Apollo - A webinar for the Phascolarctos cinereus research community

1. An Introduction to Apollo  A webinar for the Phascolarctos cinereus research community Monica Munoz-Torres, PhD | @monimunozto  Berkeley Bioinformatics Open-Source Projects (BBOP)  Lawrence Berkeley National Laboratory  Joint Genome Institute | University of California Berkeley | U.S. Department of Energy   04 August, 2015

2. APOLLO DEVELOPMENT APOLLO DEVELOPERS 2 h" p://G e nom e Ar c hite c t. or g / Nathan Dunn Eric Yao JBrowse, UC Berkeley Deepak Unni Colin Diesh Elsik Lab, University of Missouri Suzi Lewis Principal Investigator BBOP Moni Munoz-Torres Stephen Ficklin GenSAS, Washington State University

3. 3 ANNOTATION PLAN Introduction Assembly freeze Automated Annotation Manual annotation Using Web Apollo Curation freeze Merge: automated + manual Genome-wide & gene- specific comparative analyses QC QC Synthesis & dissemination.

4. OUTLINE  Web Apollo Collabora(ve Cura(on and Interac(ve Analysis of Genomes 4OUTLINE •  THE GENE MODEL predic(on, annota(on, cura(on •  APOLLO empowering collabora(ve cura(on •  APOLLO on THE WEB becoming acquainted •  EXAMPLE demonstra(ons

5. 5 BY THE END OF THIS TALK  you will  v Be>er understand genome cura(on in the context of annota(on: assembled genome à automated annotaEon à manual annotaEon v Become familiar with the environment and func(onality of the Apollo genome annota(on edi(ng tool. v Learn to iden(fy homologs of known genes of interest in a newly sequenced genome. v Learn about corrobora(ng and modifying automa(cally annotated gene models using available evidence in Apollo. Introduction

6. REVIEW ON YOUR OWN  for manual annotation To remember… Biological concepts to be>er understand manual annota(on 6FOOD FOR THOUGHT •  GLOSSARY from con$g to splice site •  CENTRAL DOGMA in molecular biology •  WHAT IS A GENE? deﬁning your goal •  TRANSCRIPTION mRNA in detail •  TRANSLATION and other deﬁni(ons •  GENOME CURATION steps involved

7. 7CURATING GENOMES What is a gene? v  The deﬁni(on of a gene paints a very complex picture of molecular ac(vity and it is a con(nuously evolving concept. •  From the Sequence Ontology (SO): “A gene is a locatable region of genomic sequence, corresponding to a unit of inheritance, which is associated with regulatory regions, transcribed regions and/or other func(onal sequence regions”. “Evolving Concept” at h>p://goo.gl/LpsajQ

8. 8CURATING GENOMES What is a gene? v  In our life(me, the Encyclopedia of DNA Elements (ENCODE) project updated this concept yet again. Long transcripts & dispersed regula$on! “A gene is a DNA segment that contributes phenotype/func(on. In the absence of demonstrated func(on, a gene may be characterized by sequence, transcrip(on or homology.” https://www.encodeproject.org/

9. 9CURATING GENOMES What is a gene?  considerations v  Consider : •  A gene is a genomic sequence (DNA or RNA) directly encoding func(onal product molecules, either RNA or protein. •  If several func(onal products share overlapping regions, we take the union of all overlapping genomics sequences coding for them. •  This union must be coherent – i.e., processed separately for ﬁnal protein and RNA products – but does not require that all products necessarily share a common subsequence. Gerstein et al., 2007. Genome Res.

10. 10CURATING GENOMES What is a gene? v  “The gene is a union of genomic sequences encoding a coherent set of poten(ally overlapping func(onal products.” Gerstein et al., 2007. Genome Res

11. 11CURATING GENOMES TRANSLATION  reading frame v  Reading frame is a manner of dividing the sequence of nucleo(des in mRNA (or DNA) into a set of consecu(ve, non-‐overlapping triplets (codons). v  Three frames can be read in the 5’ à 3’ direc(on. Given that DNA has two an(-‐parallel strands, an addi(onal three frames are possible to be read on the an(-‐sense strand. Six total possible reading frames exist. v  In eukaryotes, only one reading frame per sec(on of DNA is biologically relevant at a (me: it has the poten(al to be transcribed into RNA and translated into protein. This is called the OPEN READING FRAME (ORF) •  ORF = Start signal + coding sequence (divisible by 3) + Stop signal v  The sec(ons of the mature mRNA transcribed with the coding sequence but not translated are called UnTranslated Regions (UTR); one at each end.

12. 12CURATING GENOMES TRANSLATION  reading frame: splice sites v  The spliceosome catalyzes the removal of introns and the liga(on of ﬂanking exons. •  introns: spaces inside the gene, not part of the coding sequence •  exons: expression units (of the coding sequence) v  Splicing “signals” (from the point of view of an intron): •  There is a 5’ end splice “signal” (site): usually GT (less common: GC) •  And a 3’ end splice site: usually AG •  …]5’-‐GT/AG-‐3’[… v  It is possible to produce more than one protein (polypep(de) sequence from the same genic region, by alterna(vely bringing exons together= alternaEve splicing. For example, the gene Dscam (Drosophila) has 38,000 alterna(vely spliced mRNAs = isoforms

13. 13 "Gene structure" by Daycd- Wikimedia Commons CURATING GENOMES TRANSLATION  now in your mind

14. 14 Text for figures goes here CURATING GENOMES TRANSLATION  reading frame: phase v  Introns can interrupt the reading frame of a gene by inser(ng a sequence between two consecu(ve codons v  Between the ﬁrst and second nucleo(de of a codon v  Or between the second and third nucleo(de of a codon "Exon and Intron classes”. Licensed under Fair use via Wikipedia

15. CURATING GENOMES  overview 1  PredicEon of Gene Models 2  AnnotaEon of gene models 3  Manual annotaEon CURATING GENOMES 15

16. 16Gene Prediction GENE PREDICTION v  The iden(ﬁca(on of structural features of the genome: •  Primarily focused on protein-‐coding genes. •  Predicts also transfer RNAs (tRNA), ribosomal RNAs (rRNA), regulatory mo(fs, long and small non-‐coding RNAs (ncRNA), repe((ve elements (masked), etc. •  Two methods for iden(ﬁca(on. •  Some are self-‐trained and some must be trained.

17. 17Gene Prediction GENE PREDICTION  methods for discovery 1) Ab ini,o: -‐ based on DNA composi(on, -‐ deals strictly with genomic sequences -‐ makes use of sta(s(cal approaches to search for coding regions and typical gene signals. •  E.g. Augustus, GENSCAN, geneid, fgenesh, etc. 3’ Nat Rev Genet. 2015 Jun;16(6):321-32. doi: 10.1038/nrg3920

18. 18 Nucleic Acids 2003 vol. 31 no. 13 3738-3741 Gene Prediction GENE PREDICTION  methods for discovery (ctd) 2) Homology-‐based: -‐ evidence-‐based, -‐ ﬁnds genes using either similarity searches in the main databases or experimental data including RNAseq, expressed sequence tags (ESTs), full-‐length complementary DNAs (cDNAs), etc. •  E.g: fgenesh++, Just Annotate My genome (JAMg), SGP2

19. 19 GENE ANNOTATION Integra(on of data from computa(onal & experimental evidence with data from predic(on tools, to generate a reliable set of structural annotaEons. Involves: 1) ab ini$o predic(ons 2) assessment of biological evidence to drive the gene predic(on process 3) synthesis of these results to produce a set of consensus gene models Gene Annotation

20. 20 In some cases algorithms and metrics used to generate consensus sets may actually reduce the accuracy of the gene’s representa(on. GENE ANNOTATION Gene models may be organized into “sets” using: v  automa(c integra(on of predicted sets (combiners); e.g: GLEAN, EvidenceModeler or v  tools packaged into pipelines; e.g: MAKER, PASA, Gnomon, Ensembl, etc. Gene Annotation

21. ANNOTATION IS NOT PERFECT   automated annotation remains an imperfect art Unlike the more highly polished genomes of earlier projects, today’s genomes usually have: •  more frequent assembly errors, which lead to annota(on of genes across mul(ple scaﬀolds •  lower coverage No one is perfect, least of all automated annotation. 21 Image: www.BroadInstitute.org

22. MANUAL ANNOTATION  working concept Precise elucidaEon of biological features encoded in the genome requires careful examinaEon and review. Schiex et al. Nucleic Acids 2003 (31) 13: 3738-‐3741 Automated Predictions Experimental Evidence Manual Annotation – to the rescue. 22 cDNAs, HMM domain searches, RNAseq, genes from other species. The manual annotator evaluates all available evidence and corroborates or modiﬁes genome element predic(ons.

23. BUT, MANUAL CURATION  does not always scale Researchers on their own; may or may not publicize results; may be a dead-‐end with very few people ever aware of these results. Elsik et al. 2006. Genome Res. 16(11):1329-‐33. MANUAL ANNOTATION 23 Too many sequences and not enough hands. A small group of highly trained experts (e.g. GO). 1 Museum A few very good biologists, a few very good bioinforma(cians camping together for intense but short periods of (me. Jamboree 2 Co"age 3

24. 24 MANUAL ANNOTATION  objectives IdenEﬁes elements that best represent the underlying biology and eliminates elements that reﬂect systemic errors of automated analyses. Assigns funcEon through compara(ve analysis of similar genome elements from closely related species using literature, databases, and experimental data. MANUAL ANNOTATION h>p://GeneOntology.org 1 2

25. GENOME ANNOTATION  an inherently collaborative task Researchers oren turn to colleagues for second opinions and insight from those with exper(se in par(cular areas (e.g., domains, families). APOLLO 25 We need annota$on edi$ng tools to modify and reﬁne the precise loca$on and structure of the genome elements that predic$ve algorithms cannot yet resolve automa$cally. “Incorrect and incomplete genome annota$ons will poison every experiment that uses them”. -‐ M. Yandell

26. APOLLO  collaborative genome annotation editing tool 26 v  Web based, integrated with JBrowse. v  Supports real (me collabora(on! v  Automa(c genera(on of ready-‐made computable data. v  Supports annota(on of genes, pseudogenes, tRNAs, snRNAs, snoRNAs, ncRNAs, miRNAs, TEs, and repeats. v  Intui(ve annota(on, gestures, and pull-‐down menus to create and edit transcripts and exons structures, insert comments (CV, freeform text), associate GO terms, etc. APOLLO h>p://GenomeArchitect.org

27. APOLLO ARCHITECTURE  simpler, more flexible APOLLO 27 Web-‐based client + annota(on-‐edi(ng engine + server-‐side data service REST / JSON Websockets Annotation Engine (Server) Shiro LDAP OAuth JBrowse Data Organism 2 Annotations Security Preferences Organisms Tracks BAM BED VCF GFF3 BigWig Annotators Google Web Toolkit (GWT) / Bootstrap JBrowse DOJO / jQuery JBrowse Data Organism 1 Load genomic evidence for selected organism Single Data Store PostgreSQL, MySQL, MongoDB, ElasticSearch Apollo v2.0

28. We train and support hundreds of geographically dispersed scien(sts from diverse research communi(es to conduct manual annota(ons, to recover coding sequences in agreement with all available biological evidence using Web Apollo. v  Gate keeping and monitoring. v  Tutorials, training workshops, and “geneborees”. 28 DISPERSED COMMUNITIES collaborative manual annotation efforts APOLLO

29. LESSONS LEARNED  What we have learned: •  Collabora(ve work dis(lls invaluable knowledge •  We must enforce strict rules and formats •  We must evolve with the data •  A li>le training goes a long way •  NGS poses addi(onal challenges LESSONS LEARNED 29

30. Apollo h>p://genomearchitect.org/web_apollo_user_guide

31. 1.  Select a chromosomal region of interest, e.g. scaﬀold. 2.  Select appropriate evidence tracks to review the gene model. 3.  Determine whether a feature in an exis(ng evidence track will provide a reasonable gene model to start working. -‐  select and drag the feature to the ‘User-‐created Annota(ons’ area, creaEng an iniEal gene model. If necessary use edi(ng func(ons to adjust the gene model. 4.  Check your edited gene model for integrity and accuracy by comparing it with available homologs. Becoming Acquainted with Web Apollo 31 | Always remember: when annota(ng gene models using Apollo, you are looking at a ‘frozen’ version of the genome assembly and you will not be able to modify the assembly itself. 31 GENERAL PROCESS OF CURATION  steps to remember

32. 32 APOLLO  annotation editing environment BECOMING ACQUAINTED WITH APOLLO Color by CDS frame, toggle strands, set color scheme and highlights. Upload evidence files (GFF3, BAM, BigWig), add combinaEon and sequence search tracks. Query the genome using BLAT. Naviga(on and zoom. Search for a gene model or a scaffold. Get coordinates and “rubber band” selec(on for zooming. Login User-‐created annota(ons. Annotator panel. Evidence Tracks Stage and cell-‐type specific transcrip(on data.

33. REMOVABLE SIDE DOCK  with customizable tabs HIGHLIGHTED IMPROVEMENTS 33 Annotations Organism Users Groups AdminTracks Reference Sequence

34. EDITS & EXPORTS  annotation details, exon boundaries, data export HIGHLIGHTED IMPROVEMENTS 34 1 2 Annotations 1 2

35. HIGHLIGHTED IMPROVEMENTS 35 Reference Sequences 3 FASTA GFF3 EDITS & EXPORTS  annotation details, exon boundaries, data export 3

36. 36 | 36 Becoming Acquainted with Web Apollo. USER NAVIGATION Annotator panel. •  Choose appropriate evidence tracks from list on annotator panel. •  Select & drag elements from evidence track into the ‘User-created Annotations’ area. •  Edge-matching. •  Hovering over annotation in progress brings up an information pop-up.

37. 37 | 37 USER NAVIGATION Becoming Acquainted with Web Apollo. •  Annotation right-click menu

38. 38 Annota(ons, annota(on edits, and History: stored in a centralized database. 38 USER NAVIGATION Becoming Acquainted with Web Apollo.

39. 39 The Annota(on InformaEon Editor DBXRefs are database crossed references: if you have reason to believe that this gene is linked to a gene in a public database (including your own), then add it here. 39 USER NAVIGATION Becoming Acquainted with Web Apollo.

40. 40 The Annota(on InformaEon Editor •  Add PubMed IDs •  Include GO terms as appropriate from any of the three ontologies •  Write comments sta(ng how you have validated each model. 40 USER NAVIGATION Becoming Acquainted with Web Apollo.

41. 41 | Zoom in/out with keyboard: shir + arrow keys up/down 41 USER NAVIGATION Becoming Acquainted with Web Apollo. •  ‘Zoom to base level’ op(on reveals the DNA Track. •  Color exons by CDS from the ‘View’ menu. •  Toggle reference DNA sequence and translaEon frames from either direc(on.

42. Annota(ng

43. “Simple case”: -‐ the predicted gene model is correct or nearly correct, and -‐ this model is supported by evidence that completely or mostly agrees with the predic(on. -‐ evidence that extends beyond the predicted model is assumed to be non-‐coding sequence. The following are simple modiﬁca(ons. 43 | 43 ANNOTATING SIMPLE CASES Becoming Acquainted with Web Apollo. SIMPLE CASES

44. 44 | •  A conﬁrma(on box will warn you if the receiving transcript is not on the same strand as the feature where the new exon originated. •  Check ‘Start’ and ‘Stop’ signals arer each edit. 44 ADDING EXONS Becoming Acquainted with Web Apollo. SIMPLE CASES

45. If transcript alignment data are available and extend beyond your original annota(on, you may extend or add UTRs. 1.  Right click at the exon edge and ‘Zoom to base level’. 2.  Place the cursor over the edge of the exon un$l it becomes a black arrow then click and drag the edge of the exon to the new coordinate posi(on that includes the UTR. 45 | To add a new spliced UTR to an exis(ng annota(on follow the procedure for adding an exon. 45 ADDING UTRs Becoming Acquainted with Web Apollo. SIMPLE CASES

46. 1.  Zoom in to clearly resolve each exon as a dis(nct rectangle. 2.  Two exons from diﬀerent tracks sharing the same start and/or end coordinates will display a red bar to indicate matching edges. 3.  Selec(ng the whole annota(on or one exon at a (me, use this ‘edge-‐ matching’ func(on and scroll along the length of the annota(on, verifying exon boundaries against available data. Use square [ ] brackets to scroll from exon to exon. 4.  Check if cDNA / RNAseq reads lack one or more of the annotated exons or include addi(onal exons. 46 | 46 CHECK EXON INTEGRITY Becoming Acquainted with Web Apollo. SIMPLE CASES

47. To modify an exon boundary and match data in the evidence tracks: select both the oﬀending exon and the feature with the expected boundary, then right click on the annota(on to select ‘Set 3’ end’ or ‘Set 5’ end’ as appropriate. 47 | In some cases all the data may disagree with the annota(on, in other cases some data support the annota(on and some of the data support one or more alterna(ve transcripts. Try to annotate as many alterna(ve transcripts as are well supported by the data. 47 EXON STRUCTURE INTEGRITY Becoming Acquainted with Web Apollo. SIMPLE CASES

48. Flags non-‐canonical splice sites. Selec(on of features and sub-‐ features Edge-‐matching Evidence Tracks Area ‘User-‐created Annota(ons’ Track Apollo’s edi(ng logic (brain): §  selects longest ORF as CDS §  ﬂags non-‐canonical splice sites 48 ORFs AND SPLICE SITES Becoming Acquainted with Web Apollo. SIMPLE CASES

49. 49 | Exon/intron junc(on possible error Original model Curated model Non-‐canonical splices are indicated by an orange circle with a white exclama(on point inside, placed over the edge of the offending exon. Most insects, have a valid non-‐canonical site GC-‐AG. Other non-‐canonical splice sites are unverified. Web Apollo flags GC splice donors as non-‐canonical. Canonical splice sites: 3’-‐…exon]GA / TG[exon…-‐5’ 5’-‐…exon]GT / AG[exon…-‐3’ reverse strand, not reverse-‐complemented: forward strand 49 SPLICE SITES Becoming Acquainted with Web Apollo. SIMPLE CASES Zoom to review non-‐canonical splice site warnings. Although these may not always have to be corrected (e.g GC donor), they should be flagged with the appropriate comment.

50. Web Apollo calculates the longest possible open reading frame (ORF) that includes canonical ‘Start’ and ‘Stop’ signals within the predicted exons. If ‘Start’ appears to be incorrect, modify it selec(ng an in-‐frame ‘Start’ codon further up or downstream, depending on evidence (protein database, addi(onal evidence tracks). It may be present outside the predicted gene model, within a region supported by another evidence track. In very rare cases, the actual ‘Start’ codon may be non-‐canonical (non-‐ATG). 50 | 50 ‘START’ AND ‘STOP’ SITES Becoming Acquainted with Web Apollo. SIMPLE CASES

51. Evidence may support joining two or more diﬀerent gene models. Warning: protein alignments may have incorrect splice sites and lack non-‐conserved regions! 1.  In ‘User-‐created AnnotaEons’ area shir-‐click to select an intron from each gene model and right click to select the ‘Merge’ op(on from the menu. 2.  Drag suppor(ng evidence tracks over the candidate models to corroborate overlap, or review edge matching and coverage across models. 3.  Check the resul(ng transla(on by querying a protein database e.g. UniProt. Add comments to record that this annota(on is the result of a merge. 51 | 51 Red lines around exons: ‘edge-‐matching’ allows annotators to conﬁrm whether the evidence is in agreement without examining each exon at the base level. COMPLEX CASES merge two gene predictions on the same scaffold Becoming Acquainted with Web Apollo. COMPLEX CASES

52. One or more splits may be recommended when: -‐ different segments of the predicted protein align to two or more different gene families -‐ predicted protein doesn’t align to known proteins over its en(re length Transcript data may support a split, but first verify whether they are alterna(ve transcripts. 52 | 52 COMPLEX CASES split a gene prediction Becoming Acquainted with Web Apollo. COMPLEX CASES

53. DNA Track ‘User-‐created AnnotaEons’ Track 53 COMPLEX CASES correcting frameshifts, single-base errors, and selenocysteines Becoming Acquainted with Web Apollo. COMPLEX CASES

54. 1.  Web Apollo allows annotators to make single base modifica(ons or frameshirs that are reflected in the sequence and structure of any transcripts overlapping the modifica(on. Note that these manipula(ons do NOT change the underlying genomic sequence. 2.  If you determine that you need to make one of these changes, zoom in to the nucleo(de level and right click over a single nucleo(de on the genomic sequence to access a menu that provides op(ons for crea(ng inser(ons, dele(ons or subs(tu(ons. 3.  The ‘Create Genomic InserEon’ feature will require you to enter the necessary string of nucleo(de residues that will be inserted to the right of the cursor’s current loca(on. The ‘Create Genomic DeleEon’ op(on will require you to enter the length of the dele(on, star(ng with the nucleo(de where the cursor is posi(oned. The ‘Create Genomic SubsEtuEon’ feature asks for the string of nucleo(de residues that will replace the ones on the DNA track. 4.  Once you have entered the modifica(ons, Web Apollo will recalculate the corrected transcript and protein sequences, which will appear when you use the right-‐click menu ‘Get Sequence’ op(on. Since the underlying genomic sequence is reflected in all annota(ons that include the modified region you should alert the curators of your organisms database using the ‘Comments’ sec(on to report the CDS edits. 5.  In special cases such as selenocysteine containing proteins (read-‐throughs), right-‐click over the offending/premature ‘Stop’ signal and choose the ‘Set readthrough stop codon’ op(on from the menu. 54 | 54 Becoming Acquainted with Web Apollo. COMPLEX CASES COMPLEX CASES correcting frameshifts, single-base errors, and selenocysteines

55. Follow the checklist un(l you are happy with the annota(on! And… –  Comment to validate your annota(on, even if you made no changes to an exis(ng model. Think of comments as your vote of conﬁdence. –  Or add a comment to inform the community of unresolved issues you think this model may have. 55 | 55 Always Remember: Web Apollo cura(on is a community eﬀort so please use comments to communicate the reasons for your annota(on (your comments will be visible to everyone). COMPLETING THE ANNOTATION Becoming Acquainted with Web Apollo.

56. Checklist

57. 1.  Can you add UTRs (e.g.: via RNA-‐Seq)? 2.  Check exon structures 3.  Check splice sites: most splice sites display these residues …]5’-‐GT/AG-‐3’[… 4.  Check ‘Start’ and ‘Stop’ sites 5.  Check the predicted protein product(s) –  Align it against relevant genes/gene family. –  blastp against NCBI’s RefSeq or nr 6.  If the protein product s(ll does not look correct then check: –  Are there gaps in the genome? –  Merge of 2 gene predic(ons on the same scaffold –  Merge of 2 gene predic(ons from different scaffolds –  Split a gene predic(on –  Frameshies –  error in the genome assembly? –  Selenocysteines, single-‐base errors, etc 57 | 57 7.  Finalize annota(on by adding: –  Important project informa(on in the form of comments –  IDs from public databases e.g. GenBank (via DBXRef), gene symbol(s), common name(s), synonyms, top BLAST hits, orthologs with species names, and everything else you can think of, because you are the expert. –  Whether your model replaces one or more models from the official gene set (so it can be deleted). –  The kinds of changes you made to the gene model of interest, if any. –  Any appropriate func(onal assignments of interest to the community (e.g. via BLAST, RNA-‐Seq data, literature searches, etc.) THE CHECKLIST for accuracy and integrity MANUAL ANNOTATION CHECKLIST

58. Example

59. Example Example 59 A public Apollo Demo using the Honey Bee genome is available at h>p://genomearchitect.org/WebApolloDemo -‐ Demonstra(on using the Hyalella azteca genome (amphipod crustacean).

60. What do we know about this genome? •  Currently publicly available data at NCBI: •  >37,000 nucleo(de seqsà scaffolds, mitochondrial genes •  300 amino acid seqsà mitochondrion •  53 ESTs •  0 conserved domains iden(fied •  0 “gene” entries submi>ed •  Data at i5K Workspace@NAL (annota(on hosted at USDA) -‐ 10,832 scaffolds: 23,288 transcripts: 12,906 proteins Example 60

61. PubMed Search:   what’s new? Example 61

62. PubMed Search: what’s new? Example 62 “Ten popula(ons (3 cultures, 7 from California water bodies) differed by at least 550-‐fold in sensiEvity to pyrethroids.” “By sequencing the primary pyrethroid target site, the voltage-‐gated sodium channel (vgsc), we show that point muta(ons and their spread in natural popula(ons were responsible for differences in pyrethroid sensi(vity.” “The finding that a non-‐target aqua(c species has acquired resistance to pes(cides used only on terrestrial pests is troubling evidence of the impact of chronic pesEcide transport from land-‐based applica(ons into aqua(c systems.”

63. How many sequences for our gene of interest? Example 63 •  Para, (voltage-‐gated sodium channel alpha subunit; Nasonia vitripennis). •  NaCP60E (Sodium channel protein 60 E; D. melanogaster). –  MF: voltage-‐gated ca(on channel ac(vity (IDA, GO:0022843). –  BP: olfactory behavior (IMP, GO: 0042048), sodium ion transmembrane transport (ISS,GO:0035725). –  CC: voltage-‐gated sodium channel complex (IEA, GO:0001518). And what do we know about them?

64. Retrieving sequences for   sequence similarity searches. Example 64 >vgsc-‐Segment3-‐DomainII RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDG QMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR

65. BLAT search Example 65 >vgsc-‐Segment3-‐DomainII RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDG QMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR

66. BLAT search Example 66

67. Customizations:   high-scoring segment pairs (hsp) in “BLAST+ Results” track Example 67

68. Available Tracks Example 68

69. Creating a new gene model: drag and drop Example 69 •  Apollo automatically calculates ORF. In this case, ORF includes the high-scoring segment pairs (hsp).

70. Get Sequence Example 70 http://blast.ncbi.nlm.nih.gov/Blast.cgi

71. Also, flanking sequences (other gene models) vs. NCBI nr Example 71 In this case, two gene models upstream, at 5’ end. BLAST hsps

72. Review alignments Example 72 HaztTmpM006234 HaztTmpM006233 HaztTmpM006232

73. Hypothesis for vgsc gene model Example 73

74. Editing: merge the three models Example 74 Merge by dropping an exon or gene model onto another. Merge by selec(ng two exons (holding down “Shir”) and using the right click menu. or…

75. Editing: correct boundaries, delete exons Example 75 Modify exon / intron boundary: -‐  Drag the end of the exon to the nearest canonical splice site. -‐  Use right-‐click menu. Delete ﬁrst exon from M006233

76. Editing: set translation start Example 76

77. Editing: modify boundaries Example 77 Modify intron / exon boundary also at coord. 78,999.

78. Finished model Example 78 Corroborate integrity and accuracy of the model: -‐ Start and Stop -‐ Exon structure and splice sites …]5’-‐GT/AG-‐3’[… -‐ Check the predicted protein product vs. NCBI nr

79. Information Editor •  DBXRefs: e.g. NP_001128389.1, N. vitripennis, RefSeq •  PubMed iden(ﬁer: PMID: 24065824 •  Gene Ontology IDs: GO:0022843, GO: 0042048, GO:0035725, GO:0001518. •  Comments. •  Name, Symbol. •  Approve / Delete radio bu>on. Example 79 Comments (if applicable)

80. Demo

81. APOLLO  demonstration Apollo demo video available at: h>ps://youtu.be/VgPtAP_fvxY DEMO 81

82. •  Berkeley BioinformaEcs Open-‐source Projects (BBOP), Berkeley Lab: Web Apollo and Gene Ontology teams. Suzanna E. Lewis (PI). •  § Chris$ne G. Elsik (PI). University of Missouri. •  * Ian Holmes (PI). University of California Berkeley. •  Arthropod genomics community: i5K Steering Commi>ee (esp. Sue Brown (Kansas State)), Alexie Papanicolaou (UWS), and the Honey Bee Genome Sequencing Consor(um. •  Apollo is supported by NIH grants 5R01GM080203 from NIGMS, and 5R01HG004483 from NHGRI; by Contract No. 60-‐8260-‐4-‐005 from the Na(onal Agricultural Library (NAL) at the United States Department of Agriculture (USDA); 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: h>p://AlexanderWild.com •  For your a"enEon, thank you! Thank you. 82 Web Apollo Nathan Dunn Colin Diesh § Deepak Unni § Gene Ontology Chris Mungall Seth Carbon Heiko Dietze BBOP Web Apollo: h>p://GenomeArchitect.org i5K: h>p://arthropodgenomes.org/wiki/i5K GO: h>p://GeneOntology.org Thanks! NAL at USDA Monica Poelchau Christopher Childers Gary Moore HGSC at BCM fringy Richards Dan Hughes Kim Worley JBrowse Eric Yao *

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