We thank members of the O&#8217;Halloran lab for comments on the manuscript. We thank The George Washington University Department of Biological Sciences and Columbian College of Arts and Sciences for Funding to D. O&#8217;Halloran.

1. Basic Local Alignment Search Tool (BLAST): Online Interface
<ol>
	<li>Click on this link to visit the BLAST1 web server at the National Center for Biotechnology Information (NCBI). - <a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">http://blast.ncbi.nlm.nih.gov/Blast.cgi</a>&#160; (Figure 1).</li>
	<li>Input a FASTA formatted text sequence (see Figure 2 for example) into the query box.</li>
	<li>Click the appropriate BLAST program and relevant database or individual species of interest to use in the search and then click &#8220;BLAST&#8221;. 
	Note: FASTA formatted sequence begins with a description line indicated by a &#8220;&#62;&#8221; sign. The description must follow immediately after the &#8220;&#62;&#8221; sign, the sequence (i.e. nucleotides or amino acids) follow the description on the next line. The output from the BLAST search is viewed as HTML, plain text, XML, or hit tables (Text or csv) with the default set to HTML (Figure 3).</li>
</ol>
2. Basic Local Alignment Search Tool (BLAST): Local Executables
<ol>
	<li>Download the latest BLAST command-line BLAST executables from this link: 
	<a href="ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/">ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/</a> -</li>
	<li>em&#62;For PC users: double-click the latest blast win32.exe file and accept the license agreement and click install. 
	Note: The default installation directory is C:\ncbi-blast-2.2.27+.</li>
	<li>Configure the PC environment variable as follows:
	<ol>
		<li>Click the PC &#8220;start&#8221; button, and then right click &#8220;computer&#8221;,</li>
		<li>Click &#8220;Properties&#8221; and in the pop-up click on the &#8220;advanced&#8221; tab</li>
		<li>Click the &#8220;Environment Variables button&#8221; and in the new pop-up click the &#8220;new&#8221; button under the &#8220;User variables for user&#8221; section</li>
		<li>In the pop-up add the variable name &#8220;Path&#8221; and variable value &#8220;C:\ncbi-blast-2.2.27+\bin. 
		Note: the bin directory contains the executable (i.e. blastp,&#160;etc.).</li>
	</ol>
	</li>
	<li>em&#62;For Mac users: Open the Terminal application (to do this just open &#8220;Finder&#8221; and search &#8220;Terminal&#8221; and this will display the &#8220;terminal&#8221; icon). Into the terminal window type: 
	&#62;ftp <a href="ftp://ftp.ncbi.nih.gov">ftp.ncbi.nih.gov</a> 
	Note: can also type the URL used above in the example for PC</li>
	<li>To access the NCBI ftp site type &#8220;anonymous&#8221; for Name and Password, and then type: 
	&#62;cd blast/executables/LATEST</li>
	<li>List the executables by typing: 
	&#62;ls</li>
	<li>Get the latest version by typing the following (or whatever the latest version currently is): 
	&#62;get ncbi-blast-2.2.7-macosx.tar.gz</li>
	<li>Exit the NCBI ftp server site by typing &#8220;exit&#8221;.</li>
	<li>Decompress the downloaded files by typing: 
	&#62;tar -xzf ncbi-blast-2.2.7-macosx.tar.gz</li>
	<li>Add the location of the binaries for the blast executable to your path so that the shell can search through this directory when looking for commands by typing: 
	&#62;PATH=$PATH:new_folder_location</li>
	<li>Check if this added the location to your path by typing: 
	&#62;echo $PATH</li>
	<li>Download a preformatted BLAST databases (which are updated daily) by clicking here: 
	<a href="ftp://ftp.ncbi.nlm.nih.gov/blast/db/">ftp://ftp.ncbi.nlm.nih.gov/blast/db/</a></li>
	<li>Place the database into the &#8220;db&#8221; folder.</li>
	<li>em&#62;On a PC: open a MS-DOS prompt (to do this click &#8220;start&#8221; and type &#8220;cmd&#8221; in the search bar) and change the directory to the ncbi-blast folder by typing: 
	C:\Users&#62;cd ..\ [moves up one folder] 
	C:\&#62;cd ncbi-blast-2.2.27+ 
	This will change the directory to: 
	C:\ncbi-blast-2.2.27+&#62;</li>
	<li>Create the database using the following &#8220;makedb&#8221; command: 
	&#62;makedb &#8211;in db/briggsae.fasta &#8211;dbtype prot &#8211;out db/briggsae 
	Note: In the example below (Figure 4) the database is named &#8220;briggsae&#8221; and is comprised of one linkage group from the organism Caenorhabditis briggsae.</li>
	<li>Create a query protein sequence called &#8220;test&#8221; by inserting a FASTA formatted protein text sequence into the &#8220;db&#8221; folder.</li>
	<li>Interrogate the database via a blastp search by typing the following command: 
	&#62;blastp &#8211;query db/test.txt &#8211;db db/briggsae &#8211;out text.txt</li>
	<li>em&#62;On a Mac: download a database for local Blast searches by accessing the NCBI ftp website as per the instructions above (step 2.4) and then type: 
	&#62;lcd ../databases/</li>
	<li>Download the genome or sequence of interest by typing: 
	&#62;get NC_[Accession #].fna 
	Note: &#8220;.fna&#8221; refers to the FASTA formatted nucleotide sequence and &#8220;.faa&#8221; refers to the FASTA formatted amino acid sequences.</li>
	<li>Type &#8220;quit&#8221; to exit the ftp site.</li>
	<li>Make the database by typing: 
	&#62;makeblastdb -in db/mouse.faa -out mouse -dbtype prot</li>
	<li>Insert a FAST formatted query sequence into the &#8220;bin&#8221; folder and interrogate the database with the following command: 
	&#62; blastp -query &#8220;your query.fasta&#8221; -db &#8221;your database&#8221; -out results.txt</li>
</ol>
3. Generating Multiple Sequence Alignments
<ol>
	<li>Click on these links to access commonly used Multiple Sequence Alignment (MSA) programs: 
	ClustalW6 <a href="http://www.clustal.org/">http://www.clustal.org/</a> 
	Kalign7 <a href="http://msa.sbc.su.se/cgi-bin/msa.cgi">http://msa.sbc.su.se/cgi-bin/msa.cgi</a> 
	MAFFT8,9 <a href="http://mafft.cbrc.jp/alignment/software/">http://mafft.cbrc.jp/alignment/software/</a> 
	MUSCLE10 <a href="http://www.drive5.com/muscle/">http://www.drive5.com/muscle/</a> 
	T-Coffee11 <a href="http://www.tcoffee.org/Projects/tcoffee/">http://www.tcoffee.org/Projects/tcoffee/</a> 
	PROBCONS12 <a href="http://toolkit.tuebingen.mpg.de/probcons">http://toolkit.tuebingen.mpg.de/probcons</a></li>
	<li>Click on this link - <a href="http://tcoffee.crg.cat/apps/tcoffee/do:regular">http://tcoffee.crg.cat/apps/tcoffee/do:regular</a> - and input FASTA formatted sequence data into the query box 
	Note: A sample output from T-Coffee can be seen in Figure 5, similar residues are color coded.</li>
	<li>Download the Clustal MSA as a command line version (ClustalW) or a graphical version (ClustalX) by clicking this link: <a href="http://www.clustal.org/clustal2/">http://www.clustal.org/clustal2/</a> - then click on the appropriate executable (i.e. win, Linux, Mac OS X).</li>
	<li>Upload data as FASTA formatted sequence text and align (Figure 6).</li>
</ol>
4. Determining Best-fit Models of Evolution
<ol>
	<li>Click here to download the ProtTest13 program: 
	<a href="http://darwin.uvigo.es/our-software/">http://darwin.uvigo.es/our-software/</a></li>
	<li>Once ProtTest is downloaded, double-click on the ProtTest.jar file</li>
	<li>Once ProtTest is launched, click on &#8220;select file&#8221; and load the sequence data (Figure 7).</li>
	<li>Then click &#8220;start&#8221; and the program will begin (Figure 8). 
	Note: After completion of the run (Figure 8), the program will indicate the best model based on criteria e.g. &#8220;Best model according to AIC: WAG+I+G&#8221;</li>
</ol>
5. Inferring Sequence Based Phylogenies by Maximum Likelihood or Bayesian Inference
<ol>
	<li>Downloaded PhyML4 here: 
	<a href="https://code.google.com/p/phyml/">https://code.google.com/p/phyml/</a></li>
	<li>Launch the executable by double clicking the appropriate application (i.e. phyml Windows, phyml Linux,&#160;etc.) and the interface window will pop up (Figure 9).</li>
	<li>Load the input sequence as a PHYLIP formatted sequence by typing: 
	&#62;&#8221;file name&#8221;.phy 
	Note: To convert between sequence formats, use the &#8220;Readseq&#8221; web program available at - <a href="http://iubio.bio.indiana.edu/cgi-bin/readseq.cgi">http://iubio.bio.indiana.edu/cgi-bin/readseq.cgi</a>.</li>
	<li>Launch the program by typing &#8220;Y&#8221;.</li>
	<li>Download MrBayes5 here: 
	<a href="http://mrbayes.sourceforge.net/download.php">http://mrbayes.sourceforge.net/download.php</a></li>
	<li>To start the program click on the executable file and read NEXUS formatted sequence data into the program by typing: 
	&#62;execute &#8220;file name&#8221;.nex</li>
	<li>Set the evolutionary model.</li>
	<li>Select the number of generations to run by typing: 
	&#62;mcmcp ngen = 1000000 [this sets the number of generations to 1000000] 
	&#62;sump burnin =10000 [this sets the burnin to 10000]</li>
	<li>Save the branch lengths in the results file by typing: 
	&#62;mcmcp savebrlens = yes&#160;</li>
	<li>Run the analysis by typing: 
	&#62;mcmc</li>
	<li>Summarize the trees using the &#8220;sumt&#8221; command.</li>
</ol>
6. Visualizing Phylogenies
<ol>
	<li>View a list of tree viewer programs here: 
	<a href="http://www.treedyn.org/overview/editors.html">http://www.treedyn.org/overview/editors.html</a></li>
	<li>Download the TreeView14 program here: 
	<a href="http://taxonomy.zoology.gla.ac.uk/rod/treeview.html">http://taxonomy.zoology.gla.ac.uk/rod/treeview.html</a></li>
</ol>

<ol>
	<li>Altschul, S. F., Carroll, R. J., Lipman, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Weights+for+data+related+by+a+tree.">Weights for data related by a tree.</a> J. Mol. Biol. 207 (4), 647-653 (1989).</li><li>Akaike, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+look+at+the+statistical+model+identification.">A new look at the statistical model identification.</a> IEEE Trans. Automat. Contr. 19 (6), 706-723 (1974).</li><li>Schwarz, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimating+the+dimension+of+a+model.">Estimating the dimension of a model.</a> Ann. Stat. 6 (2), 461-464 (1978).</li><li>Guindon, S., Gascuel, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple,+fast,+and+accurate+algorithm+to+estimate+large+phylogenies+by+maximum+likelihood.">A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.</a> Syst. Biol. 52 (5), 696-704 (2003).</li><li>Huelsenbeck, J. P., Ronquist, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MRBAYES:+Bayesian+inference+of+phylogenetic+trees.">MRBAYES: Bayesian inference of phylogenetic trees.</a> Bioinformatics. 17 (8), 754-755 (2001).</li><li>Thompson, J. D., Higgins, D. G., Gibson, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CLUSTAL+W:+Improving+the+sensitivity+of+progressive+multiple+sequence+alignment+through+sequence+weighting,+position-specific+gap+penalties+and+weight+matrix+choice.">CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.</a> Nucleic Acids Res. 22 (22), 4673-4680 (1994).</li><li>Lassmann, T., Sonnhammer, E. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kalign--an+accurate+and+fast+multiple+sequence+alignment+algorithm.">Kalign--an accurate and fast multiple sequence alignment algorithm.</a> BMC Bioinformatics. 6, 298 (2005).</li><li>Katoh, K., Kuma, K., Toh, H., Miyata, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MAFFT+version+5:+Improvement+in+accuracy+of+multiple+sequence+alignment.">MAFFT version 5: Improvement in accuracy of multiple sequence alignment.</a> Nucleic Acids Res. 33 (2), 511-518 (2005).</li><li>Katoh, K., Misawa, K., Kuma, K., Miyata, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MAFFT:+A+novel+method+for+rapid+multiple+sequence+alignment+based+on+fast+fourier+transform.">MAFFT: A novel method for rapid multiple sequence alignment based on fast fourier transform.</a> Nucleic Acids Res. 30 (14), 3059-3066 (2002).</li><li>Edgar, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MUSCLE:+Multiple+sequence+alignment+with+high+accuracy+and+high+throughput.">MUSCLE: Multiple sequence alignment with high accuracy and high throughput.</a> Nucleic Acids Res. 32 (5), 1792-1797 (2004).</li><li>Notredame, C., Higgins, D. G., Heringa, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T-coffee:+A+novel+method+for+fast+and+accurate+multiple+sequence+alignment.">T-coffee: A novel method for fast and accurate multiple sequence alignment.</a> J. Mol. Biol. 302 (1), 205-217 (2000).</li><li>Do, C. B., Mahabhashyam, M. S., Brudno, M., Batzoglou, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ProbCons:+Probabilistic+consistency-based+multiple+sequence+alignment.">ProbCons: Probabilistic consistency-based multiple sequence alignment.</a> Genome Res. 15 (2), 330-340 (2005).</li><li>Darriba, D., Taboada, G. L., Doallo, R., Posada, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ProtTest+3:+Fast+selection+of+best-fit+models+of+protein+evolution.">ProtTest 3: Fast selection of best-fit models of protein evolution.</a> Bioinformatics. 27 (8), 1164-1165 (2011).</li><li>Page, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TreeView:+An+application+to+display+phylogenetic+trees+on+personal+computers.">TreeView: An application to display phylogenetic trees on personal computers.</a> Comput. Appl. Biosci. 12 (4), 357-358 (1996).</li><li>Darriba, D., Taboada, G. L., Doallo, R., Posada, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=jModelTest+2:+More+models,+new+heuristics+and+parallel+computing.">jModelTest 2: More models, new heuristics and parallel computing.</a> Nat. Methods. 9 (8), 772 (2012).</li><li>Chevenet, F., Brun, C., Banuls, A. L., Jacq, B., Christen, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TreeDyn:+Towards+dynamic+graphics+and+annotations+for+analyses+of+trees.">TreeDyn: Towards dynamic graphics and annotations for analyses of trees.</a> BMC Bioinformatics. 7, 439 (2006).</li></ol>

We have nothing to disclose.&#160;

Our hope for this article is that it will serve as a starting point to guide researchers or students that are new to phylogenetics. Genome sequencing projects have become less expensive over the last few years and as a consequence the user demand for this technology is increasing, and now the production of large sequence datasets is commonplace in small labs. These datasets often provide researchers with sets of genes that require a phylogenetic framework to begin to understand their function. Furthermore, because phylog...

In order to understand how two (or more) species evolved, it is first necessary to obtain sequence or morphological data from each sample; these data represent quantities that we can use to measure their relationship through evolutionary space. Just like when measuring linear distance, having more data available (e.g. miles, inches, microns) will equate to a more accurate measurement. Ergo, the accuracy with which a researcher can deduce evolutionary distance is heavily influenced by the volume of informative data available to measure relationships. Furthermore, because different samples evolve at different rates and by different mechanisms, the method that we use to measure the relationship between two taxa also directly influences the accuracy of evolutionary measurements.&#160;Therefore, because evolutionary relationships are not directly observed but instead are extrapolated from sequence or morphological data, the problem of inferring evolutionary relationships becomes one of statistics. Phylogenetics is the branch of biology concerned with applying statistical models to patterns of evolution in order to optimally reconstruct the evolutionary history between taxa. This reconstruction between taxa is referred to as the taxa&#8217;s phylogeny.
To help bridge the gap in expertise between molecular biologists and evolutionary biologists we describe here a step by step pipeline for inferring phylogenies from a set of sequences. Firstly, we detail the steps involved in database interrogation using the Basic Local Alignment Search Tool (BLAST1) algorithm through the web based interface and also by using local executables; this is often the first step in obtaining a list of similar sequences to an unidentified query, although some researchers may also be interested in gathering data for a single group via web interfaces such as Phylota (http://www.phylota.net/). BLAST is an algorithm for comparing primary amino acid or nucleotide sequence data against a database of sequences to search for &#8220;hits&#8221; that resemble the query sequence. The BLAST program was designed by Stephen Altschul et al. at the National Institutes of Health (NIH)1. The BLAST server consists of a number of different programs, and here is a list of some of the most common BLAST programs:
i) Nucleotide-nucleotide BLAST (blastn): This program requires a DNA sequence input and returns the most similar DNA sequences from the DNA database that the user specifies (e.g. for a specific organism).
ii) Protein-protein BLAST (blastp): Here the user inputs a protein sequence and the program returns the most similar protein sequences from the protein database that the user specifies.
iii) Position-Specific Iterative BLAST (PSI-BLAST) (blastpgp): The user input is a protein sequence which returns a set of closely related proteins, and from this dataset a conserved profile is generated. Next a new query is generated using only these conserved &#8220;motifs&#8221; which is used to interrogate a protein database and this returns a larger group of proteins from which a new set of conserved &#8220;motifs&#8221; are extracted and then used to interrogate a protein database until an even larger set of proteins are retuned and another profile is generated and the process repeated. By including related proteins into the query in each step this program allows the user to identify sequences that are more divergent.
iv) Nucleotide 6-frame translation-protein (blastx): Here the user provides a nucleotide sequence input which is converted into the six-frame conceptual translation products (i.e. both strands) against a protein sequence database.
v) Nucleotide 6-frame translation-nucleotide 6-frame translation (tblastx): This program takes a DNA nucleotide sequence input and translates the input into all six-frame conceptual translation products which it compares against the six-frame translations of a nucleotide sequence database.
vi) Protein-nucleotide 6-frame translation (tblastn): This program uses a protein sequence input to compare against all six reading frames of a nucleotide sequence database.
Next, we describe commonly used programs for generating a Multiple Sequence Alignment (MSA) from a sequence dataset, and this is followed by a user guide to programs that determine the best-fit models of evolution for a sequence dataset. Phylogenetic reconstruction is a statistical problem, and because of this, phylogenetic methods need to incorporate a statistical framework. This statistical framework becomes an evolutionary model that incorporates sequence change within the dataset. This evolutionary model is comprised of a set of assumptions about the process of nucleotide or amino-acid substitutions, and the best-fit model for a particular dataset can be selected through statistical testing. The fit to the data of different models can be compared via likelihood ratio tests (LRTs) or information criteria to select the best-fit model within a set of possible ones. Two common information criteria are the Akaike information criterion (AIC)2 and the Bayesian information criterion (BIC)3. Once an optimal alignment is generated, there are many different methods to create a phylogeny from the aligned data. There are numerous methods of inferring evolutionary relationships; broadly, they can be divided into two categories: distance-based methods and sequence-based methods. Distance-based methods compute pairwise distances from sequences, and then use these distances to obtain the tree. Sequence-based methods use the sequence alignment directly, and usually search the tree space using an optimality criterion. We outline two sequence-based methods for reconstructing phylogenetic relationships: these are PhyML4 which implements the maximum likelihood framework, and MrBayes5 which uses Bayesian Markov Chain Monte Carlo inference. Likelihood and Bayesian methods provide a statistical framework for phylogenetic reconstruction. By providing user information on commonly used tree-building tools, we introduce the reader to the necessary data required to infer phylogenetic relationships.

<table border="0" cellpadding="0" cellspacing="0" width="713">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;">BLAST webpage&#160;</td>
			<td></td>
			<td></td>
			<td><a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">http://blast.ncbi.nlm.nih.gov/Blast.cgi</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BLAST executables&#160;</td>
			<td></td>
			<td></td>
			<td><a href="ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/">ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Preformatted BLAST databases</td>
			<td></td>
			<td></td>
			<td><a href="ftp://ftp.ncbi.nlm.nih.gov/blast/db/">ftp://ftp.ncbi.nlm.nih.gov/blast/db/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Clustal</td>
			<td></td>
			<td></td>
			<td><a href="http://www.clustal.org/">http://www.clustal.org/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Kalign</td>
			<td></td>
			<td></td>
			<td><a href="http://msa.sbc.su.se/cgi-bin/msa.cgi">http://msa.sbc.su.se/cgi-bin/msa.cgi</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MAFFT</td>
			<td></td>
			<td></td>
			<td><a href="http://mafft.cbrc.jp/alignment/software/">http://mafft.cbrc.jp/alignment/software/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MUSCLE</td>
			<td></td>
			<td></td>
			<td><a href="http://www.drive5.com/muscle/">http://www.drive5.com/muscle/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">T-Coffee</td>
			<td></td>
			<td></td>
			<td><a href="http://www.tcoffee.org/Projects/tcoffee/">http://www.tcoffee.org/Projects/tcoffee/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PROBCONS</td>
			<td></td>
			<td></td>
			<td><a href="http://toolkit.tuebingen.mpg.de/probcons">http://toolkit.tuebingen.mpg.de/probcons&#160;</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Se-Al&#160;</td>
			<td></td>
			<td></td>
			<td><a href="http://tree.bio.ed.ac.uk/software/seal/">http://tree.bio.ed.ac.uk/software/seal/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BSEdit&#160;</td>
			<td></td>
			<td></td>
			<td><a href="http://www.bsedit.org/">http://www.bsedit.org/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">JalView</td>
			<td></td>
			<td></td>
			<td><a href="http://www.jalview.org/">http://www.jalview.org/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SeaView</td>
			<td></td>
			<td></td>
			<td><a href="http://pbil.univ-lyon1.fr/software/seaview.html">http://pbil.univ-lyon1.fr/software/seaview.html</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">ProtTest&#160;</td>
			<td></td>
			<td></td>
			<td style="width:447px;"><a href="https://code.google.com/p/prottest3/">https://code.google.com/p/prottest3/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Java Runtime&#160;</td>
			<td></td>
			<td></td>
			<td><a href="http://www.java.com/en/download/chrome.jsp">http://www.java.com/en/download/chrome.jsp</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Readseq</td>
			<td></td>
			<td></td>
			<td><a href="http://iubio.bio.indiana.edu/cgi-bin/readseq.cgi">http://iubio.bio.indiana.edu/cgi-bin/readseq.cgi</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">jModelTest</td>
			<td></td>
			<td></td>
			<td style="width:447px;"><a href="https://code.google.com/p/jmodeltest2/">https://code.google.com/p/jmodeltest2/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PhyML</td>
			<td></td>
			<td></td>
			<td><a href="https://code.google.com/p/phyml/">https://code.google.com/p/phyml/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MrBayes</td>
			<td></td>
			<td></td>
			<td><a href="http://mrbayes.sourceforge.net/download.php">http://mrbayes.sourceforge.net/download.php</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">TreeView</td>
			<td></td>
			<td></td>
			<td><a href="http://taxonomy.zoology.gla.ac.uk/rod/treeview.html">http://taxonomy.zoology.gla.ac.uk/rod/treeview.html</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">TreeDyn</td>
			<td></td>
			<td></td>
			<td style="width:447px;"><a href="http://www.treedyn.org/">http://www.treedyn.org/</a></td>
		</tr>
	</tbody>
</table>

a practical guide to phylogenetics for nonexperts

Many researchers, across incredibly diverse foci, are applying phylogenetics to their research question(s). However, many researchers are new to this topic and so it presents inherent problems. Here we compile a practical introduction to phylogenetics for nonexperts.&#160;We outline in a step-by-step manner, a pipeline for generating reliable phylogenies from gene sequence datasets. We begin with a user-guide for similarity search tools via online interfaces as well as local executables. Next, we explore programs for generating multiple sequence alignments followed by protocols for using software to determine best-fit models of evolution. We then outline protocols for reconstructing phylogenetic relationships via maximum likelihood and Bayesian criteria&#160;and finally describe tools for visualizing phylogenetic trees. While this is not by any means an exhaustive description of phylogenetic approaches, it does provide the reader with practical starting information on key software applications commonly utilized by phylogeneticists. The vision for this article would be that it could serve as a practical training tool for researchers embarking on phylogenetic studies&#160;and also serve as an educational resource that could be incorporated into a classroom or teaching-lab.

Finding similarities to a query allows researchers to ascribe a potential identity to new sequences and also infer relationships between sequences. The file input type for BLAST1 is FASTA formatted text sequence or GenBank accession number. FASTA formatted sequence begins with a description line indicated by a &#8220;&#62;&#8221; sign (Figure 2). The description must follow immediately after the &#8220;&#62;&#8221; sign, the sequence (i.e. nucleotides or amino acids) follow the descri...

Watch this Scientific Journal Video about A Practical Guide to Phylogenetics for Nonexperts at JoVE.com

A Practical Guide to Phylogenetics for Nonexperts

Here we describe a step-by-step pipeline for generating reliable phylogenies from nucleotide or amino acid sequence datasets. This guide aims to serve researchers or students new to phylogenetic analysis.&#160;

Many researchers, across incredibly diverse foci, are applying phylogenetics to their research question(s). However, many researchers are new to this ...

a-practical-guide-to-phylogenetics-for-nonexperts

Research

JoVE Journal

Biology

35.2K visualizações.  The George Washington University.  Aqui nós descrevemos um gasoduto passo-a-passo para a geração de filogenias confiáveis ​​de nucleotídeos ou aminoácidos conjuntos de dados de seqüência. Este guia destina-se a servir os investigadores ou alunos novos para a análise filogenética. 

Vídeo: A Practical Guide to Phylogenetics for Nonexperts

The Ladder Rung Walking Task: A Scoring System and its Practical Application.

Progress in the development of animal models for/stroke, spinal cord injury, and other neurodegenerative disease requires tests of high sensitivity to elaborate distinct aspects of motor function and to determine even subtle loss of movement capacity. To enhance efficacy and resolution of testing, tests should permit qualitative and quantitative measures of motor function and be sensitive to changes in performance during recovery periods. The present study describes a new task to assess skilled walking in the rat to measure both forelimb and hindlimb function at the same time. Animals are required to walk along a horizontal ladder on which the spacing of the rungs is variable and is periodically changed. Changes in rung spacing prevent animals from learning the absolute and relative location of the rungs and so minimize the ability of the animals to compensate for impairments through learning. In addition, changing the spacing between the rungs allows the test to be used repeatedly in long-term studies. Methods are described for both quantitative and qualitative description of both fore- and hindlimb performance, including limb placing, stepping, co-ordination. Furthermore, use of compensatory strategies is indicated by missteps or compensatory steps in response to another limb&#x2019;s misplacement. 

The ladder rung walking task is a new test to assess skilled walking and measure both forelimb and hindlimb placing, stepping, and inter-limb co-ordination.

Progress in the development of animal models for/stroke, spinal cord injury, and other neurodegenerative disease requires tests of high sensitivity to ...

A Practical Approach to Genetic Inducible Fate Mapping: A Visual Guide to Mark and Track Cells In Vivo

Fate maps are generated by marking and tracking cells in vivo to determine how progenitors contribute to specific structures and cell types in developing and adult tissue. An advance in this concept is Genetic Inducible Fate Mapping (GIFM), linking gene expression, cell fate, and cell behaviors in vivo, to create fate maps based on genetic lineage.
GIFM exploits X-CreER lines where X is a gene or set of gene regulatory elements that confers spatial expression of a modified bacteriophage protein, Cre recombinase (CreERT). CreERT contains a modified estrogen receptor ligand binding domain which renders CreERT sequestered in the cytoplasm in the absence of the drug tamoxifen. The binding of tamoxifen releases CreERT, which translocates to the nucleus and mediates recombination between DNA sequences flanked by loxP sites. In GIFM, recombination typically occurs between a loxP flanked Stop cassette preceding a reporter gene such as GFP.
Mice are bred to contain either a region- or cell type-specific CreER and a conditional reporter allele. Untreated mice will not have marking because the Stop cassette in the reporter prevents further transcription of the reporter gene. We administer tamoxifen by oral gavage to timed-pregnant females, which provides temporal control of CreERT release and subsequent translocation to the nucleus removing the Stop cassette from the reporter. Following recombination, the reporter allele is constitutively and heritably expressed. This series of events marks cells such that their genetic history is indelibly recorded. The recombined reporter thus serves as a high fidelity genetic lineage tracer that, once on, is uncoupled from the gene expression initially used to drive CreERT.
We apply GIFM in mouse to study normal development and ascertain the contribution of genetic lineages to adult cell types and tissues. We also use GIFM to follow cells on mutant genetic backgrounds to better understand complex phenotypes that mimic salient features of human genetic disorders.
This video article guides researchers through experimental methods to successfully apply GIFM. We demonstrate the method using our well characterized Wnt1-CreERT;mGFP mice by administering tamoxifen at embryonic day (E)8.5 via oral gavage followed by dissection at E12.5 and analysis by epifluorescence stereomicroscopy. We also demonstrate how to micro-dissect fate mapped domains for explant preparation or FACS analysis and dissect adult fate-mapped brains for whole mount fluorescent imaging. Collectively, these procedures allow researchers to address critical questions in developmental biology and disease models.

A Practical Approach to Genetic Inducible Fate Mapping: A Visual Guide to Mark and Track Cells In Vivo

Genetic Inducible Fate Mapping (GIFM) marks and tracks cells with fine spatial and temporal control in vivo and elucidates how cells from a specific genetic lineage contribute to developing and adult tissues. Demonstrated here are the techniques required to fate map E12.5 mouse embryos for epifluorescent and explant analysis.

Fate maps are generated by marking and tracking cells in vivo to determine how progenitors contribute to specific structures and cell types in developing ...

A Practical and Novel Method to Extract Genomic DNA from Blood Collection Kits for Plasma Protein Preservation

Laboratory tests can be done on the cellular or fluid portions of the blood. The use of different blood collection tubes determines the portion of the blood that can be analyzed (whole blood, plasma or serum). Laboratories involved in studying the genetic basis of human disorders rely on anticoagulated whole blood collected in EDTA-containing vacutainer as the source of DNA for genetic / genomic analysis. Because most clinical laboratories perform biochemical, serologic and viral testing as a first step in phenotypic outcome investigation, anticoagulated blood is also collected in heparin-containing tube (plasma tube). Therefore when DNA and plasma are needed for simultaneous and parallel analyses of both genomic and proteomic data, it is customary to collect blood in both EDTA and heparin tubes. If blood could be collected in a single tube and serve as a source for both plasma and DNA, that method would be considered an advancement to existing methods. The use of the compacted blood after plasma extraction represents an alternative source for genomic DNA, thus minimizing the amount of blood samples processed and reducing the number of samples required from each patient. This would ultimately save time and resources.
The BD P100 blood collection system for plasma protein preservation were created as an improved method over previous plasma or serum collection tubes1, to stabilize the protein content of blood, enabling better protein biomarker discovery and proteomics experimentation from human blood. The BD P100 tubes contain 15.8 ml of spray-dried K2EDTA and a lyophilized proprietary broad spectrum cocktail of protease inhibitors to prevent coagulation and stabilize the plasma proteins. They also include a mechanical separator, which provides a physical barrier between plasma and cell pellets after centrifugation. Few methods have been devised to extract DNA from clotted blood samples collected in old plasma tubes2-4. Challenges from these methods were mainly associated with the type of separator inside the tubes (gel separator) and included difficulty in recovering the clotted blood, the inconvenience of fragmenting or dispersing the clot, and obstruction of the clot extraction by the separation gel.
We present the first method that extracts and purifies genomic DNA from blood drawn in the new BD P100 tubes. We compare the quality of the DNA sample from P100 tubes to that from EDTA tubes. Our approach is simple and efficient. It involves four major steps as follows: 1) the use of a plasma BD P100 (BD Diagnostics, Sparks, MD, USA) tube with mechanical separator for blood collection, 2) the removal of the mechanical separator using a combination of sucrose and a sterile paperclip metallic hook, 3) the separation of the buffy coat layer containing the white cells and 4) the isolation of the genomic DNA from the buffy coat using a regular commercial DNA extraction kit or a similar standard protocol.

We are describing a new method of isolating genomic DNA from whole blood collected for plasma/serology. After plasma collection, the compacted blood is usually discarded. Our novel method represents a significant improvement over existing methods and makes DNA and plasma available from a single collection, without requesting additional blood.

Laboratory tests can be done on the cellular or  fluid portions of the blood. The use of different blood collection tubes  determines the portion of the ...

V3 Stain-free Workflow for a Practical, Convenient, and Reliable Total Protein Loading Control in Western Blotting

The western blot is a very useful and widely adopted lab technique, but its execution is challenging. The workflow is often characterized as a &#34;black box&#34; because an experimentalist does not know if it has been performed successfully until the last of several steps. Moreover, the quality of western blot data is sometimes challenged due to a lack of effective quality control tools in place throughout the western blotting process. Here we describe the V3 western workflow, which applies stain-free technology to address the major concerns associated with the traditional western blot protocol. This workflow allows researchers: 1) to run a gel in about 20-30 min; 2) to visualize sample separation quality within 5 min after the gel run; 3) to transfer proteins in 3-10 min; 4) to verify transfer efficiency quantitatively; and most importantly 5) to validate changes in the level of the protein of interest using total protein loading control. This novel approach eliminates the need of stripping and reprobing the blot for housekeeping proteins such as &#946;-actin, &#946;-tubulin, GAPDH, etc. The V3 stain-free workflow makes the western blot process faster, transparent, more quantitative&#160;and reliable.

V3 workflow is a western blot procedure using stain-free gels. The stain-free technology allows researchers to visualize protein separation quality, to verify the transfer efficiency, and most importantly, to validate the change in the protein of interest using total protein quantification as a reliable loading control.

The western blot is a very useful and widely adopted lab technique, but its execution is challenging. The workflow is often characterized as a &#34;black ...

A Guide to Modern Quantitative Fluorescent Western Blotting with Troubleshooting Strategies

The late 1970s saw the first publicly reported use of the western blot, a technique for assessing the presence and relative abundance of specific proteins within complex biological samples. Since then, western blotting methodology has become a common component of the molecular biologists experimental repertoire. A cursory search of PubMed using the term &#8220;western blot&#8221; suggests that in excess of two hundred and twenty thousand published manuscripts have made use of this technique by the year 2014. Importantly, the last ten years have seen technical imaging advances coupled with the development of sensitive fluorescent labels which have improved sensitivity and yielded even greater ranges of linear detection. The result is a now truly Quantifiable Fluorescence based Western Blot (QFWB) that allows biologists to carry out comparative expression analysis with greater sensitivity and accuracy than ever before. Many &#8220;optimized&#8221; western blotting methodologies exist and are utilized in different laboratories. These often prove difficult to implement due to the requirement of subtle but undocumented procedural amendments. This protocol provides a comprehensive description of an established and robust QFWB method, complete with troubleshooting strategies.

The advancement of western blotting using fluorescence has allowed detection of subtle changes in protein expression enabling quantitative analyses. Here we describe a robust methodology for detection of a range of proteins across a variety of species and tissue types. A strategy to overcome common technical problems is also provided.

The late 1970s saw the first publicly reported use of the western blot, a technique for assessing the presence and relative abundance of specific proteins ...

Nephrotoxin Microinjection in Zebrafish to Model Acute Kidney Injury

The kidneys are susceptible to harm from exposure to chemicals they filter from the bloodstream. This can lead to organ injury associated with a rapid decline in renal function and development of the clinical syndrome known as acute kidney injury (AKI). Pharmacological agents used to treat medical circumstances ranging from bacterial infection to cancer, when administered individually or in combination with other drugs, can initiate AKI. Zebrafish are a useful animal model to study the chemical effects on renal function in vivo, as they form an embryonic kidney comprised of nephron functional units that are conserved with higher vertebrates, including humans. Further, zebrafish can be utilized to perform genetic and chemical screens, which provide opportunities to elucidate the cellular and molecular facets of AKI and develop therapeutic strategies such as the identification of nephroprotective molecules. Here, we demonstrate how microinjection into the zebrafish embryo can be utilized as a paradigm for nephrotoxin studies.

Renal injuries incurred from nephrotoxins, which include drugs ranging from antibiotics to chemotherapeutics, can result in complex disorders whose pathogenesis remains incompletely understood. This protocol demonstrates how zebrafish can be used for disease modeling of these conditions, which can be applied to the identification of renoprotective measures.

The kidneys are susceptible to harm from exposure to chemicals they filter from the bloodstream. This can lead to organ injury associated with a rapid ...

Endotracheal Intubation of Rabbits Using a Polypropylene Guide Catheter

Endotracheal intubation in rabbits can be challenging due to their unusual anatomy. Achieving a patent airway during anesthesia is critical for the avoidance of airway obstruction, prevention of gastric tympany, and to allow ventilatory support. Due to the difficulty of intubation, alternative methods such as the use of laryngeal mask airways or laryngeal tubes have been explored. However, these methods do not result in direct access to the trachea and thus may present a risk for development of complications. In addition, lack of direct intubation of the trachea can result in personnel exposure to waste anesthetic gases. Numerous methods for endotracheal intubation have been described, including blind placement, use of a fiberoptic laryngoscope or endoscope, and cricoid placement. Despite these numerous publications, many still struggle to achieve success. Here we provide a detailed description of an intubation technique that can be taught with minimal training with a short time to proficiency. Briefly, after administration of injectable anesthesia and proper positioning of the rabbit, a polypropylene catheter is placed into the trachea by direct visualization using a laryngoscope. The catheter is then used as a guide to direct the endotracheal tube into the trachea. This method allows for intubation without the need for expensive equipment and can be performed by a single individual without the need for an assistant. In conclusion, this technique can be easily taught and performed at very little cost in any clinical or research setting.

Endotracheal intubation in rabbits is challenging due to their unusual anatomy. Here we present a technique for direct intubation of the trachea using a polypropylene catheter as a guide. This method utilizes relatively inexpensive supplies, requires minimal training, and can be easily performed in any clinical setting.

Endotracheal intubation in rabbits can be challenging due to their unusual anatomy. Achieving a patent airway during anesthesia is critical for the ...

Practical Use of RNA Interference: Oral Delivery of Double-stranded RNA in Liposome Carriers for Cockroaches

RNA interference (RNAi) has been widely applied for uncovering the biological functions of numerous genes, and has been envisaged as a pest control tool operating by disruption of essential gene expression. Although different methods, such as injection, feeding, and soaking, have been reported for successful delivery of double-stranded RNA (dsRNA), the efficiency of RNAi through oral delivery of dsRNA is highly variable among different insect groups. The German cockroach, Blattella germanica, is highly sensitive to the injection of dsRNA, as shown by many studies published previously. The present study describes a method to demonstrate that the dsRNA encapsulated with liposome carriers is sufficient to retard the degradation of dsRNA by midgut juice. Notably, the continuous feeding of dsRNA encapsulated by liposomes significantly reduces the tubulin expression in the midgut, and led to the death of cockroaches. In conclusion, the formulation and utilization of dsRNA lipoplexes, which protect dsRNA against nucleases, could be a practical use of RNAi for insect pest control in the future.

This manuscript demonstrates the depletion of gene expression in the midgut of the German cockroach through oral ingestion of double-stranded RNA encapsulated in liposomes.

RNA interference (RNAi) has been widely applied for uncovering the biological functions of numerous genes, and has been envisaged as a pest control tool ...

A Sectioning, Coring, and Image Processing Guide for High-Throughput Cortical Bone Sample Procurement and Analysis for Synchrotron Micro-CT

Bone is a dynamic and mechanically active tissue that changes in structure over the human lifespan. The products of the bone remodeling process have been studied substantially using traditional two-dimensional techniques. Recent advancements in X-ray imaging technology via desktop micro-computed tomography (&#181;CT) and synchrotron radiation micro-computed tomography (SR&#181;CT) have allowed for the acquisition of high-resolution three-dimensional (3D) scans of a larger field of view (FOV) than other 3D imaging techniques (e.g., SEM) providing a more complete picture of microscopic structures within human cortical bone. The specimen should be accurately centered within the FOV, however, to limit the appearance of streak artifacts known to impact data analysis. Previous studies have reported procurement of irregularly shaped rectilinear bone blocks that result in imaging artifacts due to uneven edges or image truncation. We have applied a geological sampling protocol (coring) to procure consistently sized cortical bone core specimens for SR&#181;CT experiments from the anterior aspect of human femora. This coring method is efficient and minimally destructive to tissue. It creates uniform cylindrical samples that decrease imaging artifacts by nature of being isometric during rotation and providing a uniform path length for X-ray beams throughout scanning. Image processing of X-ray tomographic data of cored and irregularly shaped samples confirms the potential of the technique to improve visualization and analysis of cortical bone microarchitecture. A goal of this protocol is to deliver a reliable and repeatable method for the extraction of cortical bone cores that is adaptable for various types of high-resolution bone imaging experiments. An overarching goal of the work is to create a standardized cortical bone procurement for SR&#181;CT that is affordable, consistent, and straightforward. This procedure may further be adapted by researchers in related fields who commonly evaluate hard composite materials such as in biological anthropology, geosciences, or material sciences.

We employed a geological (coring) sampling protocol to procure cortical bone specimens of uniform size for SR&#181;CT experiments from the anterior aspect of human femora. This method is minimally destructive, efficient, results in cylindrical specimens that minimize imaging artifacts from irregular sample shapes and improves microarchitectural visualization and analysis.

Bone is a dynamic and mechanically active tissue that changes in structure over the human lifespan. The products of the bone remodeling process have been ...

A Step-by-Step Guide to Mosquito Electroantennography

Female mosquitoes are the deadliest animals on earth, claiming the lives of more than 1 million people every year due to pathogens they transmit when acquiring a blood-meal. To locate a host to feed on, mosquitoes rely on a wide range of sensory cues, including visual, mechanical, thermal, and olfactory. The study details a technique, electroantennography (EAG), that allows researchers to assess whether the mosquitoes can detect individual chemicals and blends of chemicals in a concentration-dependent manner. When coupled with gas-chromatography (GC-EAG), this technique allows to expose the antennae to a full headspace/complex mixture and determines which chemicals present in the sample of interest, the mosquito can detect. This is applicable to host body odors as well as plant floral bouquets or other ecologically relevant odors (e.g., oviposition sites odorants). Here, we described a protocol that permits long durations of preparation responsiveness time and is applicable to both female and male mosquitoes from multiple genera, including Aedes, Culex, Anopheles, and Toxorhynchites mosquitoes. As olfaction plays a major part in mosquito-host interactions and mosquito biology in general, EAGs and GC-EAG can reveal compounds of interest for the development of new disease vector control strategies (e.g., baits). Complemented with behavioral assays, the valence (e.g., attractant, repellent) of each chemical can be determined.

The present article details a step-by-step protocol for successful and low noise electroantennograms in several genera of mosquitoes, including both females and males.

Female mosquitoes are the deadliest animals on earth, claiming the lives of more than 1 million people every year due to pathogens they transmit when ...