Evolution & Bioinformatics <\/p>\n
Learning Outcomes <\/p>\n
Ability to complete a character matrix to use in constructing a phylogeny; <\/p>\n
Interpret a phylogeny and describe the evolutionary relationships depicted therein; <\/p>\n
Recognize and address misconceptions in evolutionary thinking; <\/p>\n
Compare and contrast different ways that you can infer the evolutionary history of an organism; and <\/p>\n
Describe and demonstrate how bioinformatic tools can be used to answer evolutionary questions. <\/p>\n
EVOLUTION <\/p>\n
The father of evolution, Charles Darwin, defined evolution as descent w\/ modification. A more fleshed out definition would describe evolution as a change in the genetic composition and heritable traits of a population over the course of many generations. As organisms evolve, genetic mutations allow for differences in their heritable traits to arise. The results of these mutations can be beneficial, detrimental, or \u2014as is most often the case\u2014 neutral. Beneficial traits that confer upon individuals increased chances of survival and reproduction in a given environment are called adaptations. As an environment changes over time, so will the traits that are considered to be adaptations. Adaptations, and all traits that are a result of genetic variation within a population, are acted on by natural selection. <\/p>\n
Natural selection is a force that results in the differential survival of individuals within a population due to differences in phenotype, or physical traits, with an underlying difference in genotype, or genetic makeup. Individuals possessing certain adaptations are more likely to survive than those that do not possess those adaptations. Heritable genetic variations that produce no difference in phenotype cannot be acted on by natural selection. Similarly, natural selection cannot act on a trait in which a population shows no genetic variability. Importantly, because natural selection acts on the genetic variability within a population, it is the population that evolves, not the individual. <\/p>\n
PHYLOGENETICS <\/p>\n
Phylogenetics is the study of the evolutionary relationships among taxa (singular: taxon), which can be individual organisms (e.g. species-level) or groups of organisms (e.g. phylumlevel). These relationships can be visually represented as phylogenetic trees. Phylogenetic trees have the various taxa that comprise them as leaves, or tips, on the ends of branches which represent lineages. Points at which branches meet are called nodes. Nodes indicate the most recent common ancestor (MRCA) of the taxa that are derived from that node. For example, in Figure 1a, the node indicated by the arrow represents the MRCA of taxa B, C, D, and E. These four taxa and their MRCA form a clade, a group consisting of a common ancestor and all of its descendants. Another term for clade is monophyletic group. If we were to include only B, C, and D, for instance, that would not be a clade because we would be omitting a descendent of the MRCA for that group. Instead, we would refer to a grouping of B, C, and D as a paraphyletic group, which is a clade missing one or more descendants from the common ancestor. The splitting of branches at a node indicates divergence events, where one lineage splits into two distinct descendent lineages. The root of the tree defines the point in the tree that acts as the MRCA for the taxa that make up the tree. Without a root, it is not possible to make inferences about evolutionary ancestry and determine when divergence events occurred in relation to one another. When the branches in a phylogenetic tree are shown to scale, the branch lengths can illustrate divergence times or the degree of genetic differences between taxa. <\/p>\n
Phylogenetic trees are hypotheses of evolutionary relationships, with the quality of a phylogeny being only as good as the quality of the data used to infer it. A rudimentary guiding principle in phylogenetics is that of maximum parsimony, which asserts that the best tree is the one that requires the fewest evolutionary changes to produce present-day observations. As more data is acquired (ex. through sequencing efforts), phylogenetic trees may change in their topology, the specific connection of nodes and branches that indicate the evolutionary history of taxa in a tree. A drawback of maximum parsimony is that a dataset can generate equally parsimonious trees with different topologies. Trees with equivalent topologies are congruent. While it may not be immediately apparent, the two trees in Figure 1a-b are congruent. The reason for this is that branches in a phylogeny can be rotated at the node, much like a mobile that one might find in a child\u2019s nursery, while still maintaining the depicted relationships. <\/p>\n
Figure 1(a) and (b): Phylogenies with congruent topologies; (c): Phylogeny showing synapomorphies (blue lines). <\/p>\n
Task 1 – MORPHOLOGY MATTERS <\/p>\n
The morphology, form and structure, of organisms give us clues about how closely related they are. When systematists select morphological traits to use in inferring evolutionary relationships among organisms, it is crucial that they choose traits that are a result of common ancestry. Morphological, or phenotypic, traits and genetic traits that are similar due a shared evolutionary history and common ancestor are said to be homologous. Homologous traits that are shared between a clade and its MRCA are called synapomorphies (Figure 1c). An often cited example of phenotypic homology would be the bone structure in the forelimbs of vertebrates (Figure 2). In contrast, analogous traits are those with a similar form or function that arose independently from one another through convergent evolution. An example of an analogous structure would be the wing of a bird and a bat. While they serve a similar function and may appear similar, they are structurally different and arose at different points in evolutionary time, not from the same common ancestor. <\/p>\n
Figure 2: Homology in the forelimb bone structure of six vertebrate organisms. <\/p>\n
Task 1a – HANDHELD TREE-BUILDING <\/p>\n
Procedure <\/p>\n
Table 1 represents a character matrix, where objects (ex. species) have a set of discrete characters (ex. traits) associated with them and these characters have a finite number of states (ex. presence or absence). Based on the organisms in Figure 3, complete the character matrix in Table 1. Put a \u201c1\u201d under characteristics present in a given organism and a \u201c0\u201d for characteristics that the organisms lacks. <\/p>\n
Figure 3: Six imaginary beetles. <\/p>\n
Table 1 <\/p>\n
Table 11.1 <\/p>\n
Identify a synapomorphy shared only amongst two taxa. We can assume that these taxa are closely related and should appear joined beside each other on the tree as sister taxa. <\/p>\n
Join the sister taxa using bracketsin the space provided under Question 1. Add the synapomorphy that you identified to the left-most branch, identifying where the trait evolved (hint: there are two pairs of sister taxa). <\/p>\n
Next, look to see if there is another synapomorphy shared between either pair of sister taxa and another taxon, but not with the other taxa in the dataset. Add this taxon as a branch connecting it to its close relatives and mark the synapomorphy on the appropriate branch. <\/p>\n
There should be one taxon left to add to the tree. Follow Step 3 in order to add that taxon to its correct branch on the tree. <\/p>\n
You now have two disconnected clades. Use branches to connect them to each other to have one complete phylogenetic tree. Label the root with the remaining synapomorphy shared by all taxa. <\/p>\n
Question <\/p>\n
1) Use the space below to draw a phylogeny of the organisms present in Figure 3. Don\u2019t forget to properly label tips and to add synapomorphies on their corresponding branches. <\/p>\n
Task 1b – \u201cLOOK MA\u2019, NO HANDS\u201d TREE-BUILDING <\/p>\n
Procedure <\/p>\n
1) You have been provided with a filled out character matrix for 7 major plant groups (Table 2). Use this matrix and the technique learned in Task 1a to draw a phylogeny in the space provided under Question 1. <\/p>\n
Table 11.2 _ <\/p>\n
Table 2 <\/p>\n
Figure 4: Seven representative plant groups -> (a) green algae, (b) liverworts, (c) gymnosperms, (d) ferns, (e) club mossed, (f) hornworts, (g) angiosperms <\/p>\n
Questions <\/p>\n
Using the filled in character matrix presented in Table 2, construct a phylogeny for the organisms shown in Figure 4. Don\u2019t forget to properly label tips and to add synapomorphies on their corresponding branches. <\/p>\n
Answer the following questions based on your newly drawn plant phylogeny. <\/p>\n
Club mosses are more closely related to hornworts than to gymnosperms. T F <\/p>\n
Ferns are equally related to angiosperms and gymnosperms. T F <\/p>\n
Angiosperms, gymnosperms, and ferns form a clade. T F 5. Hornworts, liverworts, and green algae form a clade. T F 6. List the synapomorphies shared by gymnosperms and hornworts. <\/p>\n
7. Which synapomorphy is on the branch leading to the MRCA of angiosperms and liverworts? <\/p>\n
Task 1c – CONGRUENCE CONG-RULES <\/p>\n
Procedure <\/p>\n
1) Use the phylogeny in Figure 5 to fill out the character matrix in Table 3. <\/p>\n
Table 3 <\/p>\n
Figure 5: Phylogenetic tree of various chordate organisms. 11. <\/p>\n
Questions <\/p>\n
Answer the following questions based on Figure 5. <\/p>\n
Which group is more closely related to ray-finned fish: hagfish or mammals? Explain. <\/p>\n
Which group is more closely related to amphibians: lizards or birds? Explain. <\/p>\n
Identify the reptilian organisms present in the phylogeny and mark them with a star. Would these organisms be considered a monophyletic group? Why or why not? <\/p>\n
In the space below, redraw the phylogeny in Figure 5 so that the taxa are vertically listed in the order that the first member of that group (ex. the first tunicate, the first hagfish, etc.) appeared in the fossil record. Place the oldest taxa at the top of the tree and the most recent taxa at the bottom of the tree. In redrawing the phylogeny, make sure to maintain the relationships depicted in Figure 5 (hint: node rotation). Add the synapomorphies to their corresponding branches in your newly drawn phylogeny. Biologically, are these trees different? Explain. <\/p>\n
Tunicates lack vertebrae, a trait present in all other chordates in our phylogeny. Would it be correct to refer to tunicates living today as \u201cbasal,\u201d \u201cancestral,\u201d or \u201cprimitive?\u201d Explain. <\/p>\n
Task 1d – GOTTA CATCH \u2019EM ALL <\/p>\n
Suppose that we have just discovered Pok\u00e9mon in the wild. In an attempt to place these organisms within their broader evolutionary context, scientists have sequenced their genomes. Through the principle of central dogma (DNA \u2192 RNA \u2192 protein, Figure 7), we are able to determine the amino acid sequences for the proteins coded by their genes. Some of these amino acid sequences have been made available to you for use in phylogenetic analysis. However, we are first going to hypothesize the evolutionary relationships between these organisms by using their morphological characteristics. <\/p>\n
Procedure <\/p>\n
Using only the images of the organisms in Figure 6, complete the character matrix in Table 4. Put a \u201c1\u201d under characteristics present in a given organism and a \u201c0\u201d for characteristics that the organisms lacks. <\/p>\n
Figure 6: Seven Pok\u00e9mon whose genomes have been sequenced -> (a) Pikachu, (b) Shellder, (c) Pidgeot, (d) Poliwhirl, (e) Venomoth, (f) Golbat, (g) Blastoise. <\/p>\n
Table 4 <\/p>\n
In the space below, construct a phylogeny based on the character matrix in Table 4. This phylogeny will serve as our hypothesis for the relationships between the organisms. Make sure to add the synapomorphies to their corresponding branches. <\/p>\n
What are some potential issues with drawing a tree based on morphological data like the one we just did? <\/p>\n
Task 2 – BIOINFORMATICS IS A BLAST <\/p>\n
BIOINFORMATICS <\/p>\n
With the advancement of molecular instruments for the lab, biology is quickly becoming a \u201cbig data\u201d science. We can define \u201cbig data\u201d with three Vs: volume, variety, and velocity (Dolinski & Troyanskaya, 2015). Biologists are constantly getting large amounts of data (volume) ranging from single DNA sequences to full proteomes (variety) in a short amount of time (velocity, Figure 7). Accumulation of sequence data is further accelerated not only by the increasing speed of sequencers but by the lowered costs of sequencing and computing technologies. Whereas in the past the issue was how to get these large amounts of data, we are now facing the problem of how to analyze all of this data now that we have it. As biology increasingly generates and relies on vast amounts of data to answer biological questions, the use of bioinformatics is becoming pervasive across disciplines. Bioinformatics is an interdisciplinary field that combines computer science and mathematics tools to process, store, understand, and analyze biological data. <\/p>\n
One such field that has benefitted from bioinformatic tools is that of phylogenetics. Phylogenetics has been revolutionized by the accumulation of genomic sequence data, changing it from one that relies on morphology to one that relies on genetic and genomic sequence data to reconstruct evolutionary histories. The enormous amounts of molecular data available not only make it possible to answer more complex evolutionary questions, but also necessitate bioinformatic tools. For instance, building a phylogeny can help scientists place a newly discovered species in its evolutionary context and inform the Linnaean classification of the species and can help us understand biodiversity. <\/p>\n
Figure 7: Central dogma; examples of the variety of biological \u201cbig data\u201d that can be analyzed using bioinformatic tools. <\/p>\n
We will be using a program called BLAST in order to identify organisms whose amino acid sequences are homologous to the one found in our Pok\u00e9mon. BLAST stands for Basic Local Alignment Search Tool. It works by using an input sequence (query sequence) and looking in a specific database for sequences that have regions of similarity, which can be interpreted as homology. Sequences identified by BLAST to be homologous to our query sequence are called target sequences. Much like how we can have phenotypic homology with morphological traits, we can also have molecular homology between genes and proteins across organisms. <\/p>\n
GOAL: Identify sequences belonging to the close relatives of your organism. <\/p>\n
Source File <\/p>\n
1) Your source file is called Pokemon_sequences. It contains the amino acid sequences for your organisms that you will need for this portion of the activity. Make sure you have downloaded your source file from Blackboard and opened it. <\/p>\n
Procedure <\/p>\n
1) In a web browser, navigate to: https:\/\/ncbi.nlm.nih.gov 2) Click on BLAST on the right side of the screen. <\/p>\n
Since we are working with amino acids, click on Protein BLAST. <\/p>\n
In the file called Pokemon_sequences, copy (Command-C or Ctrl-C) and paste<\/p>\n
(Command-V or Ctrl-V) the amino acid sequence from your organism into the box below \u201cEnter Query Sequence\u201d. Be sure you only include the amino acid sequence and not the name of your organism! <\/p>\n
Make sure the correct database is selected \u2013 it should be Reference proteins (refseq_protein). If it is not selected, click on the dropdown menu and select this database, otherwise, do not change any other settings on the page. <\/p>\n
Scroll down to the bottom of the page and click BLAST. <\/p>\n
Wait for the next page to load \u2013 when it does, it should look like the example in the accompanying screenshots. It will not be the same because you are looking at a different protein from a different organism. <\/p>\n
Scroll down. Under the heading \u201cGraphic Summary\u201d, you will see a graphical depiction of your query sequence at the top in blue. The red and pink lines represent other sequences, target sequences or hits, from the BLAST database that most closely resemble the sequence of your organism. Some of these hits may match only part of the sequence you submitted, and some may match the whole sequence. <\/p>\n
Scroll down. Under the heading \u201cDescriptions\u201d find the list of \u201cSequences producing significant alignments.\u201d These are the links to the same hits that were represented graphically above \u2013 do not click on the links! The description of the sequence usually ends with the genus and species of the organism it came from, for example, in Homo <\/p>\n
sapiens, Homo is the genus and sapiens is the species. <\/p>\n
Recall that phylogenies are only as good as the data used to construct them. On the right-hand side of your hits, there are different columns with metrics that can tell you about the quality of your data. One such metric is the E-value (Expect Value), which describes the likelihood that a hit is part of your results by random chance alone. The smaller the E-value, the higher the likelihood that the hit you got is significant. E-values can even be as small as zero! Normally, a researcher would pay a lot of attention to the E-value of their BLAST results and choose the sequences for their dataset carefully. For simplicity, all of the sequences you have been provided with have been carefully chosen to ensure significant hits. <\/p>\n
Check the boxes next to the first 10 different genus names. If your list contains only a few genus names, click on as many as you can find, and then select different species within the same genus. It is okay if you don\u2019t know what they are yet. <\/p>\n
Make sure the number of checked\/selected boxes is 10, as in the picture. <\/p>\n
Click on download. Select \u201cFASTA (complete sequence)\u201d, and click \u201cContinue\u201d. This will download a file of the 10 selected protein sequences to your computer \u2013 note where the file will be saved. The file will be called \u201cseqdump\u201d. <\/p>\n
Do not open the file in Microsoft Word or Notepad. If you are on a Mac, open the seqdump file with TextEdit (pre-installed in your applications folder). If you are on a<\/p>\n
PC, open the file with WordPad. Look over the sequence, but do not type or delete anything. We will use this file as the starting point for the next step of our project. <\/p>\n
In the Pokemon_sequence file, copy the sequence of your organism, then paste it at the beginning of the seqdump file. Make sure that the sequence for each organism, which begins with a \u201c>\u201d starts on its own line. <\/p>\n
If you have extra time, try looking up the names of the organisms in your list to learn more about them. <\/p>\n
Task 3 – COMPUTING RELATIONSHIPS <\/p>\n
In order for us to build a phylogeny, we must first align our sequences. We will create a multiple sequence alignment (Figure 8) using the DNA sequences below and later using the amino acid sequences that we have retrieved for our organisms. A multiple sequence alignment is a way to arrange sequences, whether DNA, RNA or protein, such as to identify regions of similarity and dissimilarity that can later be used to determine evolutionary relationships. Sequences used to create a multiple sequence alignment must be homologous, meaning they share an evolutionary history together. <\/p>\n
We will be using a software called MAFFT (Multiple Alignment using Fast Fourier Transform) to build a multiple sequence alignment for our amino acid sequences. We will then be using the output that MAFFT gives us as the input for building a tree. Any time that bioinformatic tools like MAFFT are being used, there are specific algorithms that determine how the program will work. An algorithm is a specific set of rules on how to solve a type of problem, such as building a multiple sequence alignment or a phylogenetic tree. <\/p>\n
Figure 8: Example of a multiple sequence alignment built using the MAFFT web server. <\/p>\n
GOAL: To create an amino acid multiple sequence alignment and use it to build a phylogenetic tree of the Pok\u00e9mon and its closest relatives. <\/p>\n
Procedure A <\/p>\n
In a new browser tab, navigate to http:\/\/mafft.cbrc.jp\/alignment\/server\/. MAFFT is a program that will help us build a multiple sequence alignment with the amino acid sequences we obtained from using BLAST. MAFFT will also help us to build a phylogenetic tree using our multiple sequence alignment. <\/p>\n
In the seqdump file, which should now include your Pok\u00e9mon sequence, select all of the text (Command-A or Ctrl-A), and copy. <\/p>\n
In the MAFFT window, paste the sequences. <\/p>\n
Scroll down. Note that there are many different settings and parameters that can be changed, but do not change any for now. <\/p>\n
Click on the submit button part way down the page. The results from MAFFT with the multiple sequence alignment based on your amino acid sequences will appear on the screen. <\/p>\n
Scroll down. This is one way that the alignment can be visualized. Hyphens (-) indicate gaps in the alignment. <\/p>\n
Scroll back up and click on \u201cView\u201d. <\/p>\n
Click on \u201cStart MSAViewer in this window\u201d. <\/p>\n
Look at the alignment \u2013 scroll over using the scroll bar at the top. Each amino acid is highlighted in a different color, making it easy to see where there are differences between sequences. <\/p>\n
Questions <\/p>\n
Based on what you know about DNA, what do you think causes gaps in sequence alignments? <\/p>\n
Why do you think aligning sequences is important before creating a phylogeny? <\/p>\n
Procedure B <\/p>\n
Now, we will make a phylogenetic tree based on these amino acid sequences. Click on \u201cTree\u201d at the top of your screen. <\/p>\n
Under the heading \u201cMethod\u201d, make sure the option \u201cNJ \u2190 (All of gap-free sites)\u201d is selected. Then, click \u201cGo!\u201d. <\/p>\n
When the next page loads, click \u201cView tree on Phylo.io\u201d. This will open a new window, which you can make bigger, as necessary. <\/p>\n
You have successfully built a phylogenetic tree! Now, let\u2019s see what these things are, and where they fall under a broader evolutionary context. <\/p>\n
Task 4 – FULL PHYLOGENETIC CONTEXT Procedure <\/p>\n
Use your favorite search engine to search for the names of the organisms in your tree. List each scientific name (Genus species) and common name (if applicable). <\/p>\n
Table 5 <\/p>\n
Table 11 <\/p>\n
Questions <\/p>\n
Based on the phylogeny you built, which of these organisms form sister taxa with the Pok\u00e9mon that you were investigating? <\/p>\n
Based on the sister taxa and other close relatives of your Pok\u00e9mon, where does your Pok\u00e9mon fall in the broader evolutionary context represented by the phylogeny below? Go up to the board and add your Pok\u00e9mon to the correct spot! Also, fill in all the blanks below. <\/p>\n
How do the relationships between the Pok\u00e9mon in the phylogeny above compare to the relationships between Pok\u00e9mon we hypothesized based on morphology? Using just the Pok\u00e9mon, draw a phylogeny below to illustrate how they relate to one another. <\/p>\n
Based on these exercises, do you think that molecular or morphological data are better for inferring evolutionary relationships? Why? <\/p>\n
Can you think of an example where molecular data would be better for inferring evolutionary relationships? Can you think of an example where morphological data would be better for inferring evolutionary relationships? <\/p>\n
1 <\/p>\n
1 <\/p>\n
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Evolution & Bioinformatics Learning Outcomes Ability to complete a character matrix to use in constructing a phylogeny; Interpret a phylogeny and describe the evolutionary relationships depicted therein; Recognize and address misconceptions in evolutionary thinking; Compare and contrast different ways that you can infer the evolutionary history of an organism; and Describe and demonstrate how bioinformatic […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[10],"class_list":["post-78463","post","type-post","status-publish","format-standard","hentry","category-research-paper-writing","tag-writing"],"_links":{"self":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/posts\/78463","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/comments?post=78463"}],"version-history":[{"count":0,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/posts\/78463\/revisions"}],"wp:attachment":[{"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/media?parent=78463"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/categories?post=78463"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/papersspot.com\/blog\/wp-json\/wp\/v2\/tags?post=78463"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}