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Apollo Introduction for the Chestnut Research Community

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Apollo is a web-based, collaborative genomic annotation editing platform. We need annotation editing tools to modify and refine precise location and structure of the genome elements that predictive algorithms cannot yet resolve automatically.

This presentation is an introduction to how the manual annotation process takes place using Apollo. It is addressed to the members of the American Chestnut & Chinese Chestnut Genomics research community.

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Apollo Introduction for the Chestnut Research Community

  1. 1. Introduction to Apollo
 A webinar for the American chestnut & 
 Chinese chestnut Research Community Monica Munoz-Torres, PhD | @monimunozto
 Berkeley Bioinformatics Open-Source Projects (BBOP)
 Lawrence Berkeley National Laboratory | 
 University of California Berkeley | U.S. Department of Energy 27 August, 2015
  2. 2. OUTLINE
 Web  Apollo  Collabora've  Cura'on  and     Interac've  Analysis  of  Genomes   2OUTLINE •  MANUAL  ANNOTATION   necessary,  collabora've     •  APOLLO   empowering  collabora've  cura'on     •  EXAMPLE   demonstra'ons  
  3. 3. 3 Genome Sequencing Project Introduction Assembly Automated Annotation Manual annotation Using Web Apollo Merge: automated + manual Genome-wide & gene- specific comparative analyses QC QC Synthesis & dissemination. Experimental design, sample collection preparation. QC Sequencing QC QC
  4. 4. REVIEW ON YOUR OWN
 for manual annotation To  remember…  Biological  concepts  to  be=er   understand  manual  annota'on   4FOOD FOR THOUGHT •  GLOSSARY   from  con$g  to  splice  site     •  CENTRAL  DOGMA   in  molecular  biology     •  WHAT  IS  A  GENE?   defining  your  goal   •  TRANSCRIPTION   mRNA  in  detail     •  TRANSLATION   and  other  defini'ons   •  GENOME  CURATION   steps  involved  
  5. 5. 5 BY THE END OF THIS TALK
 you will
 v Be=er  understand  genome  cura'on  in  the  context  of  annota'on:     assembled  genome  à  automated  annota=on  à  manual  annota=on   v Become  familiar  with  the  environment  and  func'onality  of  the  Apollo   genome  annota'on  edi'ng  tool.   v Learn  to  iden'fy  homologs  of  known  genes  of  interest  in  a  newly   sequenced  genome.   v Learn  about  corrobora'ng  and  modifying  automa'cally  annotated  gene   models  using  available  evidence  in  Apollo.   Introduction
  6. 6. 6CURATING GENOMES What is a gene? v  The  defini'on  of  a  gene  paints  a  very  complex  picture  of  molecular  ac'vity   and  it  is  a  con'nuously  evolving  concept.     •  From  the  Sequence  Ontology  (SO):   “A  gene  is  a  locatable  region  of  genomic  sequence,  corresponding  to  a  unit   of  inheritance,  which  is  associated  with  regulatory  regions,  transcribed   regions  and/or  other  func'onal  sequence  regions”.       “Evolving  Concept”  at  h=p://goo.gl/LpsajQ  
  7. 7. 7CURATING GENOMES What is a gene? v  In  our  life'me,  the  Encyclopedia  of  DNA  Elements  (ENCODE)  project   updated  this  concept  yet  again.  Long  transcripts  &  dispersed  regula$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/
  8. 8. 8CURATING 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.
  9. 9. 9CURATING GENOMES What is a gene? “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
  10. 10. 10CURATING 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.  
  11. 11. 11CURATING 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=  alterna=ve   splicing.  For  example,  the  gene  Dscam  (Drosophila)  has  38,000  alterna'vely   spliced  mRNAs  =  isoforms  
  12. 12. 12 "Gene structure" by Daycd- Wikimedia Commons CURATING GENOMES TRANSCRIPTION & TRANSLATION
 now in your mind
  13. 13. 13 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
  14. 14. CURATING GENOMES
 overview 1  Predic=on  of  Gene  Models       2  Annota=on  of  gene  models       3  Manual  annota=on   CURATING GENOMES 14
  15. 15. 15Gene 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.  
  16. 16. 16Gene 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
  17. 17. 17 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  
  18. 18. 18 GENE ANNOTATION Integra'on  of  data  from  computa'onal  &  experimental  evidence  with  data   from  predic'on  tools,  to  generate  a  reliable  set  of  structural  annota=ons.       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
  19. 19. 19 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
  20. 20. 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. 20 Image: www.BroadInstitute.org
  21. 21. MANUAL ANNOTATION
 working concept Precise  elucida=on  of  biological  features   encoded  in  the  genome  requires  careful   examina=on  and  review.     Schiex  et  al.  Nucleic  Acids  2003  (31)  13:  3738-­‐3741   Automated Predictions Experimental Evidence Manual Annotation – to the rescue. 21 cDNAs,  HMM  domain  searches,  RNAseq,   genes  from  other  species.  
  22. 22. 22 MANUAL ANNOTATION
 objectives Iden=fies  elements  that  best   represent  the  underlying  biology   and  eliminates  elements  that   reflect  systemic  errors  of   automated  analyses.   Assigns  func=on  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  
  23. 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. GENOME ANNOTATION
 an inherently collaborative task APOLLO 24 Researchers  oEen  turn  to  colleagues  for  second   opinions  and  insight  from  those  with  exper$se  in   par$cular  areas  (e.g.,  domains,  families).  
  25. 25. APOLLO
 collaborative genome annotation editing tool 25 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    
  26. 26. APOLLO ARCHITECTURE
 simpler, more flexible APOLLO 26 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
  27. 27. 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   Apollo.       v  Gate  keeping  and  monitoring.   v  Tutorials,  training  workshops,  and  “geneborees”.   27 DISPERSED COMMUNITIES collaborative manual annotation efforts APOLLO
  28. 28. 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 28
  29. 29. Apollo   h=p://genomearchitect.org/web_apollo_user_guide  
  30. 30. 1.  Select  or  find  a  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.   4.  If  necessary,  adjust  the  gene  model.   5.  Check  your  edited  gene  model  for  integrity  and  accuracy  by   comparing  it  with  available  homologs.   6.  Comment  and  finish.   Becoming Acquainted with Web Apollo 30 | 30 GENERAL PROCESS OF CURATION
 main steps to remember
  31. 31. 31 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  combina=on  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.  
  32. 32. Let’s  play  with  Apollo.  
  33. 33. REMOVABLE SIDE DOCK
 with customizable tabs HIGHLIGHTED IMPROVEMENTS 33 Annotations Organism Users Groups AdminTracks Reference Sequence
  34. 34. EDITS & EXPORTS
 annotation details, exon boundaries, data export HIGHLIGHTED IMPROVEMENTS 34 1 2 Annotations 1 2
  35. 35. HIGHLIGHTED IMPROVEMENTS 35 Reference Sequences 3 FASTA   GFF3   EDITS & EXPORTS
 annotation details, exon boundaries, data export 3
  36. 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. •  Hovering over annotation in progress brings up an information pop-up.
  37. 37. 37 | 37 USER NAVIGATION Becoming Acquainted with Web Apollo. •  Annotation right-click menu
  38. 38. 38 Annota'ons,  annota'on  edits,  and  History:  stored  in  a  centralized  database.   38 USER NAVIGATION Becoming Acquainted with Web Apollo.
  39. 39. 39 The  Annota'on  Informa=on  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. 40 The  Annota'on  Informa=on  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. 41 | 41 USER NAVIGATION Becoming Acquainted with Web Apollo. •  ‘Zoom  to  base  level’  op'on  reveals  the  DNA  Track.  
  42. 42. 42 | 42 USER NAVIGATION Becoming Acquainted with Web Apollo. •  Color  exons  by  CDS  from  the  ‘View’  menu.  
  43. 43. 43 | Zoom  in/out  with  keyboard:   shiv  +  arrow  keys  up/down   43 USER NAVIGATION Becoming Acquainted with Web Apollo. •  Toggle  reference  DNA  sequence  and  transla=on  frames  in  forward   strand.  Toggle  models  in  either  direc'on.  
  44. 44. Annota'ng  
  45. 45. simple  cases  
  46. 46. “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.       46 | 46 ANNOTATING SIMPLE CASES Becoming Acquainted with Web Apollo. SIMPLE CASES
  47. 47. 47 | •  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  aver  each  edit.   47 ADDING EXONS Becoming Acquainted with Web Apollo. SIMPLE CASES
  48. 48. 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.     48 | To  add  a  new  spliced  UTR  to  an  exis'ng  annota'on   follow  the  procedure  for  adding  an  exon.   48 ADDING UTRs Becoming Acquainted with Web Apollo. SIMPLE CASES
  49. 49. 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.       49 | 49 CHECK EXON INTEGRITY Becoming Acquainted with Web Apollo. SIMPLE CASES
  50. 50. 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.     50 | 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.   50 EXON STRUCTURE INTEGRITY Becoming Acquainted with Web Apollo. SIMPLE CASES
  51. 51. 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   51 ORFs AND SPLICE SITES Becoming Acquainted with Web Apollo. SIMPLE CASES
  52. 52. 52 | 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.     Canonical  splice  sites:   3’-­‐…exon]GA  /  TG[exon…-­‐5’   5’-­‐…exon]GT  /  AG[exon…-­‐3’   reverse  strand,  not  reverse-­‐complemented:   forward  strand   52 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.    
  53. 53. 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  by  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).     53 | 53 ‘START’ AND ‘STOP’ SITES Becoming Acquainted with Web Apollo. SIMPLE CASES
  54. 54. complex  cases  
  55. 55. 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  Annota=ons’  area  shiv-­‐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.   55 | 55 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
  56. 56. 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.     56 | 56 COMPLEX CASES split a gene prediction Becoming Acquainted with Web Apollo. COMPLEX CASES
  57. 57. DNA  Track   ‘User-­‐created  Annota=ons’  Track   57 COMPLEX CASES correcting frameshifts and single-base errors Becoming Acquainted with Web Apollo. COMPLEX CASES 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.  
  58. 58. 58 COMPLEX CASES correcting selenocysteine containing proteins Becoming Acquainted with Web Apollo. COMPLEX CASES
  59. 59. 59 COMPLEX CASES correcting selenocysteine containing proteins Becoming Acquainted with Web Apollo. COMPLEX CASES
  60. 60. 1.  Apollo  allows  annotators  to  make  single  base  modifica'ons  or  frameshivs  that  are  reflected  in   the  sequence  and  structure  of  any  transcripts  overlapping  the  modifica'on.  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  Inser=on’  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  Dele=on’  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  Subs=tu=on’  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,  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.    60 | 60 Becoming Acquainted with Web Apollo. COMPLEX CASES COMPLEX CASES correcting frameshifts, single-base errors, and selenocysteines
  61. 61. Follow  the  checklist  un'l  you  are  happy  with  the  annota'on!   And  remember  to…   –  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.   61 | 61 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.
  62. 62. Checklist  
  63. 63. 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   –  Frameshigs     –  error  in  the  genome  assembly?   –  Selenocysteines,  single-­‐base  errors,  etc   63 | 63 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
  64. 64. Example  
  65. 65. Example Example 65 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).  
  66. 66. 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 66
  67. 67. PubMed Search: 
 what’s new? Example 67
  68. 68. PubMed Search: what’s new? Example 68 “Ten  popula'ons  (3  cultures,  7  from  California  water   bodies)  differed  by  at  least  550-­‐fold  in  sensi=vity  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   pes=cide  transport  from  land-­‐based  applica'ons  into   aqua'c  systems.”  
  69. 69. How many sequences for our gene of interest? Example 69 •  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?  
  70. 70. Retrieving sequences for 
 sequence similarity searches. Example 70 >vgsc-­‐Segment3-­‐DomainII   RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDG QMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR
  71. 71. BLAT search Example 71 >vgsc-­‐Segment3-­‐DomainII   RVFKLAKSWPTLNLLISIMGKTVGALGNLTFVLCIIIFIFAVMGMQLFGKNYTEKVTKFKWSQDG QMPRWNFVDFFHSFMIVFRVLCGEWIESMWDCMYVGDFSCVPFFLATVVIGNLVVSFMHR
  72. 72. BLAT search Example 72
  73. 73. Customizations: 
 high-scoring segment pairs (hsp) in “BLAST+ Results” track Example 73
  74. 74. Creating a new gene model: drag and drop Example 74 •  Apollo automatically calculates ORF. In this case, ORF includes the high-scoring segment pairs (hsp).
  75. 75. Available Tracks Example 75
  76. 76. Get Sequence Example 76 http://blast.ncbi.nlm.nih.gov/Blast.cgi
  77. 77. Also, flanking sequences (other gene models) vs. NCBI nr Example 77 In  this  case,  two  gene   models  upstream,  at  5’   end.   BLAST  hsps  
  78. 78. Review alignments Example 78 HaztTmpM006234   HaztTmpM006233   HaztTmpM006232  
  79. 79. Hypothesis for vgsc gene model Example 79
  80. 80. Editing: merge the three models Example 80 Merge  by  dropping  an   exon  or  gene  model   onto  another.   Merge  by  selec'ng   two  exons  (holding   down  “Shiv”)  and   using  the  right  click   menu.   or…  
  81. 81. Editing: correct boundaries, delete exons Example 81 Modify  exon  /  intron   boundary:     -­‐  Drag  the  end  of  the   exon  to  the  nearest   canonical  splice  site.   -­‐  Use  right-­‐click  menu.   Delete  first  exon  from   HaztTmpM006233  
  82. 82. Editing: set translation start Example 82
  83. 83. Editing: modify boundaries Example 83 Modify  intron  /   exon  boundary   also  at  coord.   78,999.  
  84. 84. Finished model Example 84 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  
  85. 85. 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 85 Comments   (if  applicable)  
  86. 86. Demo  video  
  87. 87. APOLLO
 demonstration Apollo  demo  video  available  at:     h=ps://youtu.be/VgPtAP_fvxY   DEMO 87
  88. 88. APOLLO DEVELOPMENT APOLLO DEVELOPERS 88 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
  89. 89. •  Berkeley  Bioinforma=cs  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   •      •  For  your  a^en=on,  thank  you!   Thank you. 89 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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