Difference between revisions of "BIO Assignment 4 2011"

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Assignment 4 - Homology modeling
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Assignment 4 (last: 2011) - Phylogenetic Analysis
 
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;How could the search for ultimate truth have revealed so hideous and visceral-looking an object?
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Introduction
::''<small>Max Perutz (on his first glimpse of the Hemoglobin structure)</small>''
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&nbsp;
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;Nothing in Biology makes sense except in the light of evolution.
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:''Theodosius Dobzhansky''
 
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Where is the hidden beauty in structure, and where, the "ultimate truth"? In the previous assignments we have studied sequence conservation in APSES family domains and we have discovered homologues in all fungal species. This is an ancient protein family that had already duplicated to several paralogues at the time the cenancestor of all fungi lived, more than 600,000,000 years ago, in the [http://www.ucmp.berkeley.edu/fungi/fungifr.html Vendian period] of the Proterozoic era of Precambrian times.
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... but does evolution make sense in the light of biology?
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As we have seen in the previous assignments, the Mbp1 transcription factor has homologues in all other fungi, yet there is not always a clear one-to-one mapping between members of a family in distantly related species. It appears that various systems of APSES domain transcription factors have evolved independently. Of course this bears directly on our notion of function - what it means to say that two genes in different organisms have the "same" function. In case two organisms both have an orthologous gene for the same, distinct function, saying that the function is the same may be warranted. But what if that gene has duplicated in one species, and the two paralogues now perform different, related functions in one organism? Theses two are still orthologues to the other species, but now we expect functionally significant residues to have adapted to the new role of one paralogue. In order to be able to even ask such questions, we need to make the evolutionary history of gene families explicit. This is the domain of '''phylogenetic analysis'''. We can ask questions like: how many paralogues did the cenancestor of a clade possess? Which of these underwent additional duplications in the phylogenesis of the organism I am studying? Did any genes get lost? And - adding additional biological insight to the picture - did the observed duplications lead to the "invention" of new biological systems? When was that? And perhaps even: how did the species benefit from this event?
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We will develop this kind of analysis in this assignment. In the previous assignment you have established which gene in your species is the reciprocally most closely related orthologue to yeast Mbp1 and you have identified the full complement of APSES domain genes in your assigned organism. In this assignment, we will analyse these genes' evolutionary relationship and compare it to the evolutionary relationship of all fungal APSES domains. The goal is to define families of related transcription factors and their evolutionary history.
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A number of excellent tools for phylogenetic analysis exist; ''general purpose packages'' include the (free) [http://evolution.genetics.washington.edu/phylip.html PHYLIP] package and the (commercial) PAUP package. ''Specialized tools'' for tree-building include Treepuzzle or Mr. Bayes. This assignment is constructed around programs that are available in PHYLIP, however you are welcome to use other tools that fulfill a similar purpose if you wish. In this field, researchers consider trees that have been built with ML (maximum likelihood) methods to be more reliable than trees that are built with parsimony methods, or distance methods such as NJ (Neighbor Joining). However ML methods are also much more compute-intensive. Just like with multiple sequence alignments, some algorithms will come closer to guessing the truth and others will not and usually it is hard to tell which is the more trustworthy of two diverging results. The prudent researcher tries out alternatives and forms her own opinion. Specifically, we may usually assume results that converge when computed with different algorithms, to be more reliable than those that depend strongly on a particular algorithm, parameters, or details of input data.
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However: regarding algorithm and resources, we will take a shortcut in this assignment (something you should not do in real life). We will assume that the tree the algorithm constructs is correct. In "real life" you would establish its reliability with a bootstrap procedure: repeat the tree-building a hundred times with partial data and see which branches and groupings are robust and which depend on the details of the data. In this assignment, we should simply acknowledge that bifurcations that are very close to each other have not been "resolved" and be appropriately cautious in our inferences. In phylogenetic analysis, not all lines a program draws are equally trustworthy. Don't take the trees as a given fact just because a program suggests this. Look at the evidence, include independent information where available, use your reasoning, and analyse the results critically. As you will see, there are some facts that we know for certain: we know which species the genes we have sequenced come from, and we can (usually) make good assumptions about the relationship of the species themselves - the history of speciation events that underlies all evolution of genes. This is extremely helpful information for our work.  
  
In order to understand how specific residues in the sequence contribute to the putative function of the protein, and why and how they are conserved throughout evolution, we would need to study an explicit molecular model of an APSES domain protein, bound to its cognate DNA sequence. Explanations of a protein's observed properties and functions can't rely on the general fact that it binds DNA, we need to consider details in terms of specific residues and their spatial arrangement. In particular, it would be interesting to correlate the conservation patterns of key residues with their potential to make specific DNA binding interactions. Unfortunately, no APSES domain structures in complex with bound DNA has been solved up to now, and the experimental evidence we have considered in Assignment 2 ([http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=10747782 Taylor ''et al.'', 2000]) is not sufficient to unambiguously define the details of how a DNA double helix might be bound. Moreover, at least two distinct modes of DNA binding are known for proteins of the winged-helix superfamily, of which the APSES domain is a member.
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=====Introduction: Tasks=====
  
''In this assignment you will (1) construct a molecular model of the Mbp1 orthologue in your assigned organism, (2) identify similar structures of distantly related domains for which protein-DNA complexes are known, (3) assemble a hypothetical complex structure and(4) discuss whether the available evidence allows you to distinguish between different modes of ligand binding, ''
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For this assignment, we start from the APSES domains you have collected previously. You will align these domains with a set of reference domains and edit the alignment to make it suitable for phylogenetic analysis, using Jalview. Then you will construct a phylogenetic tree and interpret the tree. The goal is to identify orthologues and paralogues. <!-- Optionally, you will look at structural and functional conservation of residues. -->
  
For the following, please remember the following terminology:
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In case you want to review concept of trees, clades, LCAs, OTUs and the like, I have linked an excellent and very understandable introduction-level [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/Baldauf_2003_PhylogenyTutorial.pdf article on phylogenetic analysis (pdf)] here and to the resource section at the bottom of this page.
  
;Target
 
:The protein that you are planning to model.
 
;Template
 
:The protein whose structure you are using as a guide to build the model.
 
;Model
 
:The structure that results from the modeling process. It has the '''Target sequence''' and is similar to the '''Template structure'''.
 
 
&nbsp;
 
&nbsp;
 
A brief overview article on the construction and use of homology models is linked to the resource section at the bottom of this page. That section also contains links to other sites and resources you might find useful or interesting.
 
  
 
{{Template:Preparation|
 
{{Template:Preparation|
care=Be sure you have understood all parts of the assignment and cover all questions in your answers! Sadly, we see too many assignments which, arduously effected, nevertheless intimate nescience of elementary tenets of molecular biology. If the sentence above did not trigger an urge to open a dictionary, you are trying to guess, rather than confirm possibly important information.|
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care=Be sure you have understood all parts of the assignment and cover all questions in your answers! Sadly, we always get assignments back in which important aspects have simply overlooked marks unnecessarily. If you did not notice that the above did not make sense, you are reading what you expect, not what is written.|
 
num=4|
 
num=4|
 
ord=fourth|
 
ord=fourth|
due = Monday, November 12 at 10:00 in the morning}}
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due = Monday, November 28 at 12:00 in the morning}}
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;Your documentation for the procedures you follow in this assignment will be worth 1 mark.
  
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==(1) Preparation==
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==(1) Preparations==
 
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===(1.1) Template choice and sequence (1 mark)===
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===(1.1) Preparing Input Files===
 
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</div>
 
&nbsp;<br>
 
&nbsp;<br>
Often more than one related structure can be found in the PDB. We have touched on principles of selecting template structures in the lecture and there is a short summary of [[Template_choice_principles|template choice principles]] on this Wiki. One can either search the PDB itself through its '''Advanced Search''' interface; for example one can search for sequence similarity with a BLAST search, or search for structural similarity by accessing structures according to their CATH or SCOP classification. But one can always also use the BLAST interface at the NCBI, since the sequences contained in PDB files are accessible as a database subsection on the BLAST menu.
 
  
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For this assignment, we start from the multiple sequence alignments we have constructed previously. We will edit the alignment to make it suitable for phylogenetic analysis. We will construct a phylogenetic tree and we will analyse the tree.
*Use the NCBI BLAST interface to identify all PDB files that are clearly homologous to your target APSES domain, if you haven't already done so in Assignment 2. Document that you have searched in the correct subsection of the database by selecting "pdb" on the database options menu. For the hits you find, consider how these coordinate sets differ and which features would make each more or less suitable for your task by commenting briefly on
+
 
:*sequence similarity to your target
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=====Introduction: Principle=====
:*size of expected model (length of alignment)
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:*presence or absence of ligands
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In order to use molecular sequences for the construction of phylogenetic trees, you have to build a multiple alignment first, then edit it. This is important: all rows of sequences have to contain the exact same number of characters and to hold '''aligned characters in corresponding positions'''. Phylogeny programs are not meant to revise an alignment but to analyze evolutionary relationships, '''after''' the alignment has been determined. The program's inferences are made on a column-wise basis and if your columns contain data from unrelated positions, the inferences are going to be questionable.
:*experimental method and quality of the data set
 
Then choose the '''template''' you consider the most suitable and note why you have decided to use this template.
 
  
* Retrieve the most suitable template structure coordinate file from the PDB.
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The result of the tree construction is a decision about the most likely evolutionary relationships. Fundamentally, tree-construction programs decide which sequences had common ancestors.
  
(0.5 marks)
 
</div>
 
  
It is not straightforward at all how to number sequence in such a project. The "natural" numbering starts with the start-codon of the full length protein and goes sequentially from there. However, this does not map exactly to other numbering schemes we have encountered. As you know the first residue of the APSES domain as the CDD defines it is not Residue 1 of the Mbp1 protein. The first residue of the e.g. 1MB1 FASTA file '''is''' the first residue of Mbp1 protein, but the last five residues are an artifical His tag. Is H125 of 1MB1 thus equivalent to R125 in MBP1_SACCE? The N-terminus of the Mbp1 crystal structure is disordered. The first residue in the structure is ASN 3, therefore N is the first residue in a FASTA sequence derived from the cordinate section of the PDB file (the <code>ATOM  </code> records; whereas the SEQRES records start with MET ... and so on. You need to remember: a sequence number is not absolute, but derived from a particular context.
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'''Distance based''' phylogeny programs start by using sequence comparisons to estimate evolutionary distances:
  
The homology model will be based on an alignment of target and template. Thus we have to define the target sequence. As discussed in class, PDB files have an explicit  and an implied sequence and these do not necessarily have to be the same. To compare the implied and the explicit sequence for the template, you need to extract sequence information from coordinates. One way to do this is via the Web interface for [http://swift.cmbi.ru.nl/servers/html/index.html '''WhatIf'''], a crystallography and molecular modeling package that offers many useful tools for coordinate manipulation tasks.  
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* they apply a model of evolution such as a mutation data matrix, to calculate a score for each pair of sequences,
 +
* this score is stored in a "distance matrix" ...
 +
* ... and used to estimate a tree that groups sequences with close relationships together. (e.g. by using an NJ, Neigbor Joining, algorithm).  
  
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They are fast, can work on large numbers of sequences, but are less accurate if genes evolve at different rates.
*Navigate to the '''Administration''' sub-menu of the [http://swift.cmbi.ru.nl/servers/html/index.html WhatIf Web server]. Follow the link to '''Make sequence file from PDB file'''. Enter the PDB-ID of your template into the form field and '''Send''' the request to the server. The server accesses the PDB file and extracts sequence information directly from the <code>ATOM&nbsp;&nbsp;</code> records of the file. The results will be returned in PIR format. Copy the results, edit them to FASTA format and save them in a text-only file. Make sure you create a valid FASTA formatted file! Use this '''implied''' sequence to check if and how it differs from the sequence ...
 
  
:*... listed in the <code>SEQRES</code> records of the coordinate file;
 
:*... given in the FASTA sequence for the template, which is provided by the PDB;
 
:*... stored in the protein database of the NCBI.
 
: and record your results.
 
  
* In a table, establish how the sequence numbers in the coordinate section of your template(*) correspond to your target sequence numbering.  
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'''Parsimony based''' phylogeny programs build a tree that minimizes the number of mutation events that are required to get from a common ancestral sequence to all observed sequences. They take all columns into account, not just a single number per sequence pair, as the Distance Methods do. For closely related sequences they work very well, but they construct inaccurate trees when they can't make good estimates for the required number of sequence changes.
  
(0.5 marks)
 
</div>
 
  
:(*) <small>These residue numbers are important, since they are referenced e.g. by VMD when you visualize the structure. The easiest way to list them is via the ''Sequence Viewer'' extension of VMD.</small>.
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'''ML''', or '''Maximum Likelihood''' methods attempt to find the tree for which the observed sequences would be the most likely under a particular evolutionary model. They are based on a rigorous statistical framework and yield the most robust results. But they are also quite compute intensive and a tree of the size that we are building in this assignment is a challenge for the resources of common workstation (runs about an hour on my computer). If the problem is too large, one may split a large problem into smaller, obvious subtrees (e.g. analysing orthologues as a group, only including a few paralogues for comparison) and then merge the smaller trees; this way even very large problems can become tractable.
:<small>Don't do this for every residue individually but define ranges. Look at the correspondence of the first and last residue of target and template sequence and take indels into account. Establishing sequence correspondence precisely is crucially important! For example, when a publication refers to a residue by its sequence number, you have to be able to relate that number to the residue numbers of the model as well as your target sequence.</small>.
 
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ML methods suffer less from "long-branch attraction" - the phenomenon that weakly similar sequences can be grouped inappropriately close together in a tree due to spuriously shared differences.
  
===(1.2) The input alignment  (1 mark)===
 
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The sequence alignment between target and template is the single most important factor that determines the quality of your model. No comparative modeling process will repair an incorrect alignment; it is useful to consider a homology model rather like a three-dimensional map of a sequence alignment rather than a structure in its own right. In a homology modeling project, typically the largest amount of time should be spent on preparing the best possible alignment. Even though automated servers like the SwissModel server will align sequences and select template structures for you, it would be unwise to use these only because they are convenient. You should take advantage of the much more sophisticated alignment methods available. Analysis of wrong models can't be expected to produce right results.
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Clearly, in order for tree-estimation to work, one must not include fragments of sequence which have evolved under a different evolutionary model as all others, e.g. after domain fusion, or after accommodating large stretches of indels. Thus it is appropriate to edit the sequences and pare them down to a most characteristic subset of amino acids. The goal is not to be as comprehensive as possible, but to input those columns of aligned residues that will best represent the true phylogenetic relationships between the sequences.
  
The best possible alignment is usually constructed from a multiple sequence alignment that includes at least '''the target and template sequence''' and other related sequences as well. The additional sequences are an important aid in identifying the correct placement of insertions and deletions. Your alignment should have been carefully reviewed by you and wherever required, manually adjusted to move insertions or deletions between target and template out of the secondary structure elements of the template structure.
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=====Introduction: Gaps=====
  
In the case of Mbp1 genes however, all orthologues we have considered have no indels in the APSES domain regions. Evolutionary pressure on the APSES domains has selected against indels in the more than 600 million years these sequences have evolved independently in their respective species.
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Gaps are a real problem here, as usual. Strictly speaking, the similarity score of an '''alignment''' program as well as the distance score of a '''phylogeny''' program are not calculated for an ordered sequence, but for a sum of independent values, one for each aligned columns of characters. The order of the columns does not change the score. However in an optimal sequence alignment with gaps, this is no longer strictly true since a one-character gap creation has a different penalty score than a one-character gap extension! Most '''alignment''' programs use a model with a constant gap insertion penalty and a linear gap extension penalty. This is not rigorously justified from biology, but parametrized (or you could say "tweaked") to correspond to our observations. However, most '''phylogeny''' programs, (such as the programs in PHYLIP) do not work in this way. PHYLIP strictly operates on columns of characters and treats a gap character just like a residue with the one letter code "-". Thus gap insertion- and extension- characters get the same score. For short indels, this '''underestimates''' the distance between pairs of sequences, since any evolutionary model should reflect the fact that gaps are much less likely than point mutations. If the gap is very long though, all events are counted individually as many single substitutions (rather than one lengthy one) and this '''overestimates''' the distance. And it gets worse: long stretches of gaps can make sequences appear similar in a way that is not justified, just because they are identical in the "-" character. It is therefore common and acceptable to edit gaps in the alignment and delete all but one or two columns of gapped sequence, or to remove such columns altogether.
  
Accordingly, all we need to do is to write the APSES domain sequences one under the other.
 
  
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=====Introduction: The outgroup=====
* Copy the FASTA formatted sequence for the APSES domain of your organism's Mbp1 orthologue from the sequences [[All_APSES_domains|defined in Assignment 3]] and save it as FASTA formatted text file. This is your '''target''' sequence. Compare this with the FASTA formatted file you have extracted from the PDB coordinate set. This is your '''template''' sequence. Then generate a multi-FASTA formatted file that contains both sequences, and '''pad''' the sequence(s) where required with hyphens as gap characters, so that target and template sequences have exactly the same length and are aligned.  Refer to the [[Assignment_4_fallback_data|'''Fallback data''']] if you are not sure about the format.
 
  
(1 mark)
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To analyse phylogenetic trees it is useful (and for some algorithms required) to define an outgroup, a sequence that presumably diverged from all other sequences in a clade before they split up among themselves. Wherever the outgroup inserts into the tree, this is the root of the rest of the tree. And whenever a molecular clock is assumed, the branching point that connects the outgroup can be assumed to be the oldest divergence event. I have defined an outgroup sequence and added it to the [[Reference APSES domains|reference APSES domains page]]. The procedure is explained in detail on that page.
</div>
 
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>gi|301025594|ref|ZP_07189117.1| KilA-N domain protein [Escherichia coli MS 69-1]
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<span style="color: #999999;">MTSFQLSLISRE</span>IDGEIIHLRAKDGYINATSMCRTAGKLLSDYTRLKTTQEFFDELSRDMGIPISELIQS
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  FKGGRPENQGTWVHPDIAINLAQ<span style="color: #999999;">WLSPKFAVQVSRWVREWMSGERTTAEMPVHLKRYMVNRSRIPHTHFS
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ILNELTFNLVAPLEQAGYTLPEKMVPDISQGRVFSQWLRDNRNVEPKTFPTYDHEYPDGRVYPARLYPNE
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YLADFKEHFNNIWLPQYAPKYFADRDKKALALIEKIMLPNLDGNEQF</span>
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''E. coli'' KilA-N protein. Residues that do not align with APSES domains are shown in grey.
  
==(2) Homology model==
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=====Preparing APSES sequences=====
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=== (2.1) SwissModel (1 mark)===
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#Navigate to the [[Reference APSES domains|reference APSES domains page]] and copy the sequences.
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#Open Jalview, select '''File &rarr; Input Alignment &rarr; from Textbox''' and paste the sequences into the textbox.
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#Add the APSES domain sequences '''from your species''' that you have defined in the previous assignment.
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#When all the sequences are present, click on '''New Window'''.
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#In Jalview, select Web Service &rarr; Alignment &rarr; MAFFT Multiple Sequence Alignment. The alignment is calculated in a few minutes and displayed in a new window.
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#Choose any colour scheme and add '''Colour &rarr; by Conservation'''. Adjust the slider left or right to see which columns are highly conserved.
 +
#Save the alignment as a Jalview project before editing it for phylogenetic analysis. You may need it again.  
 
</div>
 
</div>
&nbsp;<br>
 
  
Access the Swissmodel server at '''http://swissmodel.expasy.org''' . Navigate to the '''Alignment Interface'''.
 
  
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
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=====Introduction: Alignment editing for phylogenetic reconstruction=====
*Paste your alignment for target and model into the form field. Refer to the [[Assignment_4_fallback_data|'''Fallback Data file''']] if you are not sure about the format. Make sure to select the correct option for the alignment input format on the form.
 
:<small>(You have to choose the correct format, and, if e.g. you choose a CLUSTAL format, you have to include a header line and a blank line. In the past we have seen problems with uploading alignments that have not been saved as "text only" and including periods i.e.  "."  in sequence names of CLUSTAL formatted alignments. Underscores appear to be safe.</small>
 
  
* Click '''submit alignment ''' and on the returned page define your '''target''' and '''template''' sequence. For the '''template sequence''' define the PDB ID of the coordinate file. Enter the correct Chain-ID.
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In practice, follow the fundamental principle that '''all characters in a column should be related by homology'''. This implies the following rules of thumb:
:<small>Recently the PDB has undergone a "remediation" process in which archived coordinate files were altered by the database to conform to new format standards. One of the changes was to assign a chain identifier of "A" to all chains that did not previously have a chain identifier. SwissModel uses a derivative of coordinate sets from the PDB (a dataset they call ExPDB). Apparently the PDB proper and ExPDB have now gone out of synchrony; when I entered the (correct, according to PDB) chain designation "A" for 1MB1, SwissModel rejected the alignment with a nondescript error message. When I entered an underscore "_" instead, which would be the designation for a chain without explicit chain identifier, such as the pre-remidation versio of the coordinates, the alignment was accepted and processed. I have e-mailed SwissModel about the problem; they are in the process of correcting it and may or may not be done while you are working on your assignments. If your template chain has the chain identifier "A" and your alignment gets rejected, try entering entering an underscore instead.</small>
 
:<small>'''Enter''' the correct chain ID into the form-field even if you think it already appears there, don't simply accept the preloaded default. There is a bug in SwissModel's parser code that may cause incorrect strings to be sent to the server from that field. I have e-mailed SwissModel about the problem which may or may not be corrected while you are working on your assignments.</small>
 
  
*Click '''submit alignment''' and review the alignment on the returned page. Make sure it has been interpreted correctly by the server. The conserved residues have to be lined up and matching. Then click '''submit alignment''' again, to start the modeling process.
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*Remove all stretches of residues in which the ''alignment'' appears ambiguous (not just highly variable, but ambiguous regarding the aligned positions).
 +
*Remove all frayed N- and C- termini, especially regions in which not all sequences that are being compared appear homologous and that may stem from unrelated domains.
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*Remove all gapped regions that appear to be alignment artefacts due to inappropriate input sequences.  
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*Remove all but approximately one column from gapped regions '''in those cases where the presence of several related insertions suggest that the indel is real, and not just an alignment artefact.''' (Some researchers simply remove all gapped regions).
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*Remove sections N- and C- terminal of gaps where the alignment appears questionable. 
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*Also, consider that neither residues that are completely different between all species, nor residues that are completely conserved are informative for relationship distances.
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*If your sequences are too long, your tree calculations may run out of memory. 60-80 aligned residues should be plenty and if the sequences fit on a single line you will save yourself potential trouble with block-wise vs. interleaved input.If you do run out of memory try removing columns of sequence.
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*Move the KilA-N outgroup sequence to the first line of your alignment, since this is where PHYLIP will look for it by default.  
  
* The resulting page returns information about the resulting model. Save the '''model coordinates''' on your computer. Read the information on what is being returned by the server (click on the red questionmark icon). Paste the Anolea profile into your assignment.
 
:<small>Do not paste a screenshot of the result, but copy and paste the image from the Web-page! You do not need to submit the actual coordinate files with your assignment.</small>
 
  
(1 mark)
 
</div>
 
&nbsp;<br>
 
In case you do not wish to submit the modelling job yourself, or have insurmountable problems when using the SwissModel interface, you may access the result files from the  [[Assignment_4_fallback_data|'''Fallback Data file''']]. Document the problems and note this in your assignment.
 
  
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[[Image:EditingGuide.jpg|frame|none|(Possible) steps in editing a multiple sequence alignment towards a PHYLIP input file. '''a''': raw alignment (CLUSTAL format); '''b''': sequences assembled into single lines; '''c''': columns to be deleted highlighted in red - 1, 3 and 4: large gaps; 2: uncertain alignment and 5: frayed C-terminus: both would put non-homologous characters into the same column; '''d''': input data for PHYLIP: names for sequences must not be longer than 10 characters, the first line must contain the number of sequences and the sequence length. PHYLIP is very picky about incorrectly formatted input, read the [http://evolution.genetics.washington.edu/phylip/doc/sequence.html PHYLIP sequence format guide].]]
  
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;Once you are satisfied with your editing, proceed as follows:
  
==(3) Model analysis==
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<div style="padding: 5px; background: #DDDDEE;">
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#Download the PHYLIP package from the [http://evolution.genetics.washington.edu/phylip.html Phylip homepage] and install it on your computer.
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#Prepare a PHYLIP input file from your Jalview alignment. The simplest way to achieve this appears to be:
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##In Jalview, use '''File &rarr; Output to Textbox&rarr;FASTA''', then '''Edit&rarr;Select All''' and '''Edit&rarr;copy''' the sequences.
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##In a browser, navigate to the [http://www-bimas.cit.nih.gov/molbio/readseq/ '''Readseq sequence conversion service'''].
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##Paste your sequences into the form and choose '''Phylip''' as the output format. Click on '''submit'''.
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##Save the resulting page as a text file in the directory where the phylip executables reside on your computer. Give it some useful name such as <code>All-APSES_domains.phy</code>.
 +
#Make a copy of that file and name it <code>infile</code>. Note: make sure that your Microsoft Windows operating system does not silently append the extension ".txt" to your file. It should be called "infile", nothing else and you should never, never, ever permit your operating systems to slyly hide file extensions from you when it displays filenames. You have been warned.
 
</div>
 
</div>
&nbsp;
+
 
&nbsp;
 
  
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
=== (3.1) The PDB file (1 mark)===
+
 
 +
===(1.2) Calculating a Tree===
 
</div>
 
</div>
 +
 +
&nbsp;<br>
 
&nbsp;<br>
 
&nbsp;<br>
 +
<div style="padding: 5px; background: #DDDDEE;">
  
Open your '''model''' coordinates in a text-editor (make sure you view the PDB file in a fixed-width font) and consider the following questions: (Alternatively, view the coordinates linked to the [[Assignment_5_fallback_data|'''Fallback Data file''']].)
+
*Use the '''proml''' program of PHYLIP (protein sequences, maximum likelihood tree) to calculate a phylogenetic tree. Use the default parameters except that you must change option <code>S: Speedier but rougher analysis?</code> to No - your analysis should not sacrifice accuracy for speed. The calculation will take a while.
  
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
 
*What is the residue number of the first residue in the '''model'''? What should it be, based on the alignment? If the putative DNA binding region was reported to be residues 50-74 in the Mbp1 protein, which residues of the '''model''' correspond to that?
 
(1 mark)
 
 
</div>
 
</div>
  
<!-- discuss flagging of loops - setting of B-factor to 99.0 phps. ANOLEA vs. Gromos ... packing vs. energy? -->
+
&nbsp;<br>
&nbsp;
+
&nbsp;<br>
&nbsp;
+
 
 +
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
  
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
+
==(2) Analysis (2 marks)==
===(3.2) First visualization (1 mark)===
 
 
</div>
 
</div>
&nbsp;<br>
 
  
In assignment 2 you have already studied a Mbp1 structure and compared it with your organism's Mbp1 APSES domain, Since a homology model inherits its structural details from the '''template''', the model should look very similar to the original structure but contain the sequence of the '''target'''.
+
I have constructed a cladogram for the species we are analysing, based on data published for 1551 fungal ribosomal sequences. Such reference tres from rRNA data are a standard method of phylogenetic analysis, supported by the assumption that rRNA sequences are monophyletic and have evolved under comparable selective pressure in all species.
 +
 
 +
[[Image:FungiCladogram.jpg|frame|none|Cladogram of fungi studied in the assignments. This cladogram is based on small subunit ribosomal rRNA sequences, and largely follows ''Tehler et al.'' (2003) ''Mycol Res.'' '''107''':901-916. Even though many details of fungal phylogeny remain unresolved, the branches shown here individually appear to have strong support. In a cladogram such as this, the branch lengths are not drawn to any scale of similarity.]]
  
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
+
Your species may not be included in this cladogram, but you can easily calculate your own with the following procedure:
*Save your '''model''' coordinates to your harddisk and visualize the structure in VMD. (Alternatively, copy and save the coordinates linked to the  [[Assignment_4_fallback_data|'''Fallback Data file''']] to your harddisk.) Make an informative stereo view that shows the general orientation of the helix-turn-helix motif and the "wing", and paste it into your assignment.
 
  
* Discuss briefly which parts of the model may be unreliable and color these (if any) distinctly in your submitted image.
+
<div style="padding: 5px; background: #DDDDEE;">
 +
#Access the [http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=taxonomy NCBI taxonomy database Entrez query page].
 +
#Edit the list of reference species below to include your species and paste it into the form.
  
(1 mark)
+
"Emericella nidulans"[Scientific Name] OR
 +
"Candida albicans"[Scientific Name] OR
 +
"Neurospora crassa"[Scientific Name] OR
 +
"Saccharomyces cerevisiae"[Scientific Name] OR
 +
"Schizosaccharomyces pombe"[Scientific Name] OR
 +
"Ustilago maydis"[Scientific Name]
  
 +
#Next, as '''Display''' option, select '''Common Tree'''.
 +
#Then select the '''phylip tree''' option and click '''save as''' to save the tree in Newick format.
 +
#The output can be edited, and visualized in any program that reads Newick trees.
 
</div>
 
</div>
&nbsp;<br>
 
&nbsp;<br>
 
  
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
 
 
==(4) The DNA ligand==
 
</div>
 
&nbsp;
 
&nbsp;
 
  
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
  
===(4.1) Finding a similar protein-DNA complex (1 mark)===
+
===(2.2) Visualizing the APSES domain Phylogenetic Tree===
 
</div>
 
</div>
&nbsp;<br>
 
  
One of the really interesting questions we can discuss with reference to our model is how sequence variation might be converted into changing DNA recognition sites, and then lead to changed cognate DNA binding sequences. But in order to address this, we would need to add a plausible model for how DNA is bound to APSES domains.
 
  
Since there is currently no software available that would accurately model such a complex from first principles, we will base a model of  a bound complex on homology modeling as well. This means we need to find a similar structure for which the position of bound DNA is known, then superimpose that structure with our model. This places the DNA molecule into the spatial context of the model we are studying. However, you may remember from the third assignment that the APSES domains in fungi seem to be a relatively small family. And there is no structure available of an APSES domain-DNA complex. How can we find a coordinate set of a strcturally similar protein-DNA complex?
+
Once Phylip is done calculating the tree, the tree in a text format will be contained in the Phylip <code>outfile</code> - the documentation of what the program has done. Open this textfile for a first look. The tree is complicated and it can look confusing at first. The tree in Newick format is contained in the Phylip file <code>outtree</code>. Visualize it as follows:
  
Remember that homologous sequences can have diverged to the point where their sequence similarity is no longer recognizable, however their structure may be quite well conserved. Thus if we could find similar structures in the PDB, these might provide us with some plausible hypotheses for how DNA is bound by APSES domains. We thus need a tool similar to BLAST, but not for the purpose of sequence alignment, but for structure alignment. A kind of BLAST for structures. Just like with sequence searches, we might not want to search with the entire protein, if we are interested in is a subdomain that binds to DNA. Attempting to match all structural elements in addition to the ones we are actually interested in is likely to make the search less specific - we would find false positives that are similar to some irrelevant part of our structure. However, defining too small of a subdomain would also lead to a loss of specificity: in the extreme it is easy to imagine that the search for e.g. a single helix would retrieve very many hits that would be quite meaningless.
+
<div style="padding: 5px; background: #DDDDEE;">
 +
#Open <code>outtree</code> in a texteditor and copy the tree.
 +
#Visualize the tree in alternative representations:
 +
##Navigate to the [http://www.proweb.org/treeviewer/ Proweb treeviewer], paste and visualize your tree.
 +
##Navigate to the [http://www.trex.uqam.ca/index.php?action=newick&project=trex Trex-online Newick tree viewer] for an alternative view. Visualize the tree as a phylogram. You can increase the window height to keep the labels from overlapping.
 +
##In your Jalview window, choose '''File &rarr; Load associated Tree''' and load the Phylip <code>outtree</code> file. You can click into the tree-window to show which clades branch off at what level - it should be obvious that you can identify three major subclades.
 +
##Study the tree: understand what you see and what you would have expected.  
 +
</div>
  
At the '''NCBI''', [http://www.ncbi.nlm.nih.gov/Structure/VAST/vast.shtml VAST] is provided as a search tool for structural similarity search.  
+
Here are two principles that will help you make sense of the tree.
  
At the '''EBI''' there are a number of very well designed structure analysis tools linked off the [http://www.ebi.ac.uk/Tools/structural.html '''Structural Analysis''' page]. As part of its MSD Services, [http://www.ebi.ac.uk/msd-srv/ssm/ '''MSDfold'''] provides a convenient interface for structure searches.
 
  
However we have also read previously that the APSES domains are members of a much larger superfamily, the "winged helix" DNA binding domains , of which hundreds of structures have been solved.
+
A: '''A gene that is present in an ancestral species is inherited in all descendant species'''. The gene has to be observed in all OTUs, unless its has been lost (which is a rare event).
 
 
&nbsp;<br>
 
  
[[Image:A5_Mbp1_subdomain.jpg|frame|none|Stereo-view of a subdomain within the 1MB1 structure that includes residues 36 to 76. The color gradient ramps from blue (36) to green (76) and the "wing" is clearly seen as the green pair of beta-strands, extending to the right of the helix-turn-helix motif.]]
+
B: '''Paralogous genes in an ancestral species should give rise to monophyletic subtrees for each of the paralogues, in all descendants'''; this means: if the LCA of a branch has e.g. three genes, we would expect three copies of the species cladogram below this branchpoint, one for each of these genes. Each of these subtrees should recapitulate the reference phylogenetic tree of the species, up to the branchpoint of their LCA.
  
&nbsp;<br>
 
  
APSES domains represent one branch of the tree of helix-turn-helix (HTH) DNA binding modules. (A recent review on HTH proteins is linked from the resources section at the bottom of this page). Winged Helix domains typically bind their cognate DNA with a "recognition helix" which precedes the beta hairpin and binds into the major groove; additional stabilizing interactions are provided by the edge of a beta-strand binding into the minor groove. This is good news: once we have determined that the APSES domain is actually an example of a larger group of transcription factors, we can compare our model to a structure of  a protein-DNA complex. CATH does not provide information on complexes, but we can search the PDB with CATH codes in the following way:
+
With these two simple principles (you should draw them out on a piece of paper if they do not seem obvious to you), you can probably pry your tree apart quite nicely. A few colored pencils and a printout of the tree will help.
  
* Access [http://cathwww.biochem.ucl.ac.uk/cgi-bin/cath/GotoCath.pl?cath=1.10.10.10 CATH domain 1.10.10.10].
 
* Navigate to the [http://www.pdb.org/ PDB home page] and follow the link to [http://www.pdb.org/pdb/search/advSearch.do Advanced Search]
 
* In the options menu for "Choose a Query Type" select Structure Features &rarr; CATH classification. A window will open that allows you to navigate down through the CATH tree. The interface is awkward because it does not display the actual CATH codes along with the class names, but you can view the class names on the CATH page linked above. Click on '''the triangle icons''' before "Mainly Alpha"&rarr;"Orthogonal Bundle"&rarr;"ARC repressor mutant, subunit A" then click on the link to "winged helix repressor DNA binding domain". As of this writing, this subquery matches 295 structures.
 
* Click on the (+) button behind the subquery to add an additional query. Select the option "Structure Summary"&rarr;"Molecule / Chain type". In the option menus that pop up, select "Contains Protein &rarr; Yes",  "Contains DNA &rarr; Yes""Contains RNA &rarr; Ignore". This selects files that contain Protein-DNA complexes.
 
* Check the box below this subquery to "Remove Similar Sequences at 90% identity" and click on "Evaluate Query". As of this writing, seventy complexes were returned.
 
* In the left-hand menu, under the Tabulate section, click on the "Collage" function to display icons of the structure files. This is a fast way to obtain an overview of the structures that have been returned. First of all you may notice that in fact not all of the structures are really different, despite selecting only to retrieve dissimilar sequences. This appears to be a deficiency of the algorithm. But you can also easily recognize how the recognition helix inserts into the major groove of most of the structures that were returned (at least those where the domain is not a very small part of a much larger complex). There is one exception: the structure 1DP7 shows how the human RFX1 protein binds DNA in a non-canonical way. We shall use structural superposition of your homology model and two of the winged-helix proteins to decide which mode of DNA binding seems to be more plausible for Mbp1 homologues.
 
  
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
+
&nbsp;
* Follow the procedure outlined above, from a CATH entry page up to viewing a Collage (or alternatively a tabular view) of the retrieved coordinate files. You can be maximally concise documenting the procedure I have defined above, but do spend a bit of time to understand the key elements of the PDB's advanced search interface.
+
&nbsp;
 
 
(1 mark)
 
</div>
 
  
  
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
  
===(4.2) Preparation and superposition of a canonical complex (1 mark)===
+
===(2.1) The Cenancestor's APSES Domains===
 
</div>
 
</div>
&nbsp;<br>
 
  
The structure we shall use as a reference for the canonical binding mode is the Elk-1 transcription factor.
+
Refer to your tree for the following tasks. (Please remember to include your tree in your Assignment submission - it is a result of your computational experiment. Its easiest to copy/paste the tree from the Phylip outfile, rather than copying an image from a Tree viewer). Be specific in your discussion, i.e. refer to specific branchpoints (branchpoints are numbered in the Phylip output) and OTU or gene names in your analysis (see the example below).  
  
[[Image:A5_canonical_wHTH.jpg|frame|none|Stereo-view of the canonical DNA binding mode of the Winged Helix domain family. Shown here is the Elk-1 transcription factor - an ETS DNA binding domain - in complex with a high-affinity binding site (1DUX). Note how the "recognition helix" inserts into the major groove of the DNA molecule. The color gradient ramps from blue (34) to green (84). Note how the first helix of the "helix-turn-helix" architecture serves only to position the recognition helix and makes few interactions by itself.]]
 
  
The 1DUX coordinate-file contains two protein domains and two B-DNA dimers in one asymmetric unit. For simplicity, let's delete the second copy.
+
<div style="padding: 5px; background: #DDDDEE;">
 
+
*Consider how many APSES domain proteins the fungal cenancestor appears to have possessed and what evidence you see in the tree that this is so.  
* Access the PDB and navigate to the 1DUX structure explorer page. Download the coordinates to your computer.
 
* Open the coordinate file in a text-editor and delete the coordinates for chains <code>D</code>,<code>E</code> and <code>F</code>; you may also delete all <code>HETATM</code> records and the <code>MASTER</code> record. Save the file with a different name, e.g. 1DUX_monomer.pdb .
 
* Open VMD and load your homology model. Turn off the axes, display the model as a Tube representation in stereo, and color it by Index. Then load your edited 1DUX file, display this coordinate set in a tube representation as well, and color it by ColorID in some color you like. It is important that you can distinguish easily which structure is which
 
* You could use the Extensions&rarr;Analysis&rarr;RMSD calculator interface to superimpose the two strutcures '''IF''' you would know which residues correspond to each other. Sometimes it is useful to do exactly that: define exact correspondences between residue pairs and superimpose according to these selected pairs. For our purpose it is much simpler to use the Multiseq tool (and the structures are simple and small enough that the STAMP algorithm for structural alignment can define corresponding residue pairs automatically). Open the '''multiseq''' extension window, select the check-boxes next to both protein structures, and open the '''Tools&rarr;Stamp Structural Alignment''' interface.
 
* In the "'Stamp Alignment Options'" window, check the radio-button for ''Align the following ...'' '''Marked Structures''' and click on '''OK'''.
 
* In the '''Graphical Representations''' window, double-click on all "NewCartoon" representations for both molecules, to undisplay them.
 
* You should now see a superimposed tube model of your homology model and the 1DUX protein-DNA complex. You can explore it, display side-chains etc. and study some of the details of how a transcription factor recognizes and binds to its cognate DNA sequence. However, remember that the model's side-chain orientations have not been experimentally determined but inferred from the template, and that the template's strcture was determined in the absence of bound ligand.
 
 
 
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
 
* Orient and scale your superimposed structures so that their structural similarity is apparent, and the recognition helix can be clearly seen inserting into the DNA major groove. Paste a copy of your image into your assignment. Remark briefly on which parts of the structure appear to superimpose best.  Note whether this orientation of a B-DNA double-helix is a plausible model for DNA binding of your Mbp1 orthologue.
 
 
 
(1 mark)
 
 
</div>
 
</div>
&nbsp;<br>
 
&nbsp;
 
  
  
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
  
===(4.2) Preparation and superposition of a non-canonical complex (1 mark)===
+
===(2.2) Unraveling your organism's APSES domains (2 marks)===
 
</div>
 
</div>
 +
 +
&nbsp;<br>
 
&nbsp;<br>
 
&nbsp;<br>
 +
<div style="padding: 5px; background: #FFCC99;">
 +
;Analysis (2 marks)
  
The structure displaying a non-canonical complex between a winged-helix domain and its cognate DNA binding site is the human Regulatory Factor X.
+
Assume that the cladogram for fungi that I have given above is correct, and that the mixed gene tree you have calculated is fundamentally correct in its overall arrangement but may have local inaccuracies due to the limited resolution of the method. You have identified the APSES domain genes of the fungal cenancestor above. Apply the expectations we have stated above to discuss briefly through what sequence of duplications and/or gene loss your organism has ended up with the APSES domains it possesses today. Make specific reference to the cladogram of species and note in particular in case some of your sequences appear to have been placed into regions of the tree where they don't seem to belong. Also note which branchpoints in the evolutionary history of your sequences correspond to speciations and which ones to duplications.
 
 
[[Image:A5_non-canonical_wHTH.jpg|frame|none|Stereo-view of a non-canonical wHTH-DNA complex, discovered in with the stucture of human Regulatory Factor X (hRFX) binding its cognate X-box DNA sequence (1DP7). Note how the helix that coressponds to the recogition helix in the canonical domain lies across the minor groove whereas the beta-"wing" inserts into the major groove. The color gradient ramps from blue (18) to green (68).]]
 
 
 
The 1DP7 coordinate-file contains only one protein domain and only one B-DNA monomer in its asymmetric unit. This is a file for which we have to generate ''biological unit'' coordinates! Then, for simplicity we will delete the second protein monomer. As you know, there are at least two systems that make the so-called biological units available: the PDB itself, through the Biological Unit file that is accessible via the "Download Files" section  on any Structure Explorer page, and the EBI through the PQS service. '''How''' the biological units are stored is subtly different for both cases and for our purpose this small difference is important. The PDB generates additional chins as copies of the original and delineates them with <code>MODEL</code>, <code>ENDMDL</code> records, just like in a multi-structure NMR file. The chain IDs and the atom numbers are the same as the original. The EBI's PQS service creates copies that have distinct atomnumbers and chain IDs. The difference is that the PDB file thus '''contains the same molecule in two different orientations''', wheras the PQS file contains '''two independent molecules'''. This is an important difference when it comes to selecting residues, visualizing and superimposing structures. For VMD, the PQS way of doing things is the right way to go, since by default only the first <code>MODEL</code> will be displayed if several are available.
 
 
 
* Access the [http://pqs.ebi.ac.uk/ '''EBI PQS server'''], enter 1DP7 into the '''PDBidcode''' form field and click on '''Submit'''.
 
* On the results page, click on the link under '''1dp7_0''', which is the unique suggestion for a biological unit that the server has identified.
 
* On the PQS OUTPUT page that is retrieved, click on the '''1dp7.mmol''' link, this will load the PDB formatted coordinate file.
 
* Save the coordinates as 1DP7_complex.pdb (or some other name that makes sense to you), open it in a text editor, delete the <code>HETATM</code> records from the end and the entire chain "B". Also make sure not to delete any of the <code>TER</code> records for chains "D", "P" or "A". Save the file.
 
* In the multiseq window, choose File&rarr;Import Data, '''Browse...''' to your 1DP7_complex file, select it and click on '''Open'''. Click '''OK''' to load the file.
 
* Mark all three protein chains by selecting the checkbox next to thier name and again run the STAMP structural alignment.
 
* In the graphical representations window, double-click again on all cartoon representations that multiseq has generated to undisplay them, undisplay also the Tube representation of 1DUX, create a Tube representatrion for 1DP7, and select a Color by ColorID (a differnet color you like). The resulting scene should look similar to the one you have created above, only with 1DP7 in place of 1DUX and colored differently.
 
  
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
 
* Orient and scale your superimposed structures so that their structural similarity is apparent, the orientation is similar to the scene generated above and the 1DP7 "wing" can be clearly seen inserting into the DNA major groove. Paste a copy of your image into your assignment. Remark briefly on which parts of the structure appear to superimpose best.  Note whether this orientation of a B-DNA double-helix is a plausible model for DNA binding of your Mbp1 orthologue.
 
  
(1 mark)
+
Note: A common confusion about cenancestral genes arises from the fact that by far not all expected genes are present in the OTUs. Some will have been lost, some will have been incorrectly annotated in their genome (frameshifts!) and not been found with PSI-BLAST, some may have been missed by you. In general you have to ask: '''given the species represented in a subclade, what is the last common ancestor of that branch'''? The expectation is that '''all''' descendants of that ancestor should be represented in that branch '''unless''' one of the above reasons why a gene might be absent would apply.
</div>
 
&nbsp;<br>
 
  
<div style="padding: 5px; background: #E9EBF3;  border:solid 1px #AAAAAA;">
 
  
===(4.3) Interpretation (2 marks)===
+
If your species does not have all the genes you would expect it to have inherited from its ancestors, you MUST note that fact and attempt to explain it.  
 
</div>
 
</div>
&nbsp;<br>
 
  
In your previous assignment, you have commented on conservation patterns in Mbp1 orthologues. You can refer back to your last results (easier to do), or you can import the APSES domain alignment for Mbp1 proteins and again color by conservation (easier to study) to briefly discuss the following question.
 
  
&nbsp;<br><div style="padding: 5px; background: #DDDDEE;">
+
For example the following discusion for ''Saccharomyces cerevisiae'' would be sufficient for full marks:
* Considering the conservation patterns for Mbp1 orthologues, and assuming that all these orthologues bind DNA in a similar way, which model appears to be more plausible for protein-DNA interactions in APSES domains? Is it the canonical, or the non-canonical binding mode? Discuss briefly what you would expect to find and how this relates to your observations. Distinguish clearly between experimental evidence, computational inference and empirical hypothesis. You are of course welcome to paste detail views (stereo !) of particular sidechains, or surfaces etc. if this helps your arguments. Sometimes a picture is worth many words. But this is not a requirement, we are more interested in evidence-based reasoning than in the form of the presentation.
+
:(Numbers refer to branchpoints of the mixed gene tree, letters to branchpoints of the species tree). I have found five homologues to ''Saccharomyces cerevisiae'' Mbp1 and included them in the mixed gene tree. Two subclades are well defined, and contain all current species, they branch from 41 (Xbp1) and 50 (Sok2/Phd1). The subclade below 6 includes Mbp1 orthologues as well as Swi4 orthologues that do not appear well resolved. Considering only species below the ''saccharomycetales'' branchpoint, I postulate a duplication at that branchpoint that gave rise to yeast Mbp1 and Swi4 since the respective branches contain representatives from all fungi that descended from that branch. There is no good support for the idea that the cenancestor had a Swi4 paralogue. Therefore the cenancestor most likely posessed two paralogues: Mbp1, and Sok2. ''Saccharomyces cerevisiae'' has one gene in each of the major subclades, there is no gene loss. It also has an additional paralogue to Sok2: the Phd1 gene that duplicated at branchpoint 3.  
  
(2 marks)
 
</div>
 
&nbsp;<br>
 
&nbsp;<br>
 
  
 
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
 
<div style="padding: 5px; background: #BDC3DC;  border:solid 1px #AAAAAA;">
  
==(5) Summary of Resources==
+
==(3) Summary of Resources==
 
</div>
 
</div>
 
&nbsp;<br>
 
&nbsp;<br>
  
;Links and background reading
+
;Links
 +
:* [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/Baldauf_2003_PhylogenyTutorial.pdf '''Review (PDF, restricted)''' Sandra Baldauf: Phylogeny for the Faint of Heart]
 +
:* [http://evolution.genetics.washington.edu/phylip.html '''PHYLIP''' home page]
  
:* [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/Peitsch_2002_UseOfModels.pdf '''Review (PDF, restricted)''' Manuel Peitsch on Homology Modeling]
+
;Sequences
:* [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/Aravind_2005_HTHdomains.pdf '''Review (PDF, restricted)''' Aravind ''et al.'' Helix-turn-helix domains]
+
:* [[Reference APSES domains|Reference APSES domains page]]
:* [http://biochemistry.utoronto.ca/undergraduates/courses/BCH441H/restricted/2000_Gajiwala_WingedHelixDomains.pdf '''Review (PDF, restricted)''' Gajiwala &amp; Burley, winged-Helix domains]
 
:* [[Organism_list_2007|Assigned Organisms]]
 
:* [http://www.wwpdb.org/documentation/format23/v2.3.html '''PDB file format'''] (see the Coordinate Section if you are unsure about chain identifiers)
 
:* [http://en.wikipedia.org/wiki/Structural_alignment Wikipedia on '''Structural Superposition'''] <small>(although the article is called "Structural Alignment")</small>
 
  
;[[Assignment_4_fallback_data|'''Fallback Data page''']]
+
<div style="padding: 5px; background: #D3D8E8;  border:solid 1px #AAAAAA;">
 
+
[End of assignment]
;Alignments
+
</div>
:* [[APSES_domains_MUSCLE|APSES domains MUSCLE aligned]]
 
 
 
&nbsp;
 
&nbsp;
 
  
{{Template:Assignment_Footer}}
+
If you have any questions at all, don't hesitate to mail me at [mailto:boris.steipe@utoronto.ca boris.steipe@utoronto.ca] or post your question to the [mailto:bch441_2011@googlegroups.com Course Mailing List]

Latest revision as of 23:34, 21 September 2012

Note! This assignment is currently active. All significant changes will be announced on the mailing list.

 
 


   

Assignment 4 (last: 2011) - Phylogenetic Analysis

Introduction  

Nothing in Biology makes sense except in the light of evolution.
Theodosius Dobzhansky

... but does evolution make sense in the light of biology?

As we have seen in the previous assignments, the Mbp1 transcription factor has homologues in all other fungi, yet there is not always a clear one-to-one mapping between members of a family in distantly related species. It appears that various systems of APSES domain transcription factors have evolved independently. Of course this bears directly on our notion of function - what it means to say that two genes in different organisms have the "same" function. In case two organisms both have an orthologous gene for the same, distinct function, saying that the function is the same may be warranted. But what if that gene has duplicated in one species, and the two paralogues now perform different, related functions in one organism? Theses two are still orthologues to the other species, but now we expect functionally significant residues to have adapted to the new role of one paralogue. In order to be able to even ask such questions, we need to make the evolutionary history of gene families explicit. This is the domain of phylogenetic analysis. We can ask questions like: how many paralogues did the cenancestor of a clade possess? Which of these underwent additional duplications in the phylogenesis of the organism I am studying? Did any genes get lost? And - adding additional biological insight to the picture - did the observed duplications lead to the "invention" of new biological systems? When was that? And perhaps even: how did the species benefit from this event?


We will develop this kind of analysis in this assignment. In the previous assignment you have established which gene in your species is the reciprocally most closely related orthologue to yeast Mbp1 and you have identified the full complement of APSES domain genes in your assigned organism. In this assignment, we will analyse these genes' evolutionary relationship and compare it to the evolutionary relationship of all fungal APSES domains. The goal is to define families of related transcription factors and their evolutionary history.

A number of excellent tools for phylogenetic analysis exist; general purpose packages include the (free) PHYLIP package and the (commercial) PAUP package. Specialized tools for tree-building include Treepuzzle or Mr. Bayes. This assignment is constructed around programs that are available in PHYLIP, however you are welcome to use other tools that fulfill a similar purpose if you wish. In this field, researchers consider trees that have been built with ML (maximum likelihood) methods to be more reliable than trees that are built with parsimony methods, or distance methods such as NJ (Neighbor Joining). However ML methods are also much more compute-intensive. Just like with multiple sequence alignments, some algorithms will come closer to guessing the truth and others will not and usually it is hard to tell which is the more trustworthy of two diverging results. The prudent researcher tries out alternatives and forms her own opinion. Specifically, we may usually assume results that converge when computed with different algorithms, to be more reliable than those that depend strongly on a particular algorithm, parameters, or details of input data.

However: regarding algorithm and resources, we will take a shortcut in this assignment (something you should not do in real life). We will assume that the tree the algorithm constructs is correct. In "real life" you would establish its reliability with a bootstrap procedure: repeat the tree-building a hundred times with partial data and see which branches and groupings are robust and which depend on the details of the data. In this assignment, we should simply acknowledge that bifurcations that are very close to each other have not been "resolved" and be appropriately cautious in our inferences. In phylogenetic analysis, not all lines a program draws are equally trustworthy. Don't take the trees as a given fact just because a program suggests this. Look at the evidence, include independent information where available, use your reasoning, and analyse the results critically. As you will see, there are some facts that we know for certain: we know which species the genes we have sequenced come from, and we can (usually) make good assumptions about the relationship of the species themselves - the history of speciation events that underlies all evolution of genes. This is extremely helpful information for our work.

Introduction: Tasks

For this assignment, we start from the APSES domains you have collected previously. You will align these domains with a set of reference domains and edit the alignment to make it suitable for phylogenetic analysis, using Jalview. Then you will construct a phylogenetic tree and interpret the tree. The goal is to identify orthologues and paralogues.

In case you want to review concept of trees, clades, LCAs, OTUs and the like, I have linked an excellent and very understandable introduction-level article on phylogenetic analysis (pdf) here and to the resource section at the bottom of this page.

 

Preparation, submission and due date

Read carefully.
Be sure you have understood all parts of the assignment and cover all questions in your answers! Sadly, we always get assignments back in which important aspects have simply overlooked marks unnecessarily. If you did not notice that the above did not make sense, you are reading what you expect, not what is written.

Review the guidelines for preparation and submission of BCH441 assignments.

The due date for the assignment is Monday, November 28 at 12:00 in the morning.

   

Your documentation for the procedures you follow in this assignment will be worth 1 mark.

   

(1) Preparations

   

(1.1) Preparing Input Files

 

For this assignment, we start from the multiple sequence alignments we have constructed previously. We will edit the alignment to make it suitable for phylogenetic analysis. We will construct a phylogenetic tree and we will analyse the tree.

Introduction: Principle

In order to use molecular sequences for the construction of phylogenetic trees, you have to build a multiple alignment first, then edit it. This is important: all rows of sequences have to contain the exact same number of characters and to hold aligned characters in corresponding positions. Phylogeny programs are not meant to revise an alignment but to analyze evolutionary relationships, after the alignment has been determined. The program's inferences are made on a column-wise basis and if your columns contain data from unrelated positions, the inferences are going to be questionable.

The result of the tree construction is a decision about the most likely evolutionary relationships. Fundamentally, tree-construction programs decide which sequences had common ancestors.


Distance based phylogeny programs start by using sequence comparisons to estimate evolutionary distances:

  • they apply a model of evolution such as a mutation data matrix, to calculate a score for each pair of sequences,
  • this score is stored in a "distance matrix" ...
  • ... and used to estimate a tree that groups sequences with close relationships together. (e.g. by using an NJ, Neigbor Joining, algorithm).

They are fast, can work on large numbers of sequences, but are less accurate if genes evolve at different rates.


Parsimony based phylogeny programs build a tree that minimizes the number of mutation events that are required to get from a common ancestral sequence to all observed sequences. They take all columns into account, not just a single number per sequence pair, as the Distance Methods do. For closely related sequences they work very well, but they construct inaccurate trees when they can't make good estimates for the required number of sequence changes.


ML, or Maximum Likelihood methods attempt to find the tree for which the observed sequences would be the most likely under a particular evolutionary model. They are based on a rigorous statistical framework and yield the most robust results. But they are also quite compute intensive and a tree of the size that we are building in this assignment is a challenge for the resources of common workstation (runs about an hour on my computer). If the problem is too large, one may split a large problem into smaller, obvious subtrees (e.g. analysing orthologues as a group, only including a few paralogues for comparison) and then merge the smaller trees; this way even very large problems can become tractable.

ML methods suffer less from "long-branch attraction" - the phenomenon that weakly similar sequences can be grouped inappropriately close together in a tree due to spuriously shared differences.


Clearly, in order for tree-estimation to work, one must not include fragments of sequence which have evolved under a different evolutionary model as all others, e.g. after domain fusion, or after accommodating large stretches of indels. Thus it is appropriate to edit the sequences and pare them down to a most characteristic subset of amino acids. The goal is not to be as comprehensive as possible, but to input those columns of aligned residues that will best represent the true phylogenetic relationships between the sequences.

Introduction: Gaps

Gaps are a real problem here, as usual. Strictly speaking, the similarity score of an alignment program as well as the distance score of a phylogeny program are not calculated for an ordered sequence, but for a sum of independent values, one for each aligned columns of characters. The order of the columns does not change the score. However in an optimal sequence alignment with gaps, this is no longer strictly true since a one-character gap creation has a different penalty score than a one-character gap extension! Most alignment programs use a model with a constant gap insertion penalty and a linear gap extension penalty. This is not rigorously justified from biology, but parametrized (or you could say "tweaked") to correspond to our observations. However, most phylogeny programs, (such as the programs in PHYLIP) do not work in this way. PHYLIP strictly operates on columns of characters and treats a gap character just like a residue with the one letter code "-". Thus gap insertion- and extension- characters get the same score. For short indels, this underestimates the distance between pairs of sequences, since any evolutionary model should reflect the fact that gaps are much less likely than point mutations. If the gap is very long though, all events are counted individually as many single substitutions (rather than one lengthy one) and this overestimates the distance. And it gets worse: long stretches of gaps can make sequences appear similar in a way that is not justified, just because they are identical in the "-" character. It is therefore common and acceptable to edit gaps in the alignment and delete all but one or two columns of gapped sequence, or to remove such columns altogether.


Introduction: The outgroup

To analyse phylogenetic trees it is useful (and for some algorithms required) to define an outgroup, a sequence that presumably diverged from all other sequences in a clade before they split up among themselves. Wherever the outgroup inserts into the tree, this is the root of the rest of the tree. And whenever a molecular clock is assumed, the branching point that connects the outgroup can be assumed to be the oldest divergence event. I have defined an outgroup sequence and added it to the reference APSES domains page. The procedure is explained in detail on that page.

>gi|301025594|ref|ZP_07189117.1| KilA-N domain protein [Escherichia coli MS 69-1]
MTSFQLSLISREIDGEIIHLRAKDGYINATSMCRTAGKLLSDYTRLKTTQEFFDELSRDMGIPISELIQS
FKGGRPENQGTWVHPDIAINLAQWLSPKFAVQVSRWVREWMSGERTTAEMPVHLKRYMVNRSRIPHTHFS
ILNELTFNLVAPLEQAGYTLPEKMVPDISQGRVFSQWLRDNRNVEPKTFPTYDHEYPDGRVYPARLYPNE
YLADFKEHFNNIWLPQYAPKYFADRDKKALALIEKIMLPNLDGNEQF

E. coli KilA-N protein. Residues that do not align with APSES domains are shown in grey.

Preparing APSES sequences
  1. Navigate to the reference APSES domains page and copy the sequences.
  2. Open Jalview, select File → Input Alignment → from Textbox and paste the sequences into the textbox.
  3. Add the APSES domain sequences from your species that you have defined in the previous assignment.
  4. When all the sequences are present, click on New Window.
  5. In Jalview, select Web Service → Alignment → MAFFT Multiple Sequence Alignment. The alignment is calculated in a few minutes and displayed in a new window.
  6. Choose any colour scheme and add Colour → by Conservation. Adjust the slider left or right to see which columns are highly conserved.
  7. Save the alignment as a Jalview project before editing it for phylogenetic analysis. You may need it again.


Introduction: Alignment editing for phylogenetic reconstruction

In practice, follow the fundamental principle that all characters in a column should be related by homology. This implies the following rules of thumb:

  • Remove all stretches of residues in which the alignment appears ambiguous (not just highly variable, but ambiguous regarding the aligned positions).
  • Remove all frayed N- and C- termini, especially regions in which not all sequences that are being compared appear homologous and that may stem from unrelated domains.
  • Remove all gapped regions that appear to be alignment artefacts due to inappropriate input sequences.
  • Remove all but approximately one column from gapped regions in those cases where the presence of several related insertions suggest that the indel is real, and not just an alignment artefact. (Some researchers simply remove all gapped regions).
  • Remove sections N- and C- terminal of gaps where the alignment appears questionable.
  • Also, consider that neither residues that are completely different between all species, nor residues that are completely conserved are informative for relationship distances.
  • If your sequences are too long, your tree calculations may run out of memory. 60-80 aligned residues should be plenty and if the sequences fit on a single line you will save yourself potential trouble with block-wise vs. interleaved input.If you do run out of memory try removing columns of sequence.
  • Move the KilA-N outgroup sequence to the first line of your alignment, since this is where PHYLIP will look for it by default.


(Possible) steps in editing a multiple sequence alignment towards a PHYLIP input file. a: raw alignment (CLUSTAL format); b: sequences assembled into single lines; c: columns to be deleted highlighted in red - 1, 3 and 4: large gaps; 2: uncertain alignment and 5: frayed C-terminus: both would put non-homologous characters into the same column; d: input data for PHYLIP: names for sequences must not be longer than 10 characters, the first line must contain the number of sequences and the sequence length. PHYLIP is very picky about incorrectly formatted input, read the PHYLIP sequence format guide.
Once you are satisfied with your editing, proceed as follows
  1. Download the PHYLIP package from the Phylip homepage and install it on your computer.
  2. Prepare a PHYLIP input file from your Jalview alignment. The simplest way to achieve this appears to be:
    1. In Jalview, use File → Output to Textbox→FASTA, then Edit→Select All and Edit→copy the sequences.
    2. In a browser, navigate to the Readseq sequence conversion service.
    3. Paste your sequences into the form and choose Phylip as the output format. Click on submit.
    4. Save the resulting page as a text file in the directory where the phylip executables reside on your computer. Give it some useful name such as All-APSES_domains.phy.
  3. Make a copy of that file and name it infile. Note: make sure that your Microsoft Windows operating system does not silently append the extension ".txt" to your file. It should be called "infile", nothing else and you should never, never, ever permit your operating systems to slyly hide file extensions from you when it displays filenames. You have been warned.


(1.2) Calculating a Tree

 
 

  • Use the proml program of PHYLIP (protein sequences, maximum likelihood tree) to calculate a phylogenetic tree. Use the default parameters except that you must change option S: Speedier but rougher analysis? to No - your analysis should not sacrifice accuracy for speed. The calculation will take a while.

 
 

(2) Analysis (2 marks)

I have constructed a cladogram for the species we are analysing, based on data published for 1551 fungal ribosomal sequences. Such reference tres from rRNA data are a standard method of phylogenetic analysis, supported by the assumption that rRNA sequences are monophyletic and have evolved under comparable selective pressure in all species.

Cladogram of fungi studied in the assignments. This cladogram is based on small subunit ribosomal rRNA sequences, and largely follows Tehler et al. (2003) Mycol Res. 107:901-916. Even though many details of fungal phylogeny remain unresolved, the branches shown here individually appear to have strong support. In a cladogram such as this, the branch lengths are not drawn to any scale of similarity.

Your species may not be included in this cladogram, but you can easily calculate your own with the following procedure:

  1. Access the NCBI taxonomy database Entrez query page.
  2. Edit the list of reference species below to include your species and paste it into the form.
"Emericella nidulans"[Scientific Name] OR
"Candida albicans"[Scientific Name] OR
"Neurospora crassa"[Scientific Name] OR
"Saccharomyces cerevisiae"[Scientific Name] OR
"Schizosaccharomyces pombe"[Scientific Name] OR
"Ustilago maydis"[Scientific Name]
  1. Next, as Display option, select Common Tree.
  2. Then select the phylip tree option and click save as to save the tree in Newick format.
  3. The output can be edited, and visualized in any program that reads Newick trees.


(2.2) Visualizing the APSES domain Phylogenetic Tree


Once Phylip is done calculating the tree, the tree in a text format will be contained in the Phylip outfile - the documentation of what the program has done. Open this textfile for a first look. The tree is complicated and it can look confusing at first. The tree in Newick format is contained in the Phylip file outtree. Visualize it as follows:

  1. Open outtree in a texteditor and copy the tree.
  2. Visualize the tree in alternative representations:
    1. Navigate to the Proweb treeviewer, paste and visualize your tree.
    2. Navigate to the Trex-online Newick tree viewer for an alternative view. Visualize the tree as a phylogram. You can increase the window height to keep the labels from overlapping.
    3. In your Jalview window, choose File → Load associated Tree and load the Phylip outtree file. You can click into the tree-window to show which clades branch off at what level - it should be obvious that you can identify three major subclades.
    4. Study the tree: understand what you see and what you would have expected.

Here are two principles that will help you make sense of the tree.


A: A gene that is present in an ancestral species is inherited in all descendant species. The gene has to be observed in all OTUs, unless its has been lost (which is a rare event).

B: Paralogous genes in an ancestral species should give rise to monophyletic subtrees for each of the paralogues, in all descendants; this means: if the LCA of a branch has e.g. three genes, we would expect three copies of the species cladogram below this branchpoint, one for each of these genes. Each of these subtrees should recapitulate the reference phylogenetic tree of the species, up to the branchpoint of their LCA.


With these two simple principles (you should draw them out on a piece of paper if they do not seem obvious to you), you can probably pry your tree apart quite nicely. A few colored pencils and a printout of the tree will help.


   


(2.1) The Cenancestor's APSES Domains

Refer to your tree for the following tasks. (Please remember to include your tree in your Assignment submission - it is a result of your computational experiment. Its easiest to copy/paste the tree from the Phylip outfile, rather than copying an image from a Tree viewer). Be specific in your discussion, i.e. refer to specific branchpoints (branchpoints are numbered in the Phylip output) and OTU or gene names in your analysis (see the example below).


  • Consider how many APSES domain proteins the fungal cenancestor appears to have possessed and what evidence you see in the tree that this is so.


(2.2) Unraveling your organism's APSES domains (2 marks)

 
 

Analysis (2 marks)

Assume that the cladogram for fungi that I have given above is correct, and that the mixed gene tree you have calculated is fundamentally correct in its overall arrangement but may have local inaccuracies due to the limited resolution of the method. You have identified the APSES domain genes of the fungal cenancestor above. Apply the expectations we have stated above to discuss briefly through what sequence of duplications and/or gene loss your organism has ended up with the APSES domains it possesses today. Make specific reference to the cladogram of species and note in particular in case some of your sequences appear to have been placed into regions of the tree where they don't seem to belong. Also note which branchpoints in the evolutionary history of your sequences correspond to speciations and which ones to duplications.


Note: A common confusion about cenancestral genes arises from the fact that by far not all expected genes are present in the OTUs. Some will have been lost, some will have been incorrectly annotated in their genome (frameshifts!) and not been found with PSI-BLAST, some may have been missed by you. In general you have to ask: given the species represented in a subclade, what is the last common ancestor of that branch? The expectation is that all descendants of that ancestor should be represented in that branch unless one of the above reasons why a gene might be absent would apply.


If your species does not have all the genes you would expect it to have inherited from its ancestors, you MUST note that fact and attempt to explain it.


For example the following discusion for Saccharomyces cerevisiae would be sufficient for full marks:

(Numbers refer to branchpoints of the mixed gene tree, letters to branchpoints of the species tree). I have found five homologues to Saccharomyces cerevisiae Mbp1 and included them in the mixed gene tree. Two subclades are well defined, and contain all current species, they branch from 41 (Xbp1) and 50 (Sok2/Phd1). The subclade below 6 includes Mbp1 orthologues as well as Swi4 orthologues that do not appear well resolved. Considering only species below the saccharomycetales branchpoint, I postulate a duplication at that branchpoint that gave rise to yeast Mbp1 and Swi4 since the respective branches contain representatives from all fungi that descended from that branch. There is no good support for the idea that the cenancestor had a Swi4 paralogue. Therefore the cenancestor most likely posessed two paralogues: Mbp1, and Sok2. Saccharomyces cerevisiae has one gene in each of the major subclades, there is no gene loss. It also has an additional paralogue to Sok2: the Phd1 gene that duplicated at branchpoint 3.


(3) Summary of Resources

 

Links
Sequences

[End of assignment]

If you have any questions at all, don't hesitate to mail me at boris.steipe@utoronto.ca or post your question to the Course Mailing List