What is the difference between a phylogeny and a phylogenetic tree? What is a monophyletic group? What is considered a character when reconstructing a phylogeny using DNA? What is the goal

biology multi-part question and need the explanation and answer to help me learn.

mines was the pink salmon code B2057 everything attached below
Requirements: N/a
Catching Cheaters
Part 4: Sequencing & Phylogenetic Analysis
Lab Goals
Understand the principles of molecular phylogenetic analysis.
Use phylogenetic analysis software to generate a phylogenetic tree from DNA sequences.
Analyze salmon phylogeny and identify salmon samples from the phylogenetic tree.
Outline
Review of phylogenetic (cladistics) reasoning.
Introduction to molecular characters and sequence alignment.
Use of computer programs for sequence alignment and phylogenetic reconstruction.
Generation of a molecular phylogeny for salmon based on reference samples.
Determination of class sample species based on phylogenetic positioning.
Lab Preparation & Study Questions
NOTE: You may use your own laptop if you wish, but please note that you will need to install the MEGA software onto your laptop. You can get it from megasoftware.net.
What is the difference between a phylogeny and a phylogenetic tree?
What is a monophyletic group?
What is considered a character when reconstructing a phylogeny using DNA?
What is the goal of boot-strapping?
What would be the most likely tree shape and branching pattern if you put Oncorhynchus nerka, Oncorhynchus keta, Salmo salar, and Thymallus arcticus on a phylogenetic tree? (Draw this out for practice!)
Introduction
In TBIOL120 (Bio 1) you learned about phylogenetic trees: how to read and interpret them, and how the evolutionary history of a group of organisms can be reconstructed. In lab this week, we will be analyzing your COI salmon sequences that we received from the sequencing facility, build a phylogenetic tree, and identify the species of your salmon sample maybe even catch some cheaters among the stores or restaurants where you bought your salmon!
Phylogeny and Classification
Systematics is the study of evolutionary relationships and has strong ties with the practice of taxonomy: the description, naming, and classification of organisms. A taxon (plural taxa) is a named group of organisms at any hierarchical level (e.g. species, genus, family, etc.). A phylogeny represents the evolutionary history of a group, while a phylogenetic tree is just a graphical representation of the relationships between the members, or taxa, within the group. As discussed in TBIOL120, each node represents the common ancestor of the taxa on that branch. Taxa that are all on the same branch share a common ancestor and are referred to as a monophyletic group (Greek meaning one race?). A monophyletic group consists of the common ancestor, all its descendants, and ONLY those descendants (see your textbook).
You can interpret a tree as moving back through time from the end-points (the present) to the root (the common ancestor of all the taxa in the tree). It is important to realize that a phylogenetic tree is a hypothesis about how the taxa are related to each other. Based on their current characteristics, we try to infer the evolutionary history of the group.
Phylogeny Reconstruction from Molecular Characters
Phylogenetic trees can be assembled using morphological characteristics, but phylogenetic trees are increasingly reconstructed by comparing DNA sequences among the organisms of interest. DNA sequence has the advantage of providing lots of characters for comparison: the number of characters in the data matrix can potentially be as large as the number of base pairs in the genome. It is only within the last ~30 years that this data source has become widely accessible, but in this short time it has contributed to great advances in our understanding of how various groups of organisms are related.
To use DNA sequences in a phylogenetic analysis, we must first line them up side by side for comparison. The alignment process uses an algorithm that compares and tests different arrangements of short stretches of each sequence until it maximizes the similarity of sequences to each other. Recall that one of the common types of mutations is a deletion or insertion: as a result, the algorithm may need to insert gaps into some of the sequences to make them all line up.
Once the alignment has been generated, each position (i.e., base) within the sequence can be interpreted as a distinct data point or character. In the figure above, two of the taxa share a C? at base 3, but the other two taxa have an A?. In our sequence, we have 648 bases to compare, providing lots of characters to use to generate our phylogenetic tree. The distance between each of the sequences can be calculated based on how many characters are shared between each pair of sequences. These values can be examined in a distance matrix, where each sequence is listed on both the X and the Y axes of the matrix, and the distance between each pair is listed in the corresponding position of the matrix.
One problem that must be considered is that the sequence is uninformative in regions where all the taxa have identical sequences. It is important to choose a gene that has enough variability to provide sufficient characters to distinguish between the taxa but is conserved enough to make it possible to align the sequences together.
Because a phylogenetic tree is a hypothesis, it is important to be able to evaluate the degree of reliability of the hypothesis. One method that is widely used is called boot-strapping?. The colorful name is derived from the idea of pulling yourself up using your own boot-straps (i.e. shoelaces). We need a way to assess how likely it is that a data set would be interpreted in the same way multiple times; in other words, is the current interpretation reliable? If we ran the analysis on similar data sets a hundred times, how many times would we generate the same tree? Boot-strapping is a method that tests the reliability of the tree by running the analysis multiple times with a random subset of the data. The boot-strap test evaluates the reliability of each grouping on the tree. Each branch point can then be labeled with a value reflecting the probability that that branching pattern is reliable.
Laboratory Protocol
You will be using the phylogenetic tree software program MEGA to analyze your sequences and reconstruct a phylogenetic tree from the class salmon sequences.
I. Installing MEGA – (Skip this section if you are using a UWT laptop.)
Download the program MEGA from the following link:
Run the installer.
II. Viewing your Salmon Sample COI Sequence Data
Download the .ab1 files with your sample IDs. Look at the for a reminder.
Open MEGA.
Go to the Align? menu and select Edit/View Sequencer Files (Trace)?.
Open one of your .ab1 files.
Use the tab at the bottom for a sequence trace (chromatogram). Your instructor will show you an example of what this looks like. Do this for ALL the salmon sample IDs in your group.
*** STOP HERE AND LOOK AT WHAT YOUVE DONE BEFORE MOVING ON. ***
Take a good look at your chromatograms. Your chromatogram may be beautiful, or it may be a complete mess depending on how the sequencing reaction went. If it was beautiful with nice distinct peaks (i.e. useful data) then that sequence will be a part of the analyses in the next steps. If not, then it has been excluded.
NOTE: The quality of the data at the beginning of the sequencing reaction varies between samples. Even though the same primers are used for every sequencing reaction, the sequence wont necessarily start at the same place.
III. Comparing your Sequence to the Database of Known Sequences (BLAST)
Download and open the class sequence data file (use the .txt file).
This file contains all of the high-quality sequences from the class as well as standard sequences for each of the salmon species. If your sequencing reaction didnt work well, it was excluded.
Find *your* sequence, or pick any other one if yours didnt work.
Highlight and copy that sequence using Ctrl-C.
Go to and click on the Nucleotide BLAST? tile (greenish, on the left).
Paste (Ctrl-V) your sequence into the white search box at the top.
Ignore all the other menu options and click on the blue BLAST? button at the bottom left of the page.
Look at the results page. Which species is listed at the top? What species was your sample labeled as? Do they match? Click on the top hit and look at the alignment. What else do you see here that you have questions about? Ask your instructor.
IV. Creating a Sequence Alignment from ALL the Class Data
Download the sequence file for our class from Canvas (this time, use the .fasta file).
From the File? menu -> Open a file/session?
Select the sequence file for our class (this one will end in .fasta?).
Choose Align? from the popup window; the Alignment Explorer? window will open.
Edit? menu -> Select All?
Alignment? menu -> Align by ClustalW?
A Parameters? window will open? just click OK?
*** STOP HERE AND LOOK AT WHAT YOUVE DONE BEFORE MOVING ON. ***
This step aligns your sequences so that matching areas can be compared directly. Scan rightward along the sequences by clicking on the tab at the bottom. Are the sequences lined up? Are the sequences identical? or do they have a few differences?
Data? menu -> ?Export alignment? -> ?MEGA Format?
Save the file in your H:Drive or on your desktop.
Popup window asks Protein-coding nucleotide sequence data??? select Yes?
Close Alignment Explorer? window

V. Making a Phylogenetic Tree
Now you should see the main window again.
Phylogeny? menu -> Construct/Test Neighbor Joining Tree?
Find your exported MEGA sequence alignment file (from Part IV) and open it.
Analysis preferences opens up: please make sure the appropriate settings for each category are set as follows:
Phylogeny Test: Bootstrap method
No of Bootstrap Replications: 500
Substitutions Type: Nucleotides
Model/Method: Maximum Composite Likelihood
Substitutions to Include: Transitions + Transversions
Rates Among Sites: Uniform Rates
Pattern Among Lineages: Same (Homogenous)
Gaps/Missing Data Treatment: Pairwise Deletion
Select Codon Positions: Check all boxes
Ignore the rest
Click Compute?.
After a minute or two, you will see your phylogenetic tree open up in the main screen. Click on the Bootstrap Consensus Tree? tab for a better view of all the branches.
*** STOP HERE AND LOOK AT WHAT YOUVE DONE BEFORE MOVING ON. ***
Take a moment to familiarize yourself with the format. The numbers at each node are the Bootstrap values. A value of 90 means that, when parts of the data are randomly deleted and the data is re-analyzed with some data missing, those sequences are still grouped together at least 90 percent of the time. In practice, values greater than 90 mean that the branch represents a good grouping, well supported by the sequence data. Values lower than 90 represent branches (clades) that should probably be ignored due to the uncertainty of the data.
The tree you generated is unrooted, meaning that you have to specify your outgroup.
Click on the LINE that connects to STANDARD Thymallus arcticus? to select this branch. The line should be highlighted in green.
Go to the Subtree? menu and select Root Tree?.
Your tree should now be correctly rooted with Thymallus arcticus as the outgroup.
Go to Image? menu > Save as PDF?. You can now annotate this tree per the instructions on the following pages. If you need a printout, please let your instructor know.
VI. Analyzing Your Phylogenetic Tree
Please read and follow instructions for annotating your phylogenetic tree on the lab write-up.
Label the reference sequences with the common names for those species:
Table 1. Reference salmon CO1 sequences and their common name.
Be sure to include your phylogenetic tree as part of your answers to the lab write-up.

Lab Write-Up: DNA Sequence Analysis
Please discuss these questions with your partner(s) but answer them INDIVIDUALLY. Short answer explanations need to be in your own words so I know that you understand your answers. For your lab write-up, type your final answers (using complete sentences) into a separate document.
Circle and label the following nodes on your CO1 consensus tree (use different colors and make sure you indicate your color/node combinations within your figure legend):
the node for the common ancestor of all the Oncorhynchus species.
the node for the common ancestor of all the Salmo species.
the node(s) on the tree with the highest possible bootstrap support (99-100).
Label the outgroup sequence, Thymallus arcticus, the arctic grayling, a species that is a salmonid in the salmon family but not closely related to what we call ?salmon. Use different color from Q#1 and make sure you indicate this new color/node combination within your figure legend.
Label the reference sequences on your consensus tree with the common names for those fish species (see Table 1).
Please answer the following questions regarding your CO1 consensus tree:
Are fish with the common name salmon? a monophyletic group? Why or why not?
Are fish with the common name trout? a monophyletic group? Why or why not?
Are fish belonging to the genus Oncorhynchus a monophyletic group? Why or why not?
Are fish belonging to the genus Salmo a monophyletic group? Why or why not?
Label each of our class samples with the proper species name. You can just write the name next to the sample name on your CO1 consensus tree.
Reference sequences (standards) are included to help you with this process. Look carefully at the branching pattern of the phylogeny to determine which standards have DNA sequences that form a clade with the class samples.
What species is your groups salmon samples?
Sample ID: Species:
Sample ID: Species:

Open the class data spreadsheet that is posted on Canvas.
Compare the advertised species names with their real species name as determined by DNA sequencing. Label on the tree every case of market substitution. Based on the tree, which samples are mislabeled to what species? Use the following labels.
Atlantic Pacific
Pacific Pacific
RECALL: Salmo salar = Atlantic salmon; Oncorhynchus species = Pacific salmon.
Fill in the following table using your class data. Remember that the data contains repeat trials of the same sample (so dont treat multiple replicates of the same sample as multiple samples in your analysis)! Include a table caption (located above the table) summarizing the information in this table when you submit your lab write-up.
Something to think about? should we include samples that were not successfully sequenced in the analysis of these data?
Other comments/observations: (e.g. identification of unknown samples?)
Once you have completed your annotations (Q#1-3 and Q#5-6), paste a copy of your final annotated CO1 consensus tree below. Include a figure legend (located below the figure) that briefly summarizes the information contained within your CO1 consensus tree when you submit your lab write-up.
Figure legends are 3-5 sentence descriptions of the data contained within a graph, schematic, or image/photograph. Should be self-explanatory and independent of any accompanying text.
Suppose you were a member of a public health agency responsible for enforcement of laws about accuracy in labeling. What additional information would you require before you would charge any of these stores (see Q#7) with a violation?
What questions did this study not address, or what would you like to have done further with more time/resources? Write a short paragraph proposing a next step? to this study. You may include diagrams/sketches to help you convey your idea. I encourage you to brainstorm some ideas and possibilities with your labmates, but your final proposal must be written in your own words.

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