Web Apollo: Lessons learned from community-based biocuration efforts.

Web Apollo: Lessons learned from community-based biocuration efforts.

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  UNIVERSITY OF CALIFORNIA Web Apollo:lessons learned from community-based biocuration efforts. Monica Munoz-Torres, PhD Biocurator & Bioinformatics Analyst | @monimunozto Genomics Division, Lawrence Berkeley National Laboratory 31 October, 2013
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  Outline 1. What isWeb Apollo?: • Definition & working concept. Lessons learned from communitybased biocuration efforts. 2. Community based curation from our experience: • Scope, stories to highlight. 3. Lessons Learned. 1. The power behind community-based curation of biological data: • International group efforts to create, collect, maintain, and use curation tools. Outline 2
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  What is WebApollo? • 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
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  A little historyabout Apollo*: Biologists could finally visualize computational analysis 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
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  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. • Edits in one client are instantly pushed to all other clients. 1. What is Web Apollo? 5
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  Our Working Concept In thecontext 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, classify gene membership in families and networks. 6
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  Dispersed, community-based gene manualannotation efforts. Using Web Apollo, we* 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. Education and Training done through: – Training workshops and geneborees. – Tutorials with detailed instructions. *Elsik Lab. Hymenoptera Genome Database. – Personalized user support. Georgetown University. 2. In our experience. 7
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  What did welearn? Harvesting expertise from dispersed researchers who assigned functions to predicted and curated peptides, we 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
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  It was helpfulto work together. Scientific community efforts brought together domainspecific and natural history expertise that would have otherwise remain disconnected. Warning: community-wide periodic and frequent updates, as well as coordination of organization and report (publication) of findings are necessary. 3. Lessons Learned 9
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  Automated annotations wereimproved* In many cases, automated annotations were improved. Also, learned of the challenges with new sequencing technologies, e.g.: – Frameshifts and indel errors – Split genes across scaffolds – Highly repetitive sequences To face these challenges, we trained annotators in recovering coding sequences in agreement with all available biological evidence. 3. Lessons Learned 10
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  Horizontal gene transferfrom virus to bacteria to insect. Scientific findings lead to untold stories… The genome of the jewel wasp (Nasonia vitripennis) contains the highest reported number of Ankyrin domains in insects. Thirteen ANK repeat-bearing proteins also contain C-terminal PRANC (Pox protein repeats of ankyrin C-terminal) domains. LGT between bacteria and animals: source of evolutionary innovation. Nasonia genome working group. 2010. Science, 327:343-347 3. Lessons Learned 11
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  Characterizing adaptive radiation. …and lead to uncovering old stories… Uncovering suspected candidates from 30 year old research, the Heliconius melpomene community was able to characterize the few Mendelian loci controlling divergence in wing patterns. Islands of genome divergence underlying adaptive radiation were characterized. A community effort developed a de novo reference genome on a small budget. Their findings were a milestone for understanding the basics of ecological adaptation. Heliconius genome consortium. 2012. Nature doi:10.1038/nature11041. 3. Lessons Learned 12
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  Understanding the evolutionof sociality. Comparison of the genomes of 7 species of ants contributed to a better understanding … and groups of of the evolution and organization of insect societies at the molecular level. communities told Insights drawn mainly from six core aspects of us even more! 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 13
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  More lessons learned 1.Next generation technologies brought many and new challenges. 2. You must enforce strict rules and formats; it is necessary to maintain consistency. 3. Be flexible and adaptable: study and incorporate new data, and adapt to support new platforms to keep pace and maintain the interest of scientific community. Evolve with the data! 4. 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 14
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  i5K Collaborative efforts forgenome sequencing projects lead to the birth of i5K. Small groups became large networks, which turned into an international, multi-institutional effort to sequence the genomes of 5 thousand arthropods. Up next: four species ready for community manual annotation using Web Apollo. 4. The power of biocuration 15
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  Gene Ontology Consortium Thiscommunity-based effort seeks to standardize the representation of gene and gene product attributes across species and databases. Collaborative efforts are focused on: 1. Capturing all available information to describe gene products (BP, CC, MF) in a species-independent manner. 2. Reviewing and updating the relationships. 3. Continuously developing tools to facilitate creation, maintenance and use of ontologies. 4. The power of biocuration 16
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  Integrating biocuration practices Frequently,groups incorporate both bibliographical curation and gene manual annotation efforts into their work to improve the quality and informative power of their data. E.g. Dictybase, curating literature for slime mold since 2004, serves interests in cellular development, chemotaxis, cytokinesis defects, etc. New to Web Apollo, ready to harness their community’s knowledge. 4. The power of biocuration 17
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  International Society forBiocuration ISB provides a forum for biocurators, developers, researchers, and students who are interested in: • Using common tools (GO, Genotype & Phenotype curation, GMOD tools, etc.). • Generation of gold standards for databases, ensuring that database and tools meet specific user needs. • Defining the profession of biocuration with respect to the scientific community and the granting agencies. • Member of BioDBCore, GOBLET, BioCreative. 4. The power of biocuration 18
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  The power behind community-based curationof biological data. 4. The power of biocuration 19
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  • Berkeley Bioinformatics Open-sourceProjects (BBOP), Berkeley Lab: Web Apollo and Gene Ontology teams. Suzanna Lewis (PI). • The team at Hymenoptera Genome Database. §U. of Missouri. Christine G. Elsik (PI). • Ian Holmes Lab (PI). *U. of California Berkeley. • Arthropod genomics community (e.g. Gene Robinson, Juergen Gadau, Chris R Smith, Owen McMillan, Owain Edwards, Kevin Hackett, and a few hundred more) and i5K: Org. Committee, NAL (USDA), HGSC-BCM, BGI, 1KITE. Rob Buels * • International Society for Biocuration Mitch Skinner * • 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 Thanks! BBOP Web Apollo Gene Ontology Gregg Helt Chris Mungall Ed Lee Seth Carbon Justin Reese § Heiko Dietze Chris Childers § Web Apollo: http://GenomeArchitect.org GO: http://GeneOntology.org i5K: http://arthropodgenomes.org/wiki/i5K ISB: http://biocurator.org Thank you. • For your attention, thank you! 20