Fondation Merieux J Craig Venter Institute Bioinformatics Workshop. December 5 8, 2017

Transcription

1 Fondation Merieux J Craig Venter Institute Bioinformatics Workshop December 5 8, 2017

2 Module 5: Comparative Genomics Analysis

3 Outline Definition of comparative genomics Applications in studying human pathogens Analysis tools Case studies

4 Comparative Genomics comparing genomes of different species for illuminating evolutionary mechanisms and forces for informing the understanding of the human genome conserved vs unique characteristics

5 A comparison of general features of genomes Touchman, J. (2010) Comparative Genomics. Nature Education Knowledge 3(10):13

6 A comparison of chromosomal changes Conserved segments in the human and mouse genome Human chromosomes, with segments containing at least two genes whose order is conserved in the mouse genome as color blocks. Each color corresponds to a particular mouse chromosome. (International Human Genome Sequencing Consortium; Lander, E. S. et al. 2001)

7 Applications in Studying Human Pathogens how genomic diversity is changing over time whether evolution occurs indigenously determination of the impact of introduced strains versus indigenous evolution on disease outcomes. identify genes experiencing strong positive selection viral determinants to disease severity viral adaptive drivers the role of quasispecies in disease pathogenesis vaccine development is dependent on understanding of genetic diversity universal vaccines specific vaccines: against pathogens closely related to commensal microorganisms

8 Comparative Genomics Analysis Tools whole genome comparison UCSC Browser: a large collection of genomes Ensembl: eukaryotic genomes offering tools for developing testable hypotheses

9 Analysis and Visualization Tools

10 Analysis & Visualization

11 Private Workbench

12 Workbench

13 Tight Integration of Data and Analysis Tools metadata coloring ~730,000 animal surveillance records ~14,000 virus protein structures overlapped with pre-computed SNP scores, Sequence Features systems biology data and analysis ~2000 personal workbench accounts viral protein Sequence Features

14 Case study: Influenza virus antigenic variations in Sa epitope

15 Background Antigenic variation allows pathogens to escape from immunity Caton (1982): Sa epitope

16 Sequence Feature Variant Types (SFVT)

17 Sequence Features knowledge base of characterized regions: markers used in diagnosis genetic determinants for host range, virus virulence, replication efficacy epitopes structural elements developed to support analysis of characterized regions systematically annotated Sequence Features (SFs) allows you to compare strains at the SF level

18 5,608 Curated Sequence Features for Influenza Virus Sequence Features of Influenza A & B proteins Influenza A Protein Influenza B Protein Subtype Structural SFs Functional SFs Epitopes Sequence Alterations Total no. of SFs 1 PB PB PB1 F PA HA All 1541 H H H H4 1 1 H H H H H NP NA All 756 N N N3 4 4 N5 2 2 N6 2 2 N7 1 1 N8 6 6 N M M N NS NS NA 8 8

19 Sequence Feature Variant Types Tutorial This component of IRD provides data on specific characteristic regions and/or sub regions termed 'Sequence Features' (SF) defined for all influenza virus proteins. The SFs and their metadata are derived from scientific literature and/or public domain databases. Variant types (VT) of SFs are computed by multiple sequence alignments of all relevant protein sequences in IRD. Variant types that carry a mutation(s) that has been experimentally determined to give rise to a phenotype, such as increased virulence are denoted as a Phenotype Variant Type (PVT). These PVT annotations are only available for a subset of the influenza virus subtypes. For more information about these PVT annotations, click here. Note: VT 1 is not always a functional epitope. For more information about using SFVTs, click here. For a detailed description of the development and application of the SFVT approach for the study of influenza virus, please read this scientific article: Noronha JM, Liu M, Squires RB, Pickett BE, Hale BG, Air GM, Galloway SE, Takimoto T, Schmolke M, Hunt V, Klem E, García Sastre A, McGee M, Scheuermann RH. (2012) Influenza Sequence Feature Variant Type (Flu SFVT) analysis: evidence for a role of NS1 in influenza host range restriction. J Virol, 86: doi: /JVI PMID: Go to Sequence Feature List Results matching your criteria: 105 VIRUS TYPE A B C SEQUENCE FEATURE TYPE SUBTYPE FOR HA AND NA H1 * Use comma to separate multiple entries. Ex: H1, H3, H7, N1, N2. SELECT SEGMENTS AMINO ACID COORDINATES Start: To: IMMUNE RECOGNITION CONTEXT FOR EPITOPE TARGET MHC CLASS HOST MHC ALLELE Ex. HLA A*02:01, HLA A2, H 2 Kb, Mamu A, SLA 1*04, BoLA DRB, Patr DR KEYWORD SEARCH * Use comma to separate multiple entries. Ex: alpha helix, Beta strand, IEDB: Clear Search

20 SEQUENCE FEATURE DEFINITION Protein Name Sequence Feature Name Sequence Feature ID Reference Strain Reference Sequence Accession Reference Position HA Influenza A_H1_antigenic site Sa_141(9) Influenza A_H1_SF42 A/California/04/2009(H1N1) FJ (124 HA1),142(125 HA1),172(155 HA1),174(157 HA1),176(159 HA1),177(160 HA1),179(162 HA1),180(163 HA1),181(164 HA1) SOURCE STRAIN(S) Source Strain A/Puerto Rico/8/34(H1N1) VT Number Source Position Source Accession 3D Protein Structure VT ,142,171,173,175,176,178,179,180 CY AL4, 3LZG, 3UBE, 3UBJ, 3UBN, 3UBQ, 3UYW, 3UYX, 3ZTN, 4JTV, 4JTX, 4JU0, 4M4Y Publication Epitope Type Evidence Codes PubMed: B Cell EXP P141, N142, E171, S173, P175, K176, K178, N179, S180 Epitope Sequence Comment Sites Sa and Sb are in the upper part of the HA1 globular head. Sa occurs in the front region. VARIANT TYPES VARIANT Excel Download TYPES FASTA Download View Phylogenetic Tree Find a VT(s) There Excel are 424 Download variant types, but FASTA only 100 Download with the highest strain View counts Phylogenetic are displayed. Tree Find a VT(s) There are 424 variant types, but only 100 with the highest strain counts are displayed. Sequence Variation Strain Count Variant Type Strain Count Variant VT 1 Type 6600 VT VT VT VT VT Sequence 176 Variation P 142 N 172 G 174 S 176 P 177 K 179 S 180 K 181 S N L N P N G S P K S K S N N L N D Total Variations Total Variations

21 Variations in the Sa epitope VARIANT TYPES Excel Download Find a VT(s) Phylogenetic tree view disabled because there are not enough variant types to generate the tree. There are 424 variant types, but only 421 with the highest strain counts are displayed. Edit specific positions in this VT 1 sequence with IUPAC symbols or use "?" as a wild card. If necessary, use the horizontal scroll bar to access the entire SF. Click Search to find VT(s) conforming to the edited sequence. Click Reset to restore this panel to the default VT 1 sequence. Search Reset Fill wildcards 141? 142? 172? Enter Sequence Variation to Find 174? 176? 177? 179? 180 Q 181? Sequence Variation Strain Count Variant Type VT VT VT 21 5 VT P N G S P K S K S Q N Q N L N Q Total Variations

22 Sa epitope polymorphism In flu seasons VT-1 is the dominant VT some have VT9 In flu season VT-9 is the dominant VT High immune pressure at Q has been positively selected.

23 Summary SFVT supports comparative analysis of characterized regions at the strain level Sequences change under directional selection, a process whereby natural selection favors a single phenotype and continuously shifts the allele frequency in one direction.

24 Case study: Influenza H3N2 viruses, Netherlands,

25 Influenza Cases in Eight European Countries Figure 5. Number of influenza cases admitted to ICUs by type and subtype in eight EU/EEA countries, seasons to H3N2: many severe cases Risk-assessment-seasonal-influenza update.pdf

26 Questions Explore the evolution of human H3N2 viruses in Netherlands in the past three flu seasons. Predict whether the current vaccine would be protective against the most recent viruses.

27 Sequence Variation Analysis Workflow Prepare sequence data and metadata Align sequences and check quality Construct a phylogenetic tree and explore phylogeny-metadata association Identify the unique genetic substitutions of the viruses Determine if the substitutions are located in antigenic regions

28 Personal Workbench

29 Support of user provided sequence data/metadata SEARCH DATA ANALYZE & VISUALIZE WORKBENCH SUBMIT DATA HELP Upload Data and Associated Metadata UPLOAD DATA Name * H3N2_Netherlands Description File Type * File Path * H3N2_Nether refs.fasta UPLOAD SEQUENCE ASSOCIATED METADATA (OPTIONAL) IRD supports metadata based phylogenetic tree node coloring and metadata based sequence group comparison by meta CATS. If you want to use these functionalities, you need to provide sequence associated metadata by using one of the following options: Option 1: Provide metadata in defline in my uploaded FASTA file Option 2: Provide metadata in a completed metadata template Step 1: Step 2: Step 3: Download Metadata Template Fill out the template according to instruction in comments. Upload Metadata Spreadsheet H3N2_Nether adata.xlsx Cancel Upload

30 vaccine 3C.1 3C.3a 3C.3b vaccine 3C.2a 3C.2a1

31 Comparing 3C.2a1 ( ) with others Metadata-driven Comparative Analysis Report (Ticket# MG_ ) Save Analysis Generate Phylogenetic Tree Visualize Aligned Sequences Download The Metadata driven Comparative Analysis Tool (meta CATS) (SOP) consists of three parts: a multiple sequence alignment (using MUSCLE), a chi square test of independence to identify positions (columns) of the multiple sequence alignment that significantly differ from the expected (random) distribution of residues between all metadata groups, and a Pearson's chi square test to identify the specific pairs of metadata groups that contribute to the observed statistical difference. When 3 or more groups are included in the analysis, the P value from the test of independence will identify columns having significant variation between all groups, while the Pearson's test will identify the specific pair(s) of groups that make the column significant (i.e. if those groups were not included in the analysis, the column would no longer be identified as significant). The (View SF) link associates each position with the Sequence Feature (SF) page. Note that this link is visible only if SFs overlap with the protein position exist and if the sequence data being analyzed belongs to the same viral species, type, or subtype. Chi square Test of Independence Result There are 15 positions that have a significant non random distribution between the specified groups. "*" in position column indicates fewer than 5 non zero residues in any cell of the contingency table. Group1: merged group Group2: merged group Position Chi square Value P value Degree Freedom Residue Diversity E 4 3 group1(12 C) group2(5 T) E 4 3 group1(12 A) group2(5 G) E 4 3 group1(12 C) group2(5 T) E 4 3 group1(12 T) group2(5 G) group1(10 A) group2(5 G) group1(10 A) group2(5 G) group1(10 G) group2(5 A)

32 Comparing 3C.2a1 ( ) with others 3C.2a1 other 3Cs

33 Sequence Feature Details (SOP) For more information about using SFVTs, click here. For a detailed description of the development and application of the SFVT approach for the study of influenza virus, please read this scientific article: Noronha JM, Liu M, Squires RB, Pickett BE, Hale BG, Air GM, Galloway SE, Takimoto T, Schmolke M, Hunt V, Klem E, García Sastre A, McGee M, Scheuermann RH. (2012) Influenza Sequence Feature Variant Type (Flu SFVT) analysis: evidence for a role of NS1 in influenza host range restriction. J Virol, 86: doi: /JVI PMID: SEQUENCE FEATURE DEFINITION Protein Name Sequence Feature Name Sequence Feature ID Reference Strain Reference Sequence Accession Reference Position HA Influenza A_H3_experimentally determined epitope_421(30) Influenza A_H3_SF240 A/Aichi/2/1968(H3N2) AB (76 HA2) 450 SOURCE STRAIN(S) Source Strain A/Hong Kong/1/1968(H3N2) VT Number Source Position VT Source Accession CY D Protein Structure 1EO8, 1HA0, 1HGG, 1HTM, 1KEN, 1QFU, 1QU1, 2HMG, 2VIU, 2YPG, 3EYM, 3HMG, 3VUN, 4HMG, 5HMG Publication Epitope Type Evidence Codes Epitope Sequence Comment IEDB: B Cell N/A RIQDLEKYVEDTKIDLWSYNAELLVALENQ N/A VARIANT TYPES Excel Download FASTA Download View Phylogenetic Tree Find a VT(s) There are 182 variant types, but only 100 with the highest strain counts are displayed. VT-10 97% from the recent 3 seasons. consistent with Meta-CATS result. Strain Count Variant Type VT VT 2 2 VT 3 62 VT VT 5 15 VT 6 56 VT 7 20 VT 8 33 VT VT 10 Sequence Variation Total Variations R I Q D L E K Y V E D T K I D L W S Y N A E V G R D I V N

34 Summary The rapid evolution of the virus and the importance of monitoring whether antigenic drift would alter antigenicity. A/Texas/50/2012, the vaccine strain selected for the and flu seasons represents clade 3C.1. However, strains circulating in and fall into new clades of 3C.3a, 3C.3b and 3C.2a. A/Hong Kong/4801/2014, the vaccine strain selected for the season belongs to 3C.2a. However, the majority of the isolates form a new subclade 3C.2a1 within 3C.2a. Meta-CATS comparison identified 15 substitutions that distinguish the newly emerged 3C.2a1 subclade from the older clades. Further experiments need to be conducted to see whether the substitutions found in the most recent isolates have altered antigenicity.

35 Case study: Zika viruses in Southeast Asia

36 Why did not ZIKV viruses in Southeast Asia cause outbreaks and microcephaly on a large scale? recent ZIKV has been circulating since 2010 overlooked or falsely detected due to the fact that ZIKA diagnosis (primers), clinical presentations and managements are the same as DENV cases no report of outbreaks or microcephaly Africa Southeast Asia Pacific Islands South America Potential selective signatures Figure 2. Amino acid residues of the pr peptide that are unique in the South American ZIKV isolates. Model was based on DENV pr peptide (3C5X). Figure 1. Phylogenetic analysis of Southeast Asian and South American ZIKV branches