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PLAZA 3.0: an access point for plant 
comparative genomics 
Klaas Vandepoele 
29 September 2014 
VIB – Ghent University, Belgium
Overview 
 Plant genomes: status & challenges 
 Comparative genomics using PLAZA: 
concepts & tools 
 What’s new in PLAZA 3.0 ? 
2
Plant genome sequencing is booming 
 New and faster sequencing 
technologies 
 Generating a draft genome sequence 
has become cheap 
 The number of published plant 
genomes grows exponentially 
 Unlocking biological information is 
the real challenge 
3 Michael & Jackson, 2013
Genome annotation 
 Structural annotation shows 
where genes are 
 Describes their intron-exon gene 
structure 
 Functional annotation tells you 
what genes do 
 Can be downloaded along with the 
genome sequence 
4
Comparative genomics 
 Comparative genomics is a powerful 
tool allowing us: 
 to link genomic changes to 
environmental adaptation 
 to transfer knowledge from model 
species to others plants 
 to trace structural changes within a 
genome trough time 
5
Comparative genomics has a steep learning curve 
 A thorough knowledge of data 
processing tools is required 
 Computer clusters and high memory 
machines are used 
 New visualizations and methods are 
necessary to explore genomic geatures 
across multiple species 
 Limited access to high-quality 
comparative genomics information 
6
http://bioinformatics.psb.ugent.be/plaza/
http://bioinformatics.psb.ugent.be/plaza/
Gene families & genome organization 
Gene family analysis 
Genome analysis 
>20 tools available! 
11
Exploiting cross-species genome information 
 Centralized infrastructure 
 Detailed gene catalog per species 
 Structural annotation (gene models, UTRs) 
 Functional annotation (experimental, sequence-based) 
 Intuitive & advanced data mining tools for non-expert 
users 
• Sequence retrieval 
• Gene functions 
• Genome organization 
• Pathway evolution 
• Data manipulation 
12
13
14
15
16 
Text-mining 
Orthology-based
Comparative sequence analysis 
17 
 Homology = shared ancestral common origin 
 Inferred based on 
 sequence similarity (BLAST) 
 similar (multi-)domain composition & organization 
TAIR 
JGI 
EMBL 
BLASTCLUST 
Tribe-MCL 
Inparanoid 
OrthoMCL 
C/KOG 
All-against-all sequence 
similarity search (BLAST)
Gene families, Multiple sequence alignment & 
Phylogenetic trees 
18 
26K multi-gene families covering 
90% of the total proteome 
>1M proteins from 
31 species 
17K trees incl. 580K 
annotated tree nodes
19
Integrative Orthology Viewer 
•Tree-based orthologs (TROG) inferred using tree reconciliation 
•Orthologous gene families (ORTHO) inferred using OrthoMCL 
•Anchor points refer to gene-based colinearity between species 
•Best hit families (BHIF) inferred from Blast hits including inparalogs
21 
Gene colinearity & genome organization 
Gene Homology Matrix (GHM) 
i-ADHoRe 3.0 
• Represent chromosomes as 
sorted gene lists 
• Identify all homologous gene 
pairs between chromosomes (all-against- 
all BLASTP). 
• Score pairs of homologues in 
matrix 
1 
2
Genome-wide colinearity (WGDotplot) 
22 
O. sativa 
Z. mays
Multi-species colinearity 
23
PLAZA Workbench 
25 
 Create a custom gene set (~experiment) using gene identifiers or 
BLAST 
 External/internal gene IDs (e.g. AN3, AT5G28640, GRMZM2G180246_T01) 
 BLAST interface can be used to map sequence data from a non-model 
species to a reference species present in PLAZA 
 A toolbox is available to analyze user-defined gene sets 
PLAZA 
Workbench 
WGMapping 
Functional 
annotations 
Gene Families 
GO enrichment 
Tandem/block 
duplicates 
Sequence 
retrieval 
Microarray 
transcript profiling 
EST / RNA-sequencing 
Genes reported 
in Suppl. data 
iOrthologs Export data…
26
GO enrichment analysis 
27
What’s new in PLAZA 3.0? 
 New genomes 
 Dicots (13) 
• Gossypium raimondii (cotton), Eucalyptus grandis 
(eucalyptus), Solanum lycopersicum (tomato), Solanum 
tuberosum (potato), Beta vulgaris (sugar beet), Prunus 
persica (peach), Citrus sinensis (sweet orange), Cucumis 
melo (melon), Citrullus lanatus (watermelon) 
• Capsella rubella, Brassica rapa and Thelungiella parvula 
• Amborella trichopoda 
 Monocots (3) 
• Musa acuminata (banana), Setaria italica (foxtail millet) 
and Hordeum vulgare (barley) 
28
What’s new in PLAZA 3.0? 
 Gene function information 
 Free-text gene descriptions 
• Primary data provider + UniProt 
• AnnoMine* text-mining 
 Protein domains 
• InterPro 
 Structured functional annotations 
• Gene Ontology 
• MapMan 
• PlnTFDB and PlantTFDB 
29 * Sofie Van Landeghem
Extended GO projection 
30 
Orthology-based 
Homology-based 
Transfer of experimentally confirmed GO information to orthologs and homologs
Coverage gene function information 
31 
Gene Ontology (Biological Process) 
Gene descriptions 
blue = primary GO; green = GO projection (orthology + homology)
Conclusions 
 PLAZA 3.0 provides a versatile toolbox for plant genomics 
 Integration of complementary data sources describing gene 
functions 
 Improved algorithms to transfer functional annotation from 
well-characterized plant genomes to other species 
 Technical improvements 
 database design 
 comparative genomics tools 
 speed 
 visualizations 
32
33 
Acknowledgments 
• – plant comparative genomics 
 Sebastian Proost 
 Michiel Van Bel 
 Dries Vaneechoutte 
 Yves Van de Peer 
 Dirk Inzé 
plaza_genomics 
http://bioinformatics.psb.ugent.be/plaza/

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PLAZA 3.0 - an access point for plant comparative genomics

  • 1. PLAZA 3.0: an access point for plant comparative genomics Klaas Vandepoele 29 September 2014 VIB – Ghent University, Belgium
  • 2. Overview  Plant genomes: status & challenges  Comparative genomics using PLAZA: concepts & tools  What’s new in PLAZA 3.0 ? 2
  • 3. Plant genome sequencing is booming  New and faster sequencing technologies  Generating a draft genome sequence has become cheap  The number of published plant genomes grows exponentially  Unlocking biological information is the real challenge 3 Michael & Jackson, 2013
  • 4. Genome annotation  Structural annotation shows where genes are  Describes their intron-exon gene structure  Functional annotation tells you what genes do  Can be downloaded along with the genome sequence 4
  • 5. Comparative genomics  Comparative genomics is a powerful tool allowing us:  to link genomic changes to environmental adaptation  to transfer knowledge from model species to others plants  to trace structural changes within a genome trough time 5
  • 6. Comparative genomics has a steep learning curve  A thorough knowledge of data processing tools is required  Computer clusters and high memory machines are used  New visualizations and methods are necessary to explore genomic geatures across multiple species  Limited access to high-quality comparative genomics information 6
  • 9.
  • 10.
  • 11. Gene families & genome organization Gene family analysis Genome analysis >20 tools available! 11
  • 12. Exploiting cross-species genome information  Centralized infrastructure  Detailed gene catalog per species  Structural annotation (gene models, UTRs)  Functional annotation (experimental, sequence-based)  Intuitive & advanced data mining tools for non-expert users • Sequence retrieval • Gene functions • Genome organization • Pathway evolution • Data manipulation 12
  • 13. 13
  • 14. 14
  • 15. 15
  • 17. Comparative sequence analysis 17  Homology = shared ancestral common origin  Inferred based on  sequence similarity (BLAST)  similar (multi-)domain composition & organization TAIR JGI EMBL BLASTCLUST Tribe-MCL Inparanoid OrthoMCL C/KOG All-against-all sequence similarity search (BLAST)
  • 18. Gene families, Multiple sequence alignment & Phylogenetic trees 18 26K multi-gene families covering 90% of the total proteome >1M proteins from 31 species 17K trees incl. 580K annotated tree nodes
  • 19. 19
  • 20. Integrative Orthology Viewer •Tree-based orthologs (TROG) inferred using tree reconciliation •Orthologous gene families (ORTHO) inferred using OrthoMCL •Anchor points refer to gene-based colinearity between species •Best hit families (BHIF) inferred from Blast hits including inparalogs
  • 21. 21 Gene colinearity & genome organization Gene Homology Matrix (GHM) i-ADHoRe 3.0 • Represent chromosomes as sorted gene lists • Identify all homologous gene pairs between chromosomes (all-against- all BLASTP). • Score pairs of homologues in matrix 1 2
  • 22. Genome-wide colinearity (WGDotplot) 22 O. sativa Z. mays
  • 24. PLAZA Workbench 25  Create a custom gene set (~experiment) using gene identifiers or BLAST  External/internal gene IDs (e.g. AN3, AT5G28640, GRMZM2G180246_T01)  BLAST interface can be used to map sequence data from a non-model species to a reference species present in PLAZA  A toolbox is available to analyze user-defined gene sets PLAZA Workbench WGMapping Functional annotations Gene Families GO enrichment Tandem/block duplicates Sequence retrieval Microarray transcript profiling EST / RNA-sequencing Genes reported in Suppl. data iOrthologs Export data…
  • 25. 26
  • 27. What’s new in PLAZA 3.0?  New genomes  Dicots (13) • Gossypium raimondii (cotton), Eucalyptus grandis (eucalyptus), Solanum lycopersicum (tomato), Solanum tuberosum (potato), Beta vulgaris (sugar beet), Prunus persica (peach), Citrus sinensis (sweet orange), Cucumis melo (melon), Citrullus lanatus (watermelon) • Capsella rubella, Brassica rapa and Thelungiella parvula • Amborella trichopoda  Monocots (3) • Musa acuminata (banana), Setaria italica (foxtail millet) and Hordeum vulgare (barley) 28
  • 28. What’s new in PLAZA 3.0?  Gene function information  Free-text gene descriptions • Primary data provider + UniProt • AnnoMine* text-mining  Protein domains • InterPro  Structured functional annotations • Gene Ontology • MapMan • PlnTFDB and PlantTFDB 29 * Sofie Van Landeghem
  • 29. Extended GO projection 30 Orthology-based Homology-based Transfer of experimentally confirmed GO information to orthologs and homologs
  • 30. Coverage gene function information 31 Gene Ontology (Biological Process) Gene descriptions blue = primary GO; green = GO projection (orthology + homology)
  • 31. Conclusions  PLAZA 3.0 provides a versatile toolbox for plant genomics  Integration of complementary data sources describing gene functions  Improved algorithms to transfer functional annotation from well-characterized plant genomes to other species  Technical improvements  database design  comparative genomics tools  speed  visualizations 32
  • 32. 33 Acknowledgments • – plant comparative genomics  Sebastian Proost  Michiel Van Bel  Dries Vaneechoutte  Yves Van de Peer  Dirk Inzé plaza_genomics http://bioinformatics.psb.ugent.be/plaza/