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UNIVERSITY OF
CALIFORNIA

An introduction to Web Apollo.
A webinar for the i5K Pilot Species Projects
Monica Munoz-Torres, PhD
Biocurator & Bioinformatics Analyst | @monimunozto
Genomics Division, Lawrence Berkeley National Laboratory

04 February, 2014
Outline
An introduction to
Web Apollo.
A webinar for the i5K
Pilot Species Projects.

1. What is Web Apollo?:
• Definition & working concept.
2. Community based curation from our
experience.
3. Lessons Learned.
4. Becoming acquainted with Web
Apollo.

Outline

2
What is Web Apollo?
• Web Apollo is a web-based genomic annotation editing

platform.
We need annotation editing tools to modify and refine the
precise location and structure of the genome elements that
predictive algorithms cannot yet resolve automatically.

Find more about Web Apollo at
http://GenomeArchitect.org
and
Genome Biol 14:R93. (2013).

1. What is Web Apollo?

3
Brief history of Apollo*:
Biologists could finally visualize computational analyses and
experimental evidence from genomic features and build
manually-curated consensus gene structures. Apollo became a
very popular, open source tool (insects, fish, mammals, birds, etc.).
a. Desktop:
one person at a time editing a
specific region, annotations
saved in local files; slowed down
collaboration.

*

b. Java Web Start:
users saved annotations directly
to a centralized database;
potential issues with stale
annotation data remained.
1. What is Web Apollo?

4
Web Apollo
• Browser-based; plugin for JBrowse.
• Allows for intuitive annotation creation and
editing, with gestures and pull-down menus to
create transcripts, add/delete/resize
exons, merge/split exons or transcripts, insert
comments
(CV, freeform text), etc.
• Customizable rules and
appearance.

• Edits in one client are
instantly pushed to all other
clients.
1. What is Web Apollo?

5
Our Working
Concept

In the context of gene manual annotation,
curation tries to find the best examples
and/or eliminate (most) errors.
To conduct manual annotation efforts:

Automated gene models

Evidence:
cDNAs, HMM domain
searches, alignments with
assemblies or genes from other
species.
Manual annotation & curation

2. In our experience.

Gather and evaluate all available evidence
using quality-control metrics to
corroborate or modify automated
annotation predictions.
Perform sequence similarity searches
(phylogenetic framework) and use
literature and public databases to:
• Predict functional assignments from
experimental data.
• Distinguish orthologs from paralogs,
and classify gene membership in
families and networks.
6
Dispersed, community-based gene
manual annotation efforts.
Using Web Apollo, we* have trained
geographically dispersed scientific
communities to perform biologically
supported manual annotations, and
monitored their findings: ~80
institutions, 14 countries, hundreds of
scientists, and gate keepers.
– Training

workshops and geneborees.
– Tutorials with detailed instructions.
*Collaboration with Elsik Lab,
Hymenoptera Genome
– Personalized user support.
Database.
2. In our experience.

7
What have we learned?
Harvesting expertise from dispersed researchers who
assigned functions to predicted and curated peptides,
we have developed more interactive and responsive
tools, as well as better visualization, editing, and
analysis capabilities.
Assessment:

1. Was it helpful / productive to work together?
2. Were manual annotations improved?
3. Did the shared and distributed annotation effort help improve the quality
of scientific findings?

3. Lessons Learned

8
It is helpful to work together.
Scientific community efforts bring together domainspecific and natural history expertise that would have
otherwise remain disconnected.

3. Lessons Learned

9
Improved Automated Annotations*
In many cases, automated annotations have been
improved.
Also, learned of the challenges of newer sequencing
technologies, e.g.:
– Frameshifts and indel errors
– Split genes across scaffolds
– Highly repetitive sequences

To face these challenges, we train annotators in
recovering coding sequences in agreement with all
available biological evidence.
3. Lessons Learned

10
Understanding the evolution of sociality.

… groups of
communities
have taught us a
lot!

Comparison of the genomes of 7 species of
ants contributed to a better understanding
of the evolution and organization of insect
societies at the molecular level.
Insights drawn mainly from six core aspects of
ant biology:
1. Alternative morphological castes
2. Division of labor
3. Chemical Communication
4. Alternative social organization
5. Social immunity
6. Mutualism

Libbrecht et al. 2012. Genome Biology 2013, 14:212

3. Lessons Learned

11
A little training goes a long way!
With the right tools, wet lab scientists make exceptional
curators who can easily learn to maximize the
generation of accurate, biologically supported gene
models.

3. Lessons Learned

12
Web Apollo
‘File’:
Upload your own
evidence: GFF3,
BAM, BigWig,
VCF*. Add
combination and
sequence search
tracks.

‘View’: change
color by
CDS, toggle
strands, set
highlight.

‘Tools’:
Use BLAT to query the
genome with a protein
or DNA sequence.

Grey bar of coordinates
indicates location. You can
also select here in order to
zoom to a sub-region.

Navigation tools:
pan and zoom
Search box: go
to a scaffold or a
gene model.

‘User-created Annotations’ Track
Evidence Tracks Area
Login

Available Tracks

Graphical User Interface (GUI) for editing annotations
Web Apollo


The editing logic is on the server:



selects longest ORF as CDS
flags non-canonical splice sites

‘User-created Annotations’ Track
Evidence Tracks Area
Flags non-canonical
splice sites.

Selection of features and
sub-features
Edge-matching
Web Apollo



Two new kinds of tracks:



DNA Track

‘User-created Annotations’ Track

annotation editing
sequence alteration editing
Web Apollo


Annotations, annotation edits, and History: stored in a centralized database.
Web Apollo


Annotation Information Editor
Web Apollo


Annotation Information Editor
[Some of the] Functionality:




Protein-coding gene annotation (that you know and love)
Sequence alterations (less coverage = more fragmentation)
Visualization of stage and cell-type specific transcription
data as coverage plots, heat maps, and alignments
Arthropodcentric Thanks!



















AgriPest Base
FlyBase
Hymenoptera Genome Database
VectorBase
Apis mellifera
Tribolium castaneum
Pogonomyrmex barbatus
Manduca sexta
Bombus terrestris
Helicoverpa armigera
Nasonia vitripennis
Acyrthosiphon pisum
Mayetiola destructor
Atta cephalotes
Linepithema humile
Camponotus floridanus
Solenopsis invicta
Acromyrmex echinatior
•

Thanks!

Berkeley Bioinformatics Open-source Projects
(BBOP), Berkeley Lab: Web Apollo and Gene
Ontology teams. Suzanna Lewis (PI).

•

Ian Holmes Lab (PI). *U. of California Berkeley.

BBOP

•

The team at Hymenoptera Genome Database.
§U. of Missouri. Christine G. Elsik (PI).

•

Arthropod genomics community (fringy
Richards, Monica Poelchau, Alexie
Papanicolaou, Gene Robinson, Juergen
Gadau, Chris R Smith, Owen McMillan, Owain
Edwards, Kevin Hackett, and a few hundred
more).

•

i5K Steering Committee, NAL (USDA), HGSCBCM, BGI, 1KITE.

•

Web Apollo is supported by NIH grants 5R01GM080203
from NIGMS, and 5R01HG004483 from NHGRI, and by
the Director, Office of Science, Office of Basic Energy
Sciences, of the U.S. Department of Energy under
Contract No. DE-AC02-05CH11231.

•

Images used with permission: AlexanderWild.com

Web Apollo

Gene Ontology

Gregg Helt

Chris Mungall

Ed Lee

Seth Carbon

Rob Buels *

Heiko Dietze

Mitch Skinner *
Justin Reese §
Chris Childers §
Web Apollo: http://GenomeArchitect.org
GO: http://GeneOntology.org
i5K: http://arthropodgenomes.org/wiki/i5K

• For your attention, thank you!
Thank you.

21

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Introduction to Web Apollo for the i5K pilot species.

  • 1. UNIVERSITY OF CALIFORNIA An introduction to Web Apollo. A webinar for the i5K Pilot Species Projects Monica Munoz-Torres, PhD Biocurator & Bioinformatics Analyst | @monimunozto Genomics Division, Lawrence Berkeley National Laboratory 04 February, 2014
  • 2. Outline An introduction to Web Apollo. A webinar for the i5K Pilot Species Projects. 1. What is Web Apollo?: • Definition & working concept. 2. Community based curation from our experience. 3. Lessons Learned. 4. Becoming acquainted with Web Apollo. Outline 2
  • 3. What is Web Apollo? • Web Apollo is a web-based genomic annotation editing platform. We need annotation editing tools to modify and refine the precise location and structure of the genome elements that predictive algorithms cannot yet resolve automatically. Find more about Web Apollo at http://GenomeArchitect.org and Genome Biol 14:R93. (2013). 1. What is Web Apollo? 3
  • 4. Brief history of Apollo*: Biologists could finally visualize computational analyses and experimental evidence from genomic features and build manually-curated consensus gene structures. Apollo became a very popular, open source tool (insects, fish, mammals, birds, etc.). a. Desktop: one person at a time editing a specific region, annotations saved in local files; slowed down collaboration. * b. Java Web Start: users saved annotations directly to a centralized database; potential issues with stale annotation data remained. 1. What is Web Apollo? 4
  • 5. Web Apollo • Browser-based; plugin for JBrowse. • Allows for intuitive annotation creation and editing, with gestures and pull-down menus to create transcripts, add/delete/resize exons, merge/split exons or transcripts, insert comments (CV, freeform text), etc. • Customizable rules and appearance. • Edits in one client are instantly pushed to all other clients. 1. What is Web Apollo? 5
  • 6. Our Working Concept In the context of gene manual annotation, curation tries to find the best examples and/or eliminate (most) errors. To conduct manual annotation efforts: Automated gene models Evidence: cDNAs, HMM domain searches, alignments with assemblies or genes from other species. Manual annotation & curation 2. In our experience. Gather and evaluate all available evidence using quality-control metrics to corroborate or modify automated annotation predictions. Perform sequence similarity searches (phylogenetic framework) and use literature and public databases to: • Predict functional assignments from experimental data. • Distinguish orthologs from paralogs, and classify gene membership in families and networks. 6
  • 7. Dispersed, community-based gene manual annotation efforts. Using Web Apollo, we* have trained geographically dispersed scientific communities to perform biologically supported manual annotations, and monitored their findings: ~80 institutions, 14 countries, hundreds of scientists, and gate keepers. – Training workshops and geneborees. – Tutorials with detailed instructions. *Collaboration with Elsik Lab, Hymenoptera Genome – Personalized user support. Database. 2. In our experience. 7
  • 8. What have we learned? Harvesting expertise from dispersed researchers who assigned functions to predicted and curated peptides, we have developed more interactive and responsive tools, as well as better visualization, editing, and analysis capabilities. Assessment: 1. Was it helpful / productive to work together? 2. Were manual annotations improved? 3. Did the shared and distributed annotation effort help improve the quality of scientific findings? 3. Lessons Learned 8
  • 9. It is helpful to work together. Scientific community efforts bring together domainspecific and natural history expertise that would have otherwise remain disconnected. 3. Lessons Learned 9
  • 10. Improved Automated Annotations* In many cases, automated annotations have been improved. Also, learned of the challenges of newer sequencing technologies, e.g.: – Frameshifts and indel errors – Split genes across scaffolds – Highly repetitive sequences To face these challenges, we train annotators in recovering coding sequences in agreement with all available biological evidence. 3. Lessons Learned 10
  • 11. Understanding the evolution of sociality. … groups of communities have taught us a lot! Comparison of the genomes of 7 species of ants contributed to a better understanding of the evolution and organization of insect societies at the molecular level. Insights drawn mainly from six core aspects of ant biology: 1. Alternative morphological castes 2. Division of labor 3. Chemical Communication 4. Alternative social organization 5. Social immunity 6. Mutualism Libbrecht et al. 2012. Genome Biology 2013, 14:212 3. Lessons Learned 11
  • 12. A little training goes a long way! With the right tools, wet lab scientists make exceptional curators who can easily learn to maximize the generation of accurate, biologically supported gene models. 3. Lessons Learned 12
  • 13. Web Apollo ‘File’: Upload your own evidence: GFF3, BAM, BigWig, VCF*. Add combination and sequence search tracks. ‘View’: change color by CDS, toggle strands, set highlight. ‘Tools’: Use BLAT to query the genome with a protein or DNA sequence. Grey bar of coordinates indicates location. You can also select here in order to zoom to a sub-region. Navigation tools: pan and zoom Search box: go to a scaffold or a gene model. ‘User-created Annotations’ Track Evidence Tracks Area Login Available Tracks Graphical User Interface (GUI) for editing annotations
  • 14. Web Apollo  The editing logic is on the server:   selects longest ORF as CDS flags non-canonical splice sites ‘User-created Annotations’ Track Evidence Tracks Area Flags non-canonical splice sites. Selection of features and sub-features Edge-matching
  • 15. Web Apollo  Two new kinds of tracks:   DNA Track ‘User-created Annotations’ Track annotation editing sequence alteration editing
  • 16. Web Apollo  Annotations, annotation edits, and History: stored in a centralized database.
  • 19. [Some of the] Functionality:    Protein-coding gene annotation (that you know and love) Sequence alterations (less coverage = more fragmentation) Visualization of stage and cell-type specific transcription data as coverage plots, heat maps, and alignments
  • 20. Arthropodcentric Thanks!                   AgriPest Base FlyBase Hymenoptera Genome Database VectorBase Apis mellifera Tribolium castaneum Pogonomyrmex barbatus Manduca sexta Bombus terrestris Helicoverpa armigera Nasonia vitripennis Acyrthosiphon pisum Mayetiola destructor Atta cephalotes Linepithema humile Camponotus floridanus Solenopsis invicta Acromyrmex echinatior
  • 21. • Thanks! Berkeley Bioinformatics Open-source Projects (BBOP), Berkeley Lab: Web Apollo and Gene Ontology teams. Suzanna Lewis (PI). • Ian Holmes Lab (PI). *U. of California Berkeley. BBOP • The team at Hymenoptera Genome Database. §U. of Missouri. Christine G. Elsik (PI). • Arthropod genomics community (fringy Richards, Monica Poelchau, Alexie Papanicolaou, Gene Robinson, Juergen Gadau, Chris R Smith, Owen McMillan, Owain Edwards, Kevin Hackett, and a few hundred more). • i5K Steering Committee, NAL (USDA), HGSCBCM, BGI, 1KITE. • Web Apollo is supported by NIH grants 5R01GM080203 from NIGMS, and 5R01HG004483 from NHGRI, and by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. • Images used with permission: AlexanderWild.com Web Apollo Gene Ontology Gregg Helt Chris Mungall Ed Lee Seth Carbon Rob Buels * Heiko Dietze Mitch Skinner * Justin Reese § Chris Childers § Web Apollo: http://GenomeArchitect.org GO: http://GeneOntology.org i5K: http://arthropodgenomes.org/wiki/i5K • For your attention, thank you! Thank you. 21

Notas do Editor

  1. File: GFF3, BAM, BigWig, VCF (soon).Tools: The plug-in architecture of the annotation editing engine allows for sequence alignment searches using BLAT
  2. The editing logic is on the server:It selects the longest ORF as CDSAnd flags non-canonical splice sitesThe server is a Java servlet- it uses the GMOD biological object layer (gbol) data model: object model & API, based on the Chado schema
  3. A BerkeleyDB stores annotations, annotation edits, and their History