Special Topics: 2009 Swine-flu Informatics

Transcription

1 Special Topics: 2009 Swine-flu Informatics Gloria Rendon SC11 Education June, 2011

2 The swine-flu epidemic of 2009 The seminal study done at the time was published in this article: Smith GJD, Vijaykrishna D, Bahl J, Lycett SJ, Worobey M, Pybus OG, Ma SK, Cheung CL, Raghwani J, Bhatt S, Peiris JSM, Guan Y, Rambaut A. Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic. Nature 2009; 459: We will focused on parts of the report that should make more sense to us in light of what we discussed in this workshop.

3 Reconstructing Events that lead to the emergence of the viruses responsible for outbreak

4 We will focus on: GENOMICS. Genome alignment. The study included genomes of H1N1 and H3N2 flu viruses. We will see how similar they are after we align their genomes. PROTEOMICS. The study also broke down differences at the protein level. We will reconstruct the gene trees for these H1N1 proteins: HA, M1, NCAP NS, PB1. We will not replicate the study; instead we will replicate the methodology they used with a smaller sample of the data.

5 The 2009 flu epidemic: genomics GENOMICS. Genome alignment. The study included genomes of H1N1 and H3N2 flu viruses. We will see how similar they are after we align their genomes. PROTEOMICS. The study also broke down differences at the protein level. We will reconstruct the gene trees for these H1N1 proteins: HA, M1, NCAP NS, PB1. We will not replicate the study; instead we will replicate the methodology they used with a smaller sample of the data.

6 Genome-wide Alignment Traditional alignment methods do not scale up well to cope with genome sizes A combination of methods is a common strategy used by most tools that perform genome-wide alignment (pair-wise and multiple genome alignment) Human intervention during the alignment process is also possible or even expected when aligning two or more genomes

7 Multiple Genome Alignment: General Strategy 1. Anchoring: Identify reference genome. Identify and align Anchors: anchor alignments are local alignments of high identity and high information content 2. Seeding: Form collinear regions by aggregating anchors that occur in the same order in 2 or more genomes. Then assign a significance score to each collinear region. 3. Align genomes using weighted collinear regions. Special cases like missing regions, embedded regions, repeats or palindromes in some genomes may not be part of the algorithm of choice.

8 Mauve 1. Identify LMAs (local multiple alignments) 2. Use LMAs to compute pairwise distance matrix with genomes 3. Infer anchoring tree 4. Anchor nearest unaligned sequences in tree 5. Perform recursive anchor search 6. Perform global anchored search 7. Evaluate alignment in all genomes

9 Using Mauve with Bacterial Genomes (E coli, Shigella and Salmonella) Each genome occupies three lines: 1. Position ruler 2. Color-coded block Alignment 3. Species Lines connect corresponding alignments in two genomes The additional alignment line appears when a palindrome occurs By default, the first genome is the reference genome

10 Exercise 1: H1N1 flu genomes a) Aligning very similar genomes, all segments in each genome are in the correct order. Mauve will display long stretches of matched LMAs. b) Aligning same genomes with shuffled segments. Mauve will display dense lattices of connecting lines between genomes.

11 Exercise 1.a: H1N1 flu genomes 1. Start the Mauve application by double-clicking on its icon located on your desktop. 2. Load the genomes to align. click File from the menu bar and Align with Progressive Mauve from the pull down menu. The dialog window appears, click on Add sequence. To select the files, go to the exercises folder. There is a genome per file. Select the genomes with file names that end with inorder.gb these genomes have all segments in the correct order and they are in Genbank format.

12 Exercise 1.a: H1N1 flu genomes 3. There are two additional tabs in the dialog box for input parameters and scoring matrices. We will use the default values for all those options. 4. Type the name of the output file 5. Click on the Align button and wait for the alignment to be computed.

13 Exercise 1.a: H1N1 flu genomes 6. Examine the resulting Alignment. Zoom-in by clicking on the magnifying icon

14 Exercise 1.a: H1N1 flu genomes 6. Examine the resulting Alignment. Click on the alignment itself to see the corresponding annotation. In this case, location 6664, is the PA protein. You can also change the Reference Genome by clicking in its corresponding R

15 Exercise 1.b: H1N1 flu genomes Repeat the same steps with the H1N1 genomes that are not in order. Their names end in H1N1.genome.notSorted.GB Remember to include the reference (in order) genome in the list too. Warning: the execution of the alignment will take considerably more time.

16 Exercise 1.b: H1N1 flu genomes In this case we have aligned three H1N1 genomes. Two genomes have all their segments in order and one does not. Can you guess which one is which?

17 Exercise 1.b: H1N1 flu genomes In this case we have aligned five H1N1 genomes.(two with sorted segments and three with unsorted segments in their genomes)

18 Exercise 1.b: H1N1 flu genomes Notice that the conserved regions (called here LCB) cover almost the length of each genome (no gaps between colored blocks). Also noticed their shift in position from one genome to the next one. Try using the LCB ruler to change the weight values assigned to the LCBs and see how it changes the alignment.

19 Exercise 1.b: H1N1 flu genomes We can also take a closer look at the SNPs (single nucleotide polymorphism). On the Menu bar click on Tools/Export/Export SNPs. A text file will be created with the SNPs information. Let us examine it closely. Go back to alignment and check. First line: aggga,45,21,21,11105,20 means: a -> position 45 in first genome g -> position 21 in second genome g -> position 21 in third genome g -> position in fourth genome a -> position 20 in fifth genome

20 Exercise 2: other flu genomes In the same folder where the H1N1 genomes are located, we also placed other flu genomes, namely, H3N2, H2N2, and H9N2. Align these flu genomes with the H1N1 reference genome and compare alignment with the results we obtained in exercise 1 (with H1N1 genomes only). Are there longer or shorter LCBs? Are there more or fewer gaps between LCBs? Can you find among the LCBs repeats and palindromes? Which genome seems most similar to that of H1N1? Which one is most dissimilar?

21 The 2009 flu epidemic: proteomics GENOMICS. Genome alignment. The study included genomes of H1N1 and H3N2 flu viruses. We will see how similar they are after we align their genomes. PROTEOMICS. The study also broke down differences at the protein level. We will reconstruct the gene trees for these H1N1 proteins: HA, M1, NCAP NS, PB1. We will not replicate the study; instead we will replicate the methodology they used with a smaller sample of the data.

22 The 2009 flu epidemic: proteomics Let us start by looking at each protein; its structural and functional features. We will examine them in the reference species: (strain A/Puerto Rico/8/1934 H1N1) Open a browser in the Uniprot url: Click on the Retrieve tab. In the UniProt Identifiers box type the five accession numbers given in this table. Click on Retrieve. Select UniProtKB and examine the page for each protein: Protein Name M1 PB1F2 H (hemagglutinin) NS1 N (nucleoprotein) Protein Accession P03485 P0C0U1 P03452 P03496 P03466

23 Protein details in UniProt The content of most columns in this summary page is self-explanatory. The last column InterPro contains the functional domain features of the protein; each line displays a separate functional domain. Open each one in a separate tab.

24 Protein details in UniProt All FIVE proteins have been crystallized and we can examine their structures. Click on any of the five entries displayed in the previous slide. Once you get to the protein page scroll down until you reach the Cross-references section. It provides links to external databases that also have information about this protein. Click on the link(s) included in the subheading 3d structure databases

25 Protein details in UniProt If we click on the link 2HN8, in the previous page, it will take us to another database, PDB, and it will open the page that corresponds to the structure with PDB identifier: 2HN8. This is such structure.

26 Gene Trees Now, let s turn our attention to detecting variations of each one of those proteins in different species. The exercise folder contains the five fasta files of these proteins. For example, the file H1N1.M1.fasta has the M1 protein of different H1N1 samples. Construct a gene tree for each protein as follows: a) calculate multiple sequence alignment using ClustalW or muscle, b) use the alignment to calculate the tree using puzzle or protpars

27 Gene Trees Open the browser on the mobyle web server mobyle.pasteur.fr On the Programs box (on the left hand side) select alignment/multiple/clustalw-multialign In the clustalw input box (on the right hand side) locate the sequence file frame, then click on the upload tab, then click on the Choose file button. Select one of the H1N1.*.fasta files in the exercise folder. Then click on the Run button located on the top of the page. When the results are ready. Go to the results page and locate the frame alignment file ; such frame has the box that displays the results and below it click on pull-down box next to the further analysis button. Select puzzle from the list; then click on further analysis. The results of the alignment are loaded up on the puzzle input page. Click on the Run button to execute the command and wait for the results. To view the tree in graphical form click on view with archaeopteryx. The tree is the gene tree for the selected protein. Repeat these steps with the other four proteins. Do the five trees match?

28 Gene Tree of H1N1-HA This is the gene tree for the HA protein. 17 H1N1 species are represented. Five of them diverged earlier than the rest. Labels stemming from the same straight line are identical to each other

29 Additional Resources Download site for Mauve: Darling AE, Mau B, Perna NT. progressivemauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement. PLoS ONE 2009; 5:e11147 Smith GJD, Vijaykrishna D, Bahl J, Lycett SJ, Worobey M, Pybus OG, Ma SK, Cheung CL, Raghwani J, Bhatt S, Peiris JSM, Guan Y, Rambaut A. Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic. Nature 2009; 459: Genomics of Emerging Infectious Disease: 2F %2Fissue.pcol.v01.i01