COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP. Exercise 3: Pan- and Core- genome analysis, Pan-genome tree

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1 COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP Exercise 3: Pan- and Core- genome analysis, Pan-genome tree 1. Pan- and Core- genome plot construction Pan- and core-genome plots are graphs that display to what extent gene familes are conserved within a set of genomes. Conservation is evaluated by first BLASTing the proteomes of the genomes against each other. This is done in a certain order, in that for every proteome, it performs a BLAST search against all previous proteomes. The result is a set of numbers specific for that time point that represents the proteome in the order of the input list, showing: Number of new genes Number of new families Size of core genome Size of pan genome Two genes are considered to belong to the same gene family if the two are more than 50% identical over more than 50% of the length of the longest of the two genes. You will use the script coregenome-2.7c.pl. This script takes a list of proteomes, uses blast search for the gene families and derives the number of core and pan proteins for each proteome. The output list will then be redirected into an R-script, which plots all the core/pan values as a function of the proteome number. Just like the BLAST matrix script you tried the other day, this script will cache all the BLAST results. If you would like to change the order of the analysed proteomes in the plot, all BLAST searches must be carried out once again. In the event you change the order of the input proteins, all BLAST searches must be carried out again. However, all the blast results should be stored in the memory after you ran them once and then it won t take much time to produce a plot with new order of proteomes. Similarly like two days before log in to CBS computers: Open ssh shell client. Press Quick connect. Host name: organism.cbs.dtu.dk User name: studxx stud137 stud138 stud139 stud140 stud141 stud143 stud144 stud145 stud146 stud147 stud148 Escherichia Salmonella Cyanobacteria Bifidobacterium Lactic Acid Bacteria Bacteroidetes Chlorobi Clostridium Bacillus Mycobacterium Archaea

2 stud149 stud150 stud151 stud152 Brucella Pseudomonas Rhodobacter and Rhizobium Staphylococcus Password: V2Gubeso Press New terminal Window icon to open working Terminal window. Connect to another server called life: ssh X Y life The password is all the time the same Change directory to the one containing all the.orf.fsa files: cd PROTEINS Make a list of genomes for analysis foreach i ( *.fsa ) echo $i:r:r../proteins/$i >>../BLAST/PanCorePlot.cf Change directory to the one where you will be storing the analysis results in. Let say it will be the same BLAST directory you created in last exercise. Find the configuration file called PanCorePlot.cf file (less PanCorePlot.cf). You should see two tab separated columns, one contains name of the strain and the other proteome file. You will change the names to more nice ones. cd../blast/ perl -pi -e 's/ /\t/g' PanCorePlot.cf perl -pi -e 's/\_prodigal\t/\t/g' PanCorePlot.cf less PanCorePlot.cf Did anything change? Final step is to run pan-/core-genome plot construction. We once again will try to run it on the server, but not on queuing system. Command looks like this. Remember the command is too big, so it didn t fit in one line. ~carsten/scripts/coregenome/coregenome-2.7c.pl -keep PanCorePlot_v27_memory PanCorePlot.cf > PanCorePlot_v27.ps -keep function saves all proteome blast all-against-all memory to a directory, which can be used afterwards for Microarray probes design. When job is done, similarly as for blastmatrix open it with gs, gv or ghostview ghostview PanCorePlot_v27.ps The names on the figure might not fit and is difficult to read. In this case you can run plot once again using another, older version of the script coregenome-2.3.pl. The command for this looks like this:

3 ~carsten/scripts/coregenome/coregenome-2.3.pl PanCorePlot.cf > PanCorePlot_v23.ps It shouldn t take a lot of time, since the blasting information will be taken from the memory. Question: Look at the plot. Can you tell how many gene families, approximately, your genomes have in common? How many gene families are there in total for your genomes? 2. Pan-genome tree Pan-genome tree is the tree based on the genes present/absent in pan-genome of all the genomes. There are several ways of doing it. Return to your home directory: cd Copy pan-genome tree making package and extract files from it: cp ~stud137/pantree_organism.tar. tar xvf pantree_organism.tar Enter the directory in which you should find useful scripts and files: cd pantree_organism/organism/blast Copy all the earlier predicted proteomes files here: cp home/people/studxx/proteins/*.fsa. There you will use small useful script which is helpful to make a tab separated configuration file. Configuration file should contain 3 columns: GID File Name, where GID (Genome ID) is used for computational purposes, File is an.fsa file containing proteomes for each of the genomes and Name is a genome, which will be illustrated on the resulting tree. perl ~oksana/perl/pantree_mapping.pl Look into the resulting configuration file to be sure it contains the earlier described columns and if all the genomes are present there. less organism_mapping.txt PLEASE DON T DO NEXT STEPS, JUST READ WHAT YOU WOULD BE DOING IF YOU WOULD HAVE MUCH MORE TIME. You would start running all-against-all blast search to achieve the information of differences and similarities between the proteomes. For this purpose R-scripts were written. Start R installed on the CBS machines:

4 R-2.9 script_fastaprep.r will renames the proteomes files to the one containing GID next to each of the genome. And script_blastall.r will prepare submission to queueing system files. source("script_fastaprep.r") source("script_blastall.r") q() mkdir database mv *blastdb* database/ The following foreach loop prepares submission to the queueing system files for each of the proteome. This runs actuall all-against-all blast. foreach i ( *.fsa_xmsub ) perl ~oksana/perl/pantree_qsub.pl $i > $i:r.qsub foreach i (*.qsub) msub -d /home/people/studxx/pantree_organism/organism/blast/ - lncpus=2,mem=10gb,walltime=5:00:00 /home/people/studxx/pantree_organism/organism/blast/$i INSTEAD YOU WILL COPY BLASTING FILES FROM THE PREVIUOSLY MADE DATABASE AND CONTINUE THE TREE MAKING PLAN. Believe me you want to do it like this, in order not to sp time in the dark and cold campus, next to ponds full of strange creatures. cp /home/people/studxx/organism/pantree/organism/blast/res/*.txt /home/people/studxx/pantree_organism/organism/blast/res Check the number of the blast results you copied. It should be equal to squared number of analysed genomes. If it not, ask Oksana for help. lt res/*.txt wc Now you are ready to run pan matrix formation. The matrix will contain information about the gene presence or absence in the genome. If the gene is present the matrix cell will state 1, and 0 in other case. Once again several R- scripts are prepared for this purpose. R-2.9 source( script_panmatrix.r ) You will the pan-matrix calculation process in the window. In this case you will have to wait until it is done and you can once again see > sign in the beginning of the command line. When it is done, run another R-script, which builds a tree

5 from the pan-matrix. Make sure X-ming (for Windows) and X11 (for Mac) iare installed and running at the moment on your computer. First the script will visualize the tree in newly opened X11 window and then bootstrapping will be done. source( script_pantree.r ) The tree is considered to be done when the red bootstrap numbers appeared on the tree. To save the tree do following: dev.copy(device = postscript, file = "pangenomeplot.ps") dev.off() Quir R program: q() Questions: Compare pan-genome tree to the 16S rrna tree you have done before. Which tree illustrates what? Are they different? If yes, why?