This work was supported by the National Natural Science Foundation of China (31371596), the Bio-technology Research Center, China Three Gorges University (2016KBC04), and the Natural Science Foundation of Jiangsu Province, China (BK20151424).

1. Sequence Alignment
<ol>
	<li>Collect amino acid sequences of eukaryotic SWEET and prokaryotic SemiSWEET in separate documents and list them in FASTA format. Download sequences from the National Center for Biotechnology Information (NCBI), European Molecular Biology Laboratory (EMBL), and the DNA Data Bank of Japan (DDBJ) databases by similarity search with the Basic Local Alignment Search Tool (BLAST) tool.
	<ol>
		<li>In the example files, collect 228 putative SWEET protein sequences possessing two...

<ol>
	<li>Nei, M., Kumar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Molecular Evolution and Phylogenetics. , (2000).</li><li>Foth, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phylogenetic+analysis+to+uncover+organellar+origins+of+nuclear-encoded+genes.">Phylogenetic analysis to uncover organellar origins of nuclear-encoded genes.</a> Methods Mol Biol. 390, 467-488 (2007).</li><li>Baldauf, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phylogeny+for+the+faint+of+heart:+a+tutorial.">Phylogeny for the faint of heart: a tutorial.</a> Trends Genet. 19, 345-351 (2003).</li><li>Feng, D. F., Doolittle, R. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Progressive+sequence+alignment+as+a+prerequisite+to+correct+phylogenetic+trees.">Progressive sequence alignment as a prerequisite to correct phylogenetic trees.</a> J Mol Evol. 25, 351-360 (1987).</li><li>Persson, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bioinformatics+in+protein+analysis.">Bioinformatics in protein analysis.</a> EXS. 88, 215-231 (2000).</li><li>Sievers, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast,+scalable+generation+of+high-quality+protein+multiple+sequence+alignments+using+Clustal+Omega.">Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega.</a> Mol Syst Biol. 7, 539 (2011).</li><li>Sievers, F., Higgins, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clustal+omega.">Clustal omega.</a> Curr Protoc Bioinformatics. 48, 1-16 (2014).</li><li>Yang, Z., Rannala, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+phylogenetics:+principles+and+practice.">Molecular phylogenetics: principles and practice.</a> Nat Rev Genet. 13, 303-314 (2012).</li><li>Hall, B. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+the+accuracies+of+several+phylogenetic+methods+using+protein+and+DNA+sequences.">Comparison of the accuracies of several phylogenetic methods using protein and DNA sequences.</a> Mol Biol Evol. 22, 792-802 (2005).</li><li>Tamura, K., Stecher, G., Peterson, D., Filipski, A., Kumar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MEGA6:+Molecular+Evolutionary+Genetics+Analysis+version+6.0.">MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.</a> Mol Biol Evol. 30, 2725-2729 (2013).</li><li>Ronquist, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MrBayes+3.2:+efficient+Bayesian+phylogenetic+inference+and+model+choice+across+a+large+model+space.">MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space.</a> Syst Biol. 61, 539-542 (2012).</li><li>Chen, L. Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sugar+transporters+for+intercellular+exchange+and+nutrition+of+pathogens.">Sugar transporters for intercellular exchange and nutrition of pathogens.</a> Nature. 468, 527-532 (2010).</li><li>Xuan, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+role+of+oligomerization+for+bacterial+and+plant+SWEET+sugar+transporter+family.">Functional role of oligomerization for bacterial and plant SWEET sugar transporter family.</a> Proc Natl Acad Sci USA. 110, 3685-3694 (2013).</li><li>Hu, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phylogenetic+evidence+for+a+fusion+of+archaeal+and+bacterial+SemiSWEETs+to+form+eukaryotic+SWEETs+and+identification+of+SWEET+hexose+transporters+in+the+amphibian+chytrid+pathogen+Batrachochytrium+dendrobatidis.">Phylogenetic evidence for a fusion of archaeal and bacterial SemiSWEETs to form eukaryotic SWEETs and identification of SWEET hexose transporters in the amphibian chytrid pathogen Batrachochytrium dendrobatidis.</a> FASEB J. 30, 3644-3654 (2016).</li><li>Holder, M. T., Zwickl, D. J., Dessimoz, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluating+the+robustness+of+phylogenetic+methods+to+among-site+variability+in+substitution+processes.">Evaluating the robustness of phylogenetic methods to among-site variability in substitution processes.</a> Philos Trans R Soc Lond B Biol Sci. 363, 4013-4021 (2008).</li><li>Alfaro, M. E., Holder, M. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Posterior+and+the+Prior+in+Bayesian+Phylogenetics.">The Posterior and the Prior in Bayesian Phylogenetics.</a> Annu Rev Ecol Evol Syst. 37, 19-42 (2006).</li><li>Suchard, M., Rambaut, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Many-core+algorithms+for+statistical+phylogenetics.">Many-core algorithms for statistical phylogenetics.</a> Bioinformatics. 25, 1370-1376 (2009).</li><li>Zierke, S., Bakos, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FPGA+acceleration+of+the+phylogenetic+likelihood+function+for+Bayesian+MCMC+inference+methods.">FPGA acceleration of the phylogenetic likelihood function for Bayesian MCMC inference methods.</a> BMC Bioinformatics. 11, 184 (2010).</li></ol>

It is becoming increasingly popular in biological research to make a phylogenetic tree based on nucleotide or amino acid&#160;sequences8. Generally, there are three critical stages of the practice including sequence alignment, evaluation of the aligned sequences with the proper method or algorithm, and visualization of the computational result as a phylogenetic tree. In the presented study, three rounds of sequence alignment were conducted: first, the SWEET protein sequences, including the first a...

DNA or RNA sequences carry genetic information for underlying phenotypes that can be analyzed through physiological and biochemical methods or observed through morphological and fossil evidence. In a sense, genetic information is more reliable than evaluating external phenotypes because the former is the basis for the latter. In evolutionary study, fossil evidence is very direct and convincing. However, many organisms, such as microorganisms, have little chance to form a fossil during long geologic ages. Therefore, molecular information such as nucleotide sequences and amino acid sequences from related extant organisms are of value for exploring evolutionary relationships1. In the present study, a simple introduction of basic phylogenetic knowledge and an easy-to-learn protocol was provided for newcomers who need to construct a phylogenetic tree on their own.
Both DNA (nucleotide) and protein (amino acid) sequences can be used to infer phylogenetic relationships between homologous genes, organelles, or even organisms2. DNA sequences are more likely to be affected by changes during evolution. In contrast, amino acid sequences are much more stable given that synonymous mutations in nucleotide sequences do not cause mutations in amino acid sequences. As a result, DNA sequences are useful for comparison of homologous genes from closely related organisms, whereas amino acid sequences are appropriate for homologous genes from distantly related organisms3.
A phylogenetic analysis begins with the alignment of amino acid or nucleotide sequences4 retrieved from an annotated genome sequencing database5&#160;listed in FASTA format, i.e., putative or expressed protein sequences, RNA sequences, or DNA sequences. It is worth noting that it is critical to collect high-quality sequences for the analysis, and only homologous sequences can be used to analyze phylogenetic relationships. Many different platforms such as Clustal W, Clustal X, Muscle, T-coffee, MAFFT, can be used for sequence alignment. The most widely used is Clustal Omega6,7 (http://www.ebi.ac.uk/Tools/msa/clustalo/), which can be used online or can be downloaded free of charge. The alignment tool has many parameters that the user can adjust before starting the alignment, but the default parameters work well in most cases. After the process is complete, the aligned sequences should be saved in the correct format for the next step. They should then be edited or trimmed using an editing software, such as BioEdit, because phylogenetic tree construction by MEGA requires the sequences to be of equal length (including both amino acid abbreviations and hyphens. In the aligned sequence, any position without an amino acid or nucleotide is represented by a hyphen &#34;-&#34;). Generally, all of the protruding amino acids or nucleotides at either end of the alignment should be removed. In addition, columns containing poorly aligned sequences in the alignment can be deleted because they convey little valuable information, and can sometimes give confusing or false information3. The columns containing one or more hyphens can be deleted at this time or in the later tree construction stage. Alternatively, they can be used for phylogenetic computation. When the sequence alignment and trimming is finished, the aligned sequences should be saved in FASTA format, or the desired format, for later use.
Many software platforms provide tree construction functions using different methods or algorithms. In general, the methods can be classified as either distance matrix methods or discrete data methods. Distance matrix methods are simple and fast to compute, while discrete data methods are complicated and time-consuming. For very closely related taxa with a high degree of sharing of amino acid or nucleotide sequence identity, a distance matrix method (Neighbor Joining: NJ; Unweighted Pair Group Method with Arithmetic mean: UPGMA) is appropriate; for distantly related taxa, a discrete data method (Maximum Likelihood: ML; Maximum Parsimony: MP; Bayesian Inference) is optimal3,8. In this study, the ML methods in MEGA (6.0.6) and Bayesian Inference (MrBayes 3.2) were applied to construct phylogenetic trees9. Ideally, when the proper model and parameters are used, the results derived from different methods may be consistent, and they are thus more reliable and convincing.
For a ML phylogenetic tree constructed using MEGA10, the aligned sequence file in FASTA format must be uploaded into the program. The first step then is to select the optimal substitution model for the uploaded data. All available substitution models are compared based on the uploaded sequences, and their final scores will be shown in a results table. Select the model with the smallest Bayesian Information Criterion (BIC) score (listed first in the table), set ML parameters according to the recommended model, and start the computation. The computation time varies from several minutes to several days, depending on the complexity of the loaded data (length of the sequences and number of taxa) and the performance of the computer on which the programs are run. When the computation is finished, a phylogenetic tree will be shown in a new window. Save the file as &#34;FileName.mat&#34;. After setting parameters to specify the appearance of the tree, save once more. Using this method, MEGA can generate publication grade phylogenetic tree figures.
For tree construction with MrBayes11, the first step is to transform the aligned sequence, which is usually listed in FASTA format, into nexus format (.nex as the file type). Transforming FASTA files into nexus format can be processed in MEGA. Next, the aligned sequence in nexus format can be uploaded into MrBayes. When the file is successfully uploaded, specify detailed parameters for the tree computation. These parameters include details such as amino acid substitution model, variation rates, chain number for Markov chain Monte Carlo (MCMC) coupling, ngen number, average standard deviation of split frequencies, and so on. After these parameters have been specified, start the computation. In the end, two tree figures in ASC II code, one showing clade credibility and the other showing branch lengths, will be displayed on the screen.
The tree result will be saved automatically as &#34;FileName.nex.con&#34;. This tree file can be opened and edited by FigTree, and the figure displayed in FigTree can be modified further to make it more suitable for publication.
In this study, 228 SWEET proteins, including 35 SWEETs from unicellular eukaryotes and 57 SemiSWEETs from prokaryotes, were analyzed as an example. Both the SWEETs and SemiSWEETs were characterized as glucose, fructose, or sucrose transporters across membranes12,13. Phylogenetic analysis suggests that the two MtN3/saliva domains containing SWEETs might be derived from an evolutionary fusion of a bacterial SemiSWEET and of an archaeon14.

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		<col span="3" />
		<col />
	</colgroup>
	<tbody>
		<tr height="39">
			<td height="39" style="height:39px;width:127px;">Adobe Illustration</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a graphical tool developed by Adobe Systems Software Ireland Ltd. Copyright &#169; 2017</td>
		</tr>
		<tr height="36">
			<td height="36" style="height:36px;width:127px;">BioEdit</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a biological sequence alignment editor written for Windows 95/98/NT/2000/XP/7. Copyright &#169; Tom Hall</td>
		</tr>
		<tr height="36">
			<td height="36" style="height:36px;width:127px;">Clustal Omega</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a package for making multiple sequence alignments of amino acid or nucleotide sequences.&#160; http://www.clustal.org/</td>
		</tr>
		<tr height="37">
			<td height="37" style="height:37px;width:127px;">CorelDRAW</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a graphic design software. Copyright &#169; 2017 Corel Corporation</td>
		</tr>
		<tr height="34">
			<td height="34" style="height:34px;width:127px;">FigTree</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a graphical viewer of phylogenetic trees designed by the University of Edinburgh</td>
		</tr>
		<tr height="34">
			<td height="34" style="height:34px;width:127px;">MEGA</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">MolecularEvolutionary Genetics Analysis version6.0 http://www.megasoftware.net/home</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:127px;">MrBayes</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">an Bayesian phylogenetic inference tool</td>
		</tr>
		<tr height="36">
			<td height="36" style="height:36px;width:127px;">NVIDIA</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a company designs graphics processing units (GPUs) for the gaming and professional markets. Corporation Copyright &#169; 2017</td>
		</tr>
		<tr height="38">
			<td height="38" style="height:38px;width:127px;">PAUP</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">Phylogenetic Analysis Using Parsimony. David Swofford&#39;s program implements the maximum likelihood method under a number of nucleotide models.</td>
		</tr>
		<tr height="35">
			<td height="35" style="height:35px;width:127px;">Photoshop</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a raster graphics editor developed and published by Adobe Systems Software Ireland Ltd. Copyright &#169; 2017</td>
		</tr>
		<tr height="28">
			<td height="28" style="height:28px;width:127px;">RHYTHM</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a knowledge based prediction of hekix contacts. Charit&#233; Berlin &#8211; Protein Formatics Group - Copyright 2007-2009</td>
		</tr>
		<tr height="32">
			<td height="32" style="height:32px;width:127px;">TMHMM</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">a tool for prediction of transmembrane helices in proteins. http://www.cbs.dtu.dk/services/TMHMM/</td>
		</tr>
		<tr height="34">
			<td height="34" style="height:34px;width:127px;">Compter</td>
			<td style="width:127px;"></td>
			<td style="width:127px;"></td>
			<td style="width:752px;">4GB memory, Core 2 or above CPU. Windows 7, Windows 10</td>
		</tr>
	</tbody>
</table>

using phylogenetic analysis to investigate eukaryotic gene origin

Phylogenetic analysis uses nucleotide or amino acid sequences or other parameters, such as domain sequences and three-dimensional structure, to construct a tree to show the evolutionary relationship among different taxa (classification units) at the molecular level. Phylogenetic analysis can also be used to investigate domain relationships within an individual taxon, particularly for organisms that have undergone substantial change in morphology and physiology, but for which researchers lack fossil evidence due to the organisms&#39; long evolutionary history or scarcity of fossilization.
In this text, a detailed protocol is described for using the phylogenetic method, including amino acid sequence alignment using Clustal Omega, and subsequent phylogenetic tree construction using both Maximum Likelihood (ML) of Molecular Evolutionary Genetics Analysis (MEGA) and Bayesian Inference via MrBayes. To investigate the origin of eukaryotic Sugars Will Eventually be Exported Transporters (SWEET) genes, 228 SWEETs including 35 SWEET proteins from unicellular eukaryotes and 57 SemiSWEET proteins from prokaryotes were analyzed. Interestingly, SemiSWEETs were found in prokaryotes, but SWEETs were found in eukaryotes. Two phylogenetic trees constructed using theoretically distinct methods have consistently&#160;suggested that the first eukaryotic SWEET gene might stem from the fusion of a bacterial SemiSWEET gene and an archaeal SemiSWEET gene.&#160;It is worth noting that one should be cautious to draw a conclusion based only on phylogenetic analysis, although it is useful to explain the underlying relationship between different taxa, which is difficult or even impossible to discern through experimental means.

Phylogenetic trees show that all of the first MtN3/saliva domains of the 35 SWEET sequences clustered as one clade and the second MtN3/saliva domains of the SWEET sequences clustered as another clade. In addition, alignment results of the SWEETs and SemiSWEETs show that some SemiSWEETs from &#945;-Proteobacteria aligned with the first MtN3/saliva domain of the SWEET sequences, whereas SemiSWEETs from Methanobacteria (archaea) aligned with the second MtN3/saliva domain of the SWEET sequenc...

Watch this Scientific Journal Video about Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin at JoVE.com

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

A method of constructing a phylogenetic tree based on sequence homology of SWEETs from eukaryotes and SemiSWEETs from prokaryotes is described. Phylogenetic analysis is a useful tool for explaining the evolutionary relatedness between homologous proteins or genes from different organism groups.

Phylogenetic analysis uses nucleotide or amino acid sequences or other parameters, such as domain sequences and three-dimensional structure, to construct ...

This method can help answer key questions in the phytogenetic field such as how to collect sequences and how to select the correct computation model. The main advantage of this technique is that it's very easy to learn. Generally, those who are new to this method may struggle simply because they don't know how to handle the data due to a lack of basic knowledge of the principles and methods of phylogeny.This method was first developed when we analyzed the alignment of eukaryotic SWEET genes. Visual demonstration of this method is critical as there is a magnitude of choices and settings for different aspects of the alignment. Begin this procedure with selection of 35 candidate SWEET proteins from unicellular eukaryotic organisms as described in the text protocol.Align the 35 SWEET sequences by inputting them into Clustal Omega. Copy and paste the protein sequences in FASTA format into the input box or upload a sequence file in FASTA format. Specify that it is an amino acid sequence by clicking the icon under the pull down menu in the step one section.Specify the output format and other parameters in the step two section if necessary. For this study, set output format as Clustal without number and leave the other parameters on default settings. In most cases, the default parameters work well without any specification.Submit and run the alignment in the step three section. It may take anywhere from several seconds to minutes until the alignment is finished. In the Result Summary panel, right click the link under the Alignment in CLUSTAL format and save the aligned sequences as 35.clustal.To open the alignment result file in BioEdit, click Sequence and select Edit Mood in the first pull down menu on the main panel of BioEdit. Then click Edit Residues in the submenu. Select the protruding sequences on the left side of the alignment with the cursor and click the Delete icon under the Edit menu to remove the selected sequences.Select and delete the sequences on the right side of the first MtN3 saliva domain and save the trimmed first MtN3 saliva domain sequences as 35-1.fas. Likewise, delete the left and right side sequences of the second MtN3 saliva domain and save it as 35-2.fas. The first and the second MtN3 saliva domain sequences can be predicted with rhythm or TMHMM in advance.Open the file 35-1. fas with MEGA and click Align when prompted. Under the Edit menu, click Select All.Then click Select Sequences. The names and sequences of the taxa will be selected in black. Choose Copy from the Edit menu to copy the sequences onto the clipboard and then paste the copied sequences into a doc file.In the doc file, replace all number signs with the greater than sign and then delete any unrelated characters to convert them to FASTA format. Add 1 at the end of each taxon name to mark them as the first MtN3 saliva domain sequences. Process the second MtN3 saliva domain sequences following the same method and add 2 after each taxon name.Now combine the first and second MtN3 saliva domain sequences in FASTA format in a doc file. To do so, load the combined sequences into Clustal Omega again and align the sequences as before. Save the result as 35realigned.clustal.Open the 35realigned. clustal file in BioEdit. Delete the uneven amino acid residues at either end of the aligned sequences and then save the sequences as 35realigned.fas.Click Yes when warned that some nonstandard characters cannot be saved. Open 35realigned. fas in MEGA.Click the Data menu and choose Export Alignment. Then save the alignment in POP format as 35. next for later use in MR Base.Meanwhile, click the Models icon on the main panel of MEGA. Choose Find Best DNA Protein Models and click OK on the popup window. Click Compute to begin the model searching process.A new progress panel will open. This process lasts several minutes to several days depending on the complexity of the loaded sequences and the computer's performance. A table showing the results will open after the model searching process is finished.The smallest BIC score will be listed first followed by a series of different models with gradually increasing BIC scores. The first model LG+G+F with the smallest BIC score is the recommended model for the ML tree based on the 35realigned. fas file.Next, click the Phylogeny icon on the main panel of MEGA. Click Construct/Test the Maximum Likelihood Tree and then click Yes on the popup panel. A new window will open showing different parameters that need to be specified.First, set the bootstrap value in the test of the phylogeny box. 500 or 1, 000 is adequate in most cases. Under the Substitution Model, choose amino acid as the substitution type.The purpose of choosing a substitution model is to estimate the true difference between sequences based on their present states. Select LG with Freqs Model in the Model and Method box. In the Rates and Patterns box, select gamma distributed to describe rate variations across sites such as giving more weight to changes at slowly evolving sites.In the Data Subset box, select complete deletion to remove all of the columns containing hyphens. Keep all other parameters in their default states. After specification of these parameters, click the Compute icon to start the calculation.A phylogenetic ML tree will be presented when the computation using MEGA is finished. Under the pull down menu of the File icon on the Tree panel, choose Save Current Session to save the result. In the present study, the result was saved as 35.mas.On the Tree panel, many parameters including length of clade, tree style, tree topology, font of the taxon name, size and color, are displayed and can be set to different options. Save the final tree file by clicking the Image icon and save the figure in different formats or copy the image as the source for photo editing. Proceed with the analysis of the relationship of SWEETs and semiSWEETs as well as using the sequence alignment phylogenetic tree construction with MR Base as detailed in the text protocol.Phylogenetic trees show that all of the first MtN3 saliva domains of the 35 SWEET sequences clustered as one clade and the second MtN3 saliva domains of the SWEET sequences clustered as another clade. In addition, alignment results of the SWEETs and semiSWEETs show that some semiSWEETs from Alpha-Proteobacteria aligned with the first MtN3 saliva domain of the SWEET sequences whereas semiSWEETs from Methanobacteria aligned with the second MtN3 saliva domain of the SWEET sequences. These results together suggest that the two MtN3 saliva domains containing SWEETs might be derived from an evolutionary fusion of a bacterial semiSWEET and an archaean.Once mastered, this technique can be done in one hour to several days depending on the complexity of the data. While attempting this protocol, it is important to collect high-quality sequences in advance. After its development, this protocol paved the way for researchers in evolution to explore the relationships between homologous genes.After watching this video, you should have a good understanding of how to construct a phylogenetic tree.

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15.5K vistas.  China Three Gorges University. This method can help answer key questions in the phytogenetic field such as how to collect sequences and how to select the correct computation model. The main advantage of this technique is that it's very easy to learn. Generally, those who are new to this method may struggle simply because they don't know how to handle the data due to a lack of basic knowledge of the principles and methods of phylogeny.This method was first developed when we analyzed the alignment of eukaryotic SWEET ...