Apollo and i5K: Collaborative Curation and Interactive Analysis of Genomes

1. APOLLO + i5K  Collaborative Curation and   Interactive Analysis of Genomes Monica Munoz-Torres, PhD | @monimunozto  Nathan Dunn, Monica Poelchau, Ian Holmes, Colin Diesh, Deepak Unni, Christine Elsik, and Suzanna Lewis.   Berkeley Bioinformatics Open-Source Projects (BBOP)  Genomics Division, Lawrence Berkeley National Laboratory  XXIII Plant and Animal Genome Conference. San Diego, CA. January 14, 2015

2. OUTLINE  •  CURATING GENOMES steps involved •  MANUAL ANNOTATION is necessary, but does not always scale •  WEB APOLLO empowering curators •  i5K pursuing common goals Web Apollo CollaboraHve CuraHon and InteracHve Analysis of Genomes 2

3. CURATING GENOMES  steps involved 1  Crea-on of Gene Models calling ORFs, one or more rounds of gene predicHon, etc. 2  Annota-on of gene models Describing funcHon, expression paNerns, and metabolic network memberships. 3  Manual annota-on CURATING GENOMES 3

4. AUTOMATED ANNOTATION  remains an imperfect art Unlike the more highly polished genomes of earlier projects, today: a.  lower coverage. b.  more frequent assembly errors and annotaHon of genes across mulHple scaﬀolds. c.  automated genome annotaHons must be curated to resolve discrepancies, providing clarity and validaHon. CURATING GENOMES 4 Image: www.BroadInsHtute.org

5. ACCURACY OF ANNOTATION   … it depends EXAMPLE v  Eight methods for diﬀerenHal alternaHve splicing detecHon in plants, using RNAseq. v  Conclusion: NO single method performs the best in all situaHons. “The accuracy of annota/on has a major impact on which method should be chosen for analysis.” CURATING GENOMES 5 Liu et al. BMC BioinformaHcs 2014, 15:364

6. 6 MANUAL ANNOTATION  objectives IdenHﬁes elements that best represent the underlying biology (including missing genes) and eliminates elements that reﬂect systemic errors of automated analyses. Assigns funcHon through comparaHve analysis of similar genome elements from closely related species using literature, databases, and researchers’ lab data. 1 2 MANUAL ANNOTATION hNp://GeneOntology.org

7. BUT, MANUAL CURATION  does not always scale A small group of highly trained experts; e.g. GO 1 Museum A few very good biologists and a few very good bioinformaHcians camp together, during intense but short periods of Hme. Jamboree 2 Researchers work by themselves, then may or may not publicize results; may be a dead-‐ end with very few people ever aware of these results. Co?age 3 Elsik et al. 2006. Genome Res. 16(11):1329-‐33. MANUAL ANNOTATION 7 Too many sequences and not enough hands to approach curaHon.

8. POWER TO THE CURATORS  augment existing tools Fill in the gap for all the things that won’t be easy to cover with these approaches and allow researchers to beNer contribute their eﬀorts. Give more people the power to curate! Big data are not a subs/tute for, but a supplement to tradi/onal data collec/on and analysis. The Parable of Google Flu. Lazer et al. 2014. Science 343 (6176): 1203-‐1205. v Enable more curators to work v Enable beNer scienHﬁc publishing v Credit curators for their work WEB APOLLO 8

9. GENOME ANNOTATION  an inherently collaborative task Researchers ofen turn to colleagues for second opinions and insight from those with experHse in parHcular areas (e.g., domains, families). To facilitate and encourage this, we conHnue to improve Apollo. WEB APOLLO 9 v  Web based for easy access. v  Concurrent access supports real Hme collaboraHon. v  Built-‐in support for standards (transparently compliant). v  AutomaHc generaHon of ready-‐made computable data. v  Client-‐side applicaHon relieves server boNleneck and supports privacy. v  Supports annotaHon of genes, pseudogenes, tRNAs, snRNAs, snoRNAs, ncRNAs, miRNAs, TEs, and repeats. The new Javascript-‐based Apollo :

10. COLLABORATIONS  also crowdsourcing development v  New avenues for landing on Apollo and customizaHon of addiHonal applicaHons. v  Web services for alignment and funcHonal annotaHon tools. v  RNAseq datasets being used to re-‐annotate the bovine genome, ﬁnding genes that neither RefSeq nor Ensembl predicted. Also creaHng track of disagreement between sets. v  Bovine genome consorHum making previous iteraHons of manual annotaHon eﬀorts (from 3 assemblies ago) available for integraHon of curated models. WEB APOLLO 10 UNIVERSITY of MISSOURI National Agricultural Library

11. i5K  5,000 insects and related Arthropod species v  Species are selected in an eﬀort to beNer understand arthropod evoluHon and phylogeny through: v  worldwide agriculture v  food safety v  medicine v  energy producHon v  models in biology v  those species most abundant in world ecosystems v  every branch of the insect phylogeny v  Each new genome requires visualizaHon and curaHon! APOLLO + i5K 11 National Agricultural Library hNp://arthropodgenomes.org/wiki/i5K

12. i5K  who can join? v  All Arthropods are welcome! v  Pilot project: 39 species v  3 with completed manual annotaHon v  25 undergoing manual annotaHon v  We oﬀer a plaiorm for collaboraHve genome analysis. v  We do not oﬀer funding for sequencing projects. APOLLO + i5K 12 National Agricultural Library Wasmania auropunctata Phlebotomus papatasi hNp://arthropodgenomes.org/wiki/i5K

13. i5K  current workflow: pilot project APOLLO + i5K 13 National Agricultural Library Sequencing, assembly, & annotaHon Research Plan Select genes of interest Calling all collaborators Manual AnnotaHon Merge automated & manual annotaHons •  Set Hme frame •  Training •  Q&A Update gene set for computaHonal analysis •  Gatekeeping •  More curaHon CollaboraHve ComputaHonal PublicaHon

14. i5K  tools at workspace@NAL v  Web Apollo v  RegistraHon module v  DiﬀerenHal user permissions v  Django BLAST v  Queries mulHple species at once v  Links directly to Apollo v  Species pages & Gene pages v  project details, metrics, staHsHcs v  Widget to track all WA annotaHons APOLLO + i5K 14 National Agricultural Library Tripal, Chado, JBrowse, Apollo National Agricultural Library

15. i5K  what we have learned v  Enabling collaboraHon has been very useful to communiHes v  Data hosHng and administraHon at NAL facilitates process for many groups v  You must enforce strict rules and formats v  Metadata capture is a must; standards must be generated and enforced v  Users prefer small bits of help info at a Hme, instead of lengthy manuals v  The ideal assembly is of high quality and remains stable v  InvesHng Hme and eﬀort on a high quality set of automated gene predicHons will pay oﬀ v  Quality of manually annotated set will depend on the coordinator’s “whip” APOLLO + i5K 15 National Agricultural Library

16. i5K  how to join v  Visit hNp://arthropodgenomes.org/wiki/i5K to sign up v  Contact us! Please tell us about your research interests and comment on the status and quality of sequencing / assembly / automated annotaHon for your genome of interest. @monimunozto | mcmunozt @ lbl.gov v  Check out the i5K Workspace@NAL at hNps://i5k.nal.usda.gov/ APOLLO + i5K 16 National Agricultural Library

17. FUTURE PLANS  educational tools We are working with educators to make Web Apollo part of their curricula. WEB APOLLO 17 Lecture Series. In the classroom. At the lab. Classroom exercises: from genome sequence to hypothesis. CuraHon group dedicated to producing educaHon materials for non-‐model organism communiHes. Our team provides online documentaHon, hands-‐on training, and rapid response to users.

18. ALL ARE WELCOME  call or email to join the Apollo community Open Call for Developers on the First Thursday of each month at 9:00AM (Paciﬁc Time). Message @monimunozto for details. BBOP Projects 18 Join the conversaHon by submirng your email at hNps://lists.lbl.gov/sympa/subscribe/apollo hNp://GenomeArchitect.org hNp://ArthropodGenomes.org/wiki/i5K

19. •  Berkeley Bioinforma-cs Open-‐source Projects (BBOP), Berkeley Lab: Web Apollo and Gene Ontology teams. Suzanna E. Lewis (PI). •  § ChrisHne G. Elsik (PI). University of Missouri. •  * Ian Holmes (PI). University of California Berkeley. •  Arthropod genomics community: i5K Steering CommiNee (esp. Sue Brown (Kansas State)), Alexie Papanicolaou (CSIRO), Monica Poelchau, Christopher Childers (USDA/NAL), fringy Richards, Dan Hughes, Kim Worley (HGSC-‐BCM), BGI, Oliver Niehuis (1KITE hNp://www.1kite.org/), and the Honey Bee Genome Sequencing ConsorHum. •  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. •  Insect images used with permission: hNp://AlexanderWild.com •  For your a?en-on, thank you! Thank you. 19 Web Apollo Nathan Dunn Colin Diesh § Deepak Unni § Gene Ontology Chris Mungall Seth Carbon Heiko Dietze BBOP Web Apollo: hNp://GenomeArchitect.org i5K: hNp://arthropodgenomes.org/wiki/i5K GO: hNp://GeneOntology.org Thanks! NAL at USDA Monica Poelchau Christopher Childers NAL team HGSC at BCM fringy Richards Dan Hughes Kim Worley

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