA. We then went back to Geneious and exported our alignment in Phylip format (relaxed). Afterwards, we went back to JAVA and opened the exported alignment and computed the likelihood scores. Once the scores were done, we chose the best model based on some optimality criterion.Two methods were used: the Alkaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The best model shown for AIC was 11369.78 and the bet model based on BIC was 11622.87, which are the same model.

We then looked at MrBayes analysis, and we made a tree with substitution model GTR and rate variation +G (gamma). The MCMC was set to 10,100. The subsample frequency was set to 200, and the heated chains were left at 4. The priors for this Bayesian analysis were unconstrained branch length: Exponential (10), and Shape parameter (10). The distribution shown demonstrated that our analysis was too short.

We used maximum likelihood to infer a phylogenetic tree of our aligned data set with RAxML We choose our evolutionary model as rapid bootstrap with rapid hill climbing. Once the RAxML was done, we built a consensus tree with a support threshold of 50%. The clades with high support match those from the Bayesian analysis.

We also tried a different program that uses maximum likelihood, PHYML, which we ran with bootstrapping and HKY85 as out molecular model of evolution. We used the tree window to manipulate our resulting best ML tree with bootstrap support by making the outgroup the root, showing th bootstrap proportions, and making the tree easy to read.

We used the same alignment and the HKY85 model of molecular evolution to infer the best tree using MrBayes. We ran it with 3 million generations and a subsample frequency of 500. The outgroup was chose to be a ray.When the run is done, we exported the final tree with support values, the posterior distribution, and the trace.


Mimulus guttatus last blog entry

We conducted a double digest restriction associated DNA study on mimulus guttatus.The first step was collecting sample which was done on two field trip which can be read about here. Next, we extracted DNA from the sampled we collected as well as previously collected samples from our boy, Alec. Then we double digested out DNA using two restriction enzymes, which can be read on here. These enzymes cut up the genome into many pieces. Next, we ligated unique DNA barcodes into each of our individuals (the procedure being here). Our next step was to use PCR to add a second unique barcode and to test if our library construction was successful (procedure here). Our PCR was successful as evidenced by the gels that were not photographed. After the test PCR, we did a larger reaction (25 microliters) that was identical that we did with the next step. This was the last step we did as a class.

In a perfect world we would have done the following steps. We would do size selection in which we select DNA of specific sizes and we would target 400-600 bps. Size selection can be done in 3 ways, with pippen prep (automated system) in the Suni Lab #Suni, the second way with gel extraction, or we can use magnetic beads to isolate the DNA fragments as well. After size selection, we would then normalize our DNA samples, this means to bring all of our DNA samples to approx. the same concentration (making more likely the same number of DNA fragments to be sequenced). Final step would be to combine all size selected PCR products into one vessel (or 2). Next, we would run the samples on an Ilumina sequencer (out Iseq1000/walle). Sequencing would take approximately 16 hours and if successful, would generate 10s of millions of reads. These data would be run through a bioinformatics pipeline (help Dr. Z). We would align these sequenced data with the published mimulus guttatus genome and call SNPs. Finally, we would use the SNPs to infer population differentiation using a metric like Fst and assess population genetic diversity by looking at number of alleles, allelic diversity, etc. Based on what I know about mimulus guttatus, I expect populations that are geographically divergent to be genetically divergent. #MolecularEcologyForever

DD-RADSeq PCR Test of Successful Library Construction

In this lab, we tested for a successful library construction of Mimulus guttatus samples using a test PCR. The PCR was performed with inexpensive non-high-fidelity Taq. A master mix was created with 88 microliters of NEB One -Taq 2x, master mix, 4.4 microliters of Ilumina forward primer,4.4 microliters of the Ilumina reverse primer, and 68.2 of pure water. Once the master mix was created, separate reactions were done in PCR tubes for each Mimulus guttatus plant tissue. Along with 15 microliters of the master mix, we mixed in 1 microliter of the DNA restriction/ ligation product. We then ran PCR using PCR1 on BIORAD #1/2 thermocycler. We ran the products of PCR l for each sample on a 1.5% agarose gel (0.75 g agarose in 50 mL 1x TAE) with a 100 bp ladder at 130V for 40 minutes. We were able to see a smear of fragments, showing a successful library.

The second portion of this lab had a PCR run in which we added the special ‘special barcode’ sequences and the Ilumina primers to out libraries of Mimulus guttatus, allowing us to identify which specific individuals a given sequence comes from (Ligation barcode + PCR2 barcode). To generate the final Ilumina sequencing library, we began by adding flowcell annealing sequences, mutiplexing indices, and sequencing primer annealing regions to all fragments and to increase concentrations  of sequencing libraries, we perform a PCR amplification with a kit. For each library, we set up 4-8 PCR reactions (to combine and mitigate PCR bias) in 50 microliter volume. Each PCR reaction contained ~20 nanograms (~3 microliters depending on concentration) of size-selected sample, PCR primers 1 and 2 at concentration 10 micromolar each, the recommended amount 5x-HF buffer, 10mM dNTPs, water, and DNA polymerase all in a standard 0.2mL PCR tube.


We were able to digest out Mimulus guttatus samoles with selected restriction enzyme. We also utilized a digestion buffer appropriate for both enzymes. We placed 6 microliters of each sample’s DNA in the well of a PCR tube, and stored it on ice. We prepared a master mix with 9.9 microliters of CutSmart 10x buffer, 3.08 microliters of EcoRI-HF enzyme, 1.32 microliters of MPSI enzyme, and 18.7 microliters of pure water. To account for the multiple round of pipetting in the viscous liquid, we added 130% excess mastermix to each sample’s DNA. The total reaction volume amounted to 9 microliters and then the samples were sealed, vortexed, centrifuged and incubated at 37 degrees Celsius for 8 hours on a thermocycler with a heated lid set to 50 degrees Celsius.

In order to perform this double-digest restriction associated DNA sequencing, it it necessary to address adapter ligation. We first had to thaw the working stock EcoRI and MspI adapters that were made previously. We added 1 microliter of the working stock EcoRI adapter directly to each tube of digested DNA as follows: sample BT1 had Eco_2, sample BT2 had Eco_3, sample RM1 had Eco_4, sample RM2 had Eco_5, sample GS1 had Eco_6, sample GS2 had Eco_7, sample AH1 had Eco_8, sampled AH2 had Eco_9. A master mix was prepared with 4.8 microliters of CutSmart buffer 10x, 15.6 microliters of ATP, 2.4 microliters of T4 Ligase, 1.2 microliters of pure H2O, and 12 microliters of universal P2 MspI adapter (E). 130% excess of the mastermix was added to the tubes with the digested DNA and working stock to accommodate multiple round of pipetting with the viscous nature of the glycerol of the enzymes. We added 3 microliters of the mastermix to the digested DNA.

The total reaction volume of 13 microliters were sealed, vortexed, centrifuged, and incubuted at 16 degrees Celsius for 6 hours on a thermocycler with a heated lid set to 50 degrees Celsius. The samples were then stored frozen.

PCR Reaction with Plant Tissue DNA

In order to carry out the PCR reaction, we had to firstly prepare a PCR master mix for our group table, The Turtles. In the master mix, we mixed 200.4 microliters of distilled water, 30 microliters of 10x buffer, 30 microliters of MgCl2, 15 microliters of BSA, 3 microliters of dNTP’s, 3 microliters of each primer MgSTS332 primers- including both forward and backward- and .6 microliters of Taq into a sterile tube. This master mix was put in a sterile PCR tube with the extracted plant DNA that was obtained in a previous procedure. Each PCR tube that had plant DNA and master mix was labeled with group member’s initials and the initial label that appeared on the collection tube for each plant. Once all PCR tubes were filled and labeled, the Turtles group, along with the rest of the class was able to load the tubes into the PCR machine.

DNA Gel Electrophoresis with Plant Tissue

In this week’s lab, we obtained the DNA that was extracted from plant tissue previously and were able to run a gel electrophoresis analysis. The DNA was kept on ice until the procedure began. This included the dotting of purple dye on parafilm with a micropipette, using a singular tip, and added the some DNA to each dot with the same micropipette, but changing tips every time a new dot of DNA was added. Once the DNA was combined with the dye, we were able to use a micropipette that was set to a larger quantity to account for both the dye and DNA to transfer the colored DNA to the gel. We began by filling the first well with my samples and proceeded with each other member of the group, and then the last well was filled with the ladder by Professor Paul. The gel ran on a low voltage for an extended time in order to prevent running off on the gel.

DNA Extraction from Mimulus guttatus leaves

In order to perform a DNA extraction from M. guttatus leaves, we began by labeling three 2.0 mL tubes with the sample codes GS1, GS2, GS3. In each tube, three stainless steel beads and a small amount of leaf tissue were placed and attached to the modified reciprocating saw rack to be shaken. The tubes were then spun down in the centrifuge to pull down plant dust. We then added 434 microliters of preheated grind buffer to each tube and incubated it at 65 degrees celsius for 10 minutes in a water bath. We then added 130 microliters of 3M pH 4.7 potassium acetate and inverted the tubes several times and incubated the tubes on ice for 5 minutes. The tubes were once again centrifuged for 20 minutes at maximum power.

Three new sterile 1.5 mL tubes with the sample ID that it was assigned when it was collected were labeled and filled with the supernatant. We then added 1.5 volumes of binding buffer, and 650 microliters of this mixture transferred to Epoch spin column tubes. The column tubes were centrifuged for 10 minutes and the flow through was discarded. The flow centrifuge and flow through steps were completed until the mixture had all gone through. A dry centrifuge with the spin column tubes was then done for 5 minutes. The collection tubes were discarded and and the columns were placed in labeled sterile 1.5 mL microcentrifuge tubes. 100 microliters of preheated pure sterile water to each tube and was left alone to stand for five minutes and then centrifuged for 2 minutes to elute the DNA.

Using Geneious Software to compare animal tissue DNA extractions

In this lab, we were able to download a program, Geneious, which allowed us to access the sequences produced by our DNA extractions of animal tissue from sushi. From the 4 samples of DNA, only 2, GS01 and GS02, were viable to produce sequences from both the forward and backward primers. Starting with GS01, the forward primer sequence had an HQ (High Quality) of 74.2% and the reverse primer sequence had an HQ of 25.7%.Using the DeNovo feature, we were able to combine the forward and reverse primer sequences and edit the sequence to produce a consensus sequence with an HQ of  81.9%. This number was produced only after editing sequences, which consisted of cutting off the ends of the sequence and erasing or fixing single bases. GS02 was subjected to the same DeNovo feature and editing process to produce a consensus sequence with an HQ of 78.8%.

We then were able to BLAST (Basic Local Assignment Search Tool) each of our consensus sequences, which allowed us to search a database for highly similar sequences. We were able to determine how well the sequences matched based on the Grade of the sequence. We selected 5 species to compare the consensus sequences to. Using this tool, I was able to conclude that the sample labeled GS01 was most likely Thunnus Albacares, which is a yellowfin tuna meaning the sushi market was in fact selling tuna. Sample GS02 was also analyzed using the BLAST tool and after comparing the consensus sequence it was determined to most likely be Seriola quinqueradiata, which is a yellowtail fish as advertised in the sushi market.

While the sequences were very similar, there were polymorphisms. For GS01, there were 4 polymorphisms which resulted from editing since some bases were erased due to convoluted fluorescence. There were also may bases that were not definitively determined, thus the were discrepancies in those as well. Base 511 had GS02 consensus sequence of a T nucleotide, however, there the rest of the species had a consensus in which there was no base there. There was also a similar situation at base 498. At base 121, the fluorescence was confusing and caused a polymorphism which is depicted in figure 2.


Figure 1: This is a GS01 polymorphisms in which a T nucleotide was incorrect.

Figure 2: GS01 had a consensus sequence that produced a T nucleotide, however the species consensus was a C.

When GS02 was compared to 5 other sequences, there were 22 polymorphisms. Although there were many polymorphisms, this was mostly due to including a 2 species that were not as similar to the sequence that were included in the comparison. However, when GS02 was compared to just the Seriola quinqueradiata, there were no polymorphisms. An example can be seen in Figure 3.

Figure 3: A GS02 polymorphism when comparing 5 other species.

Field Trip 9/23/19

A Mimulus guttatus by a water fountain and exposed to large amounts of sunlight

On our field trip, we traveled to Muir Beach, near Mountain Tamalpais. On this trip, we were able to see multiple populations of Mimulus guttatus in different environments. Due to the different environmental pressures, these populations demonstrated different traits that correlated to adaptive pressures.

These mimulus are not yet matured, but will most likely flower due to their environment

For example, the first mimulus plants we saw were exposed to high amounts of sunlight and had constant water supply from a fountain. This caused there to be flourishing populations that were also flowering, thus signaling a readiness of maturity and to pass on genes to next generations. The plants in this area were healthy enough and in a good position, so they flowered, and bees most likely acted as pollinators for these plants since the provide an ideal landing platform for bees and red spots on the petals that could be attracting the bees. We spoke of the likeliness that a pollinator would travel far to spread the mimulus’ pollen, and determined that the mimulus guttatus that were closer would be receiving those genes rather than further ones. This would mean that there is a high probability of inbreeding, which can be dangerous to the gene pool. We were also able to see what mimulus looks like in its primary stages of life in this area as another population began to flourish. It is also worth mentioning that the mimulus populations were usually found around horsetail and ferns.

The mimulus here comes from a flowering plants and demonstrates the ideal bee landing petals and red spots

We then traveled to a more shaded part of the terrain where a creek was found. After traveling up the creek, a population of mimulus guttatus was found, but the populations was not flowering. The reason for the lack of flowering can be explained through the location of the plants. They were located in a shaded creek area that would get flooded in a few months time and had very little pollinator traffic, thus, along with shortening of the days, the mimulus reacted to these cues by not reproducing. These populations are called sink populations and they will not be participating in breeding with any other populations.

These mimulus are not flowering because of the lack of reproductive cues

These different populations are most likely not to be very connected, but it all depends on the distance that pollinators travel and the seed dispersal that occurs. Mimulus guttatus is a very diverse plant and continues to demonstrate the adaptive capabilities it possesses.

Gel Electrophoresis and PCR Cleanup

In the second part of of the DNA extraction lab from animal tissue derived from sushi samples, our lab group ran a gel electrophoresis and PCR clean up. The first step in this process was obtaining our saved PCR tubes and letting them thaw at room temperature, and then the samples were placed on ice. In order to use our samples in gel electrophoresis, we pipetted 16 dots of dye on a sheet of parafilm. Each dot was approximately 1.5 microliters. We then pipetted 3 microliters of each PCR product into its own dot while changing pipette tips in between each dot. Each member was responsible for their own PCR products. After each dot of dye had PCR product in it, we set a pipette to  5 microliters and loaded each dot into our gel. We ran the gel at 130 volts for 30 minutes.

While our samples were running gel electrophoresis, we started our PCR cleanup. We began by carefully labeling new 0.2 microliter PCR tubes with our sample codes. I labeled my tubes with GS01, GS02, Gs03, and  GS04. We proceeded to make an ExoSap Master mix by mixing 211.8 microliters of pure water, 25 microliters of 10x buffer (Sap 10x), 88 microliters of SAP, and 4.4 microliters of Exo. We were able to do this successfully eventually, but initially, we did not use the correct amount of buffer or SAP, thus we had to redo our master mix. We mixed our successful master mix by holding the tube of master mix and waving our arm left and right on a horizontal plane, multiple times.

We pipetted 7.5 microliters of each PCR product into a clean, labeled, 0.2 microliter PCR tube. We also added 12.5 microliters of the master mix into the labeled PCR tube and then placed all PCR tubes into a thermocycler and started the EXOSAP program for approximately 45 minutes. When the program was completed, our professor placed the PCR tubes in a labeled rack and then they were placed in the freezer.

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