An Introduction to Second-­Generation Sequencing: Mapping and Counting

Second-generation sequencing technologies are changing genomics research and many groups want to get in on the action. This talk simply outlines some of the dos and don'ts that I pass along to folks before they embark on a sequencing project. Included are a few slides on mRNA, miRNA, genomic tumor/normal, structural variation, and DNAse/ChIP sequencing.

Transcript

1. Sean  Davis,  M.D.,  Ph.D. Gene0cs  Branch,  Center  for  Cancer  Research Na0onal  Cancer  Ins0tute Na0onal  Ins0tutes  of  Health h>p://watson.nci.nih.gov/~sdavis An  Introduc+on  to   Second-­‐Genera+on  Sequencing: Mapping  and  Coun+ng 1 Friday, January 13, 2012
2. Normal   Karyotype Tumor   Karyotype 2 Friday, January 13, 2012
3. The  Central  Dogma 3 Friday, January 13, 2012
4. phenotype Gene  Copy   Number Sequence   Varia4on Chroma4n   Structure  and   Func4on Gene  Expression Transcrip4onal   Regula4on DNA  Methyla4on 4 Friday, January 13, 2012
5. phenotype Gene  Copy   Number Sequence   Varia4on Chroma4n   Structure  and   Func4on Gene  Expression Transcrip4onal   Regula4on DNA  Methyla4on Pa+ent  and   Popula+on   Characteris+cs 4 Friday, January 13, 2012
6. 5 Sequencing  Instruments • Illumina – GAIIx,  MiSeq,  HiSeq  2000,  HiSeq  2500 • Life  Technologies – SoLID,  Ion  Torrent,  Proton • PacBio – PacBio  RS • Roche – 454  GS  Junior,  GS  FLX • Complete  Genomics* 5 Friday, January 13, 2012
7. Hypothesize Sequence Map to reference Count Interpret 6 Friday, January 13, 2012
8. 7 Friday, January 13, 2012
9. + 8 Friday, January 13, 2012
10. 9 Friday, January 13, 2012
11. = 10 Friday, January 13, 2012
12. Your  Nature  Paper 11 Friday, January 13, 2012
13. 12 Friday, January 13, 2012
14. Q  =  -­‐10  log10  p 13 Friday, January 13, 2012
15. Mapping  to  the  Genome 14 14 Friday, January 13, 2012
16. Warmup:  Sequencing  a  BAC 15 Friday, January 13, 2012
17. Sequencing  a  BAC 16 Friday, January 13, 2012
18. Sequence  Coverage 17 Friday, January 13, 2012
19. Repeats 18 Friday, January 13, 2012
20. Repeats 19 Friday, January 13, 2012
21. Repeats  are  not  created  equal 20 Friday, January 13, 2012
22. Tag  Count  Sequencing 21 ChIP-­‐Seq DNAse-­‐Seq Nucleosome  Posi0oning Histone  Modifica0ons 21 Friday, January 13, 2012
23. DNAse-­‐chip  Method Crawford,  G.E.,  Davis,  S.,  Scacheri,  P.C.,  Renaud,  G.,  Halawi,  M.J.,  Erdos,  M.R.,  Green,  R.,   Meltzer,  P.S.,  Wolfsberg,  T.G.,  and  Collins,  F.S.  Nat  Methods,  2006 22 Friday, January 13, 2012
24. DNAse  Sites  Rela0ve  to  Genes 23 Friday, January 13, 2012
25. DNAse  HS  Sites  and  Gene  Expression  DNAse  HS  sites  near   transcrip0on  start  sites   are  associated  with   ac0vely  transcribed   genes. 24 Friday, January 13, 2012
26. Barski  A,  Zhao  K.  Genomic  loca0on  analysis  by  ChIP-­‐Seq.  J  Cell  Biochem.  2009 25 Friday, January 13, 2012
27. 26 Tag  Count  Sequencing  Pointers • Good  an0body  necessary  for  good  results • Posi0ve  controls  for  quality  control • Experimental  controls  and  experimental  design   are  important • Need  replicates  if  asking  about  generalizability • Amount  of  sequencing  varies  from  one   applica0on  to  the  next • Mul0plexing  and  indexing 26 Friday, January 13, 2012
28. 27 RNA-­‐Seq 27 Friday, January 13, 2012
29. 28 Friday, January 13, 2012
30. 29 29 Friday, January 13, 2012
31. 30 30 Friday, January 13, 2012
32. 31 Friday, January 13, 2012
33. RNA-­‐Seq  Applica0ons • Transcript  quan0fica0on  and  differen0al   expression • Splicing  and  isoform  quan0fica0on • Fusion  gene  discovery • Novel  transcript  discovery • Allele-­‐specific  expression • Variant  discovery  and  quan0fica0on • RNA-­‐edi0ng  observa0on 32 32 Friday, January 13, 2012
34. miRNA  Profiling 33 Friday, January 13, 2012
35. 34 Friday, January 13, 2012
36. 35 RNA-­‐Seq  Pointers • Replicates  necessary  for  any  sta0s0cal  inference – Not  doing  replicates  has  a  cost! • Easier  to  find  differen0al  expression  for  longer  and   more  highly  expressed  genes – Downstream  Gene  Set  Analysis  (GO,  Pathways)  need  to   be  adjusted • Quality  of  transcriptome  annota0on  important • Mapping  and  quan0fica0on  is  complicated • Microarrays  are  not  ex0nct  for  transcriptome   profiling 35 Friday, January 13, 2012
37. 36 Friday, January 13, 2012
38. Genomic  Sequencing Targe0ng  the  Exome 37 Friday, January 13, 2012
39.  Long  oligos  synthesized  on   arrays  (DNA)  RNA  baits  synthesized  from   DNA  oligo  template  RNA  baits  hybridized  to   DNA  sequencing  library  Targets  captured  using   beads  and  bio0n-­‐labeled   baits  RNA  bait  degraded,  leaving   sequencing  library  enriched   for  target  regions 38 Friday, January 13, 2012
40. 39 Friday, January 13, 2012
41. 40 Friday, January 13, 2012
42. Variant  Calling  and  Evalua0on 41 Friday, January 13, 2012
43. 42 Friday, January 13, 2012
44. The  Cancer  Genome  Atlas  Research  Network  Nature  000,  1-­‐8  (2008)  doi:10.1038/nature07385 Frequent  gene0c  altera0ons  in  three  cri0cal  signalling  pathways. 43 Friday, January 13, 2012
45. Sequencing  Tumor/Normal  Pairs 44 Friday, January 13, 2012
46. Good  SNP Tumor Novo Tumor BWA Normal BWA Normal Novo 45 Friday, January 13, 2012
47. Suspect  Variant Tumor Novo Tumor BWA Normal BWA Normal Novo 46 Friday, January 13, 2012
48. Soma0c  (tumor  only)  Variant Tumor Novo Tumor BWA Normal BWA Normal Novo 47 Friday, January 13, 2012
49. Likely  False  Posi0ve  (normal  only) Tumor Novo Tumor BWA Normal BWA Normal Novo 48 Friday, January 13, 2012
50. LOH Tumor Novo Tumor BWA Normal BWA Normal Novo 49 Friday, January 13, 2012
51. 50 Structural  Varia0on  and Copy  Number  Es0ma0on 50 Friday, January 13, 2012
52. 51 Friday, January 13, 2012
53. 52 Friday, January 13, 2012
54. Medvedev  et  al.,  Nature  2009 53 Friday, January 13, 2012
55. 54 Friday, January 13, 2012
56. 55 Friday, January 13, 2012
57. 56 Friday, January 13, 2012
58. 57 Friday, January 13, 2012
59. 58 Friday, January 13, 2012
60. Public  Data  1000  Genomes,  HapMap,  Encyclopedia  of  DNA   Elements  (ENCODE),  The  Cancer  Genome  Atlas   (TCGA),  COSMIC  database  NCBI  Gene  Expression  Omnibus  (GEO)  Sequence  Read  Archive  (SRA)  Hundreds  of  datasets  not  submi>ed  publicly  or   housed  only  in  proprietary  databases 59 Friday, January 13, 2012
61. Phenotype Gene  Copy   Number Sequence   Varia4on Chroma4n   Modifica4on Gene   Expression Transcrip4onal   Regula4on DNA   Methyla4on 60 Friday, January 13, 2012
62. Phenotype Gene  Copy   Number Sequence   Varia4on Chroma4n   Modifica4on Gene   Expression Transcrip4onal   Regula4on DNA   Methyla4on 60 Friday, January 13, 2012
63. Phenotype Gene  Copy   Number Sequence   Varia4on Chroma4n   Modifica4on Gene   Expression Transcrip4onal   Regula4on DNA   Methyla4on 60 Friday, January 13, 2012
64. 61 Gemng  Sequencing  Done Gemng  Help 61 Friday, January 13, 2012