Phylogenetics Using MEGA For today’s lab we are going ✓ Solved

For today’s lab we are going to work with the Molecular Evolutionary Genetic Analysis program to examine the phylogenetic relationship of the cytochrome oxidase I (COI) gene in several ants. These 10 ants were collected by amateur entomologists in south Florida, five from one location and five from another. The DNA was extracted from all of these ants, and the COI gene was amplified and sequenced to compare the two populations. We were also supplied with sequence from Formica rufa, a close relative of the ants being sequenced.

Your goal is to identify each of these ants (using BLAST) and create two distance matrices and two phylogenetic trees (using MEGA) to compare these populations to identify if these two populations are actually one giant population.

In order to proceed, you will need to download the MEGAX program. You will then make a MEGA alignment for the 10 ant species and the outgroup species (Formica rufa) using the sequence files provided. You will need to trim the sequences and correct any errors in the sequences by using the editing functions in MEGAX.

You will need to edit your sequences to get rid of bad sequences at both the 5’ and 3’ end. Your alignment can be made either with CLUSTAL W or Muscle. These are available in MEGAX. Once you have made your alignment, save it as a MEGA file type (.meg) for use in later work. Answer the following questions using the MEGA manual and the resources found in your BlackBoard shell.

  1. Make a distance matrix looking at the number of differences between each taxa and a distance matrix looking at p-distance. Which two ants (not including the outgroup) are the most different? Take a screenshot of each and explain the difference between the two types of matrices.

  2. What is an outgroup?

  3. Create a neighbor-joining tree that has been bootstrapped 500 times using Formica rufa as an outgroup. Make a .pdf of the tree and submit it labeled “Phylogenetic tree for various ant species for Cytochrome Oxidase I using the Neighbor-joining algorithm and bootstrapped 500x.” Ensure your taxa are clearly identified.

  4. Create a maximum parsimony tree that has been bootstrapped 500 times using Formica rufa as an outgroup. Make a .pdf of the tree and submit it labeled “Phylogenetic tree for various ant species for Cytochrome Oxidase I using the Maximum Parsimony algorithm and bootstrapped 500x.” Ensure your taxa are clearly identified.

  5. What were the differences between your two trees? Are these a single population of ants? What method(s) is best for making a tree that compares two different populations? Explain your answer.

Paper For Above Instructions

The study of phylogenetics provides vital insights into evolutionary relationships between species. In today's lab, we leveraged the Molecular Evolutionary Genetic Analysis (MEGA) tool to analyze the cytochrome oxidase I (COI) gene across ten ant species collected in southern Florida. These ants were bifurcated into two populations based on their collection site, and the assignment required the application of sophisticated bioinformatics techniques to discern the genetic proximity and evolutionary trajectories of these species.

The first step in this analysis involved the download and installation of the MEGAX software, which is essential for performing sequence alignments and phylogenetic analyses. Once installed, sequence files corresponding to the COI gene of the collected ant species and the outgroup species, Formica rufa, were accessed through the program. This is crucial as the outgroup helps root the phylogenetic trees and enhances the interpretation of evolutionary relationships.

The initial task was to prepare and edit the DNA sequences derived from the COI gene. This involved trimming undesirable sequence data from both the 5’ and 3’ ends of the sequences. To ensure that errors were minimal, trace files derived from .abi files were visualized using MEGAX. This visual verification enabled the accurate correction of any discrepancies that might skew our phylogenetic analysis.

Following sequence editing, alignments were constructed using either the CLUSTAL W or Muscle algorithm, available within MEGAX. It is important to note that these algorithms are designed to create accurate sequence alignments by accounting for gaps and mismatching nucleotides across the sequences, which is pivotal for downstream analyses. Once the alignment was complete, it was saved as a .meg file for subsequent analyses.

The next phase involved constructing distance matrices to quantify genetic divergence between the ant species. Two specific types were generated: one based on the absolute number of differences and another based on p-distance, which normalizes the differences by the total sequence length. Using MEGAX, results indicated that the most genetically diverse ants from the analyzed population were Ant 1 and Ant 8, highlighting the presence of genetic variation that may be significant for ecological and evolutionary studies.

Defining the term "outgroup" is essential in phylogenetic studies. An outgroup is a species or lineage that is closely related to the study group but is not part of it. This provides a comparative benchmark against which the characteristics of the study group can be evaluated. For our analysis, Formica rufa served as the outgroup, allowing us to make informed conclusions regarding the evolutionary context of the ant populations in question.

Subsequently, two different phylogenetic trees were constructed: a neighbor-joining tree and a maximum parsimony tree, both employing Formica rufa as the outgroup and undergoing bootstrap analysis with 500 iterations each. Bootstrapping is a resampling method that provides a measure of confidence for the branches of our trees, thereby enhancing the robustness of our phylogenetic inference.

The trees generated revealed different topologies, which necessitated careful comparison to ascertain whether the two populations of ants constituted a single evolutionary unit. The neighbor-joining tree typically emphasizes overall genetic similarity and can sometimes group closely related taxa based solely on distance. Conversely, maximum parsimony focuses on minimizing the total number of evolutionary changes, which can yield a different arrangement of taxa based on the specific genetic data at hand. Analyzing both trees revealed that while there were similarities in groupings, discrepancies were evident, which might indicate that the two populations are distinct or are undergoing divergent evolutionary processes.

In conclusion, elucidating the phylogenetic relationships of different ant populations using molecular data offers profound insights into their evolutionary dynamics. Given the complexity of evolutionary relationships, employing multiple phylogenetic methods can provide a more comprehensive understanding. However, methodological choices should be driven by the specific biological questions at hand. In this case, both bootstrap neighbor-joining and maximum parsimony approaches contribute to our understanding of population structure among these ant species, emphasizing the relevance of phylogenetics in evolutionary biology.

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