Genotyping By Sequencing (GBS) Method Overview

Transcription

1 enotyping By Sequencing (BS) Method Overview RJ Elshire, JC laubitz, Q Sun, JV Harriman ES Buckler, and SE Mitchell

2 Topics Presented Background/oals BS lab protocol Illumina sequencing review BS adapter system How BS differs from RAD Modifying BS for different species Workflow in our lab

3 Background enotyping by sequencing (BS) in any large genome species requires reduction of genome complexity I Target enrichment Long range PCR of specific genes or genomic subsets Molecular inversion probes II Restriction Enzymes (REs) *Technically less challenging* Methylation sensitive REs filter out repetitive genomic fraction Sequence capture approaches hybridization based (microarrays)

4 QTL are often located in non coding regions Vgt1, Tb, B regulatory regions kb from gene QTL Exon Exon Exon Exon Map large numbers of genome wide markers Exon capture

5 Our goal is to create a public genotyping/informatics platform based on next generation sequencing Create inexpensive, robust multiplex sequencing protocol Low coverage Sequencing Illumina A Informatics Pipelin Combine genotypic & phenotypic data for S and WAS Impute missing data Anchor markers across the genome

6 Open Source Method available for anyone to use / modify Analysis pipeline details and code are public Promote dataset compatibility Method published in PLoS ONE to promote accessibility enotype calls publically available

7 Overview of enotyping by Sequencing (BS) Restriction site ( ) sequence tag Sample1 Loss of cut site < 450 bp Sample2 Focuses Nexten sequencing power to ends of restriction fragments Scores both SNPs and presence/absence markers

8 BS is a simple, highly multiplexed system for constructing libraries for next gen sequencing Reduced sample handling Few PCR & purification steps No DNA size fractionation Efficient barcoding system Simultaneous marker discovery & genotyping Scales very well

9 BS 96 plex Protocol ( overview) Now at 384 plex 1 Plate DNA & adapter pair 2 Digest DNA with RE 3 Ligate adapters

10 BS Adapters and Enzymes Barcode Adapter P1 Sticky Ends Common Adapter P2 Illumina Sequencing Primer 2 Barcode (4 8 bp) Restriction Enzymes Illumina Sequencing Primer 1 ApeKI CWC PstI CTCA EcoT22I ATCA T 5 3

11 BS 96 plex Protocol ( overview) 1 Plate DNA & adapter pair 2 Digest DNA with RE 3 Ligate adapters 4 Pool 96 samples Clean up Primers 5 PCR

12 PRC primers: Pooled Digestion/Ligation Reactions (n=94) PCR BS Library Insert Insert P1 P2 O1 P1 P2 O2

13 BS 96 plex Protocol ( overview) Clean up Clean up 1 Plate DNA & adapter pair 2 Digest DNA with RE 3 Ligate adapters 4 Pool 96 DNA aliquots Primers 5 PCR 6 Evaluate fragment sizes

14 Perform Titration to Minimize Adapter Dimers Before Sequencing NOTE: Done once with a small number of samples Adapter dimers constitute only 005% of raw sequence reads Size Standards Optimal adapter amount Fluorescense intensity 15 bp Adapter Dimer Library 1500 bp Time Time

15 Small Fragments are Enriched in BS Libraries 40% 35% 30% 25% REFENOME B73 Refen v1 IBM (B73 X Mo17) RILs 20% 15% 10% 5% 0% Total Fragments >10000 ApeKI fragment size (bp)

16 384 plex BS Results for Maize Reads Mean read count per line = 528,000 cv =

17 Illumina Sequencing by Synthesis Review Flowcell 8 channels Solid Phase Oligos

18 Cluster Formation Amplifies Sequencing Signal Denatured Library Bridge Amplification Flow cell with bound oligos Linearization

19 A C T C A C T C T T P1 primer C A C T C T A A C T C T C T T TC TCA Sequencing by Synthesis Flowcell HiSeq 2000

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21 A C T C T A C T C T C A C T C T T N A C T C T A C T C T A C T C T In Phase Out of Phase

22 BS captures barcode and insert DNA sequence in single read Sequencing Primer 1 Read 1 Sequencing Primer 1 Read 1 Barcode RE cut site Insert DNA Insert DNA Sequencing Primer 2 Barcode Read 2 Illumina BS

23 Variable Length BS Barcodes Solves Sequence PhasingIssues First 12 nt used to calculate phasing Algorithm assumes random nt distribution Incorrect phasing causes incorrect base calls ood design and modulating the RE cut site position with variable length barcodes produces even nt distribution Read 1 Insert DNA Barcode Read 2 Barcode RE cut site Insert DNA Illumina BS

24 Invariant BS barcodes cause loss of signal intensity

25 Successful BS sequencing run

26 Most significant BS technical issue? DNA quality

27 BS does not use standard Y adapters Standard BS Ligation PCR Ligation 100% Different Ends 50% Same Ends 50%

28 Same ended Fragments Do Not Form Clusters Denatured library Bridge Amplification Cleaved from surface Cluster Formation & Linearization No P1 binding site Flow Cell with Bound Oligos

29 BS vs RAD Restriction site ( ) sequence tag Sample1 Loss of cut site < 450 bp Sample2 Focuses Nexten sequencing power to ends of restriction fragments Scores both SNPs and presence/absence markers

30 Digest Ligate adapters Pool Random shear Size select Ligate Y adapters PCR RAD BS Reference Davey et al 2011

31 Modifying BS Considerations for using BS with new species and / or different enzymes

32 Why Modify the BS Protocol? More markers Fewer markers (deeper sequence coverage per locus) Increase multiplexing More genome appropriate (avoid more repetitive DNA classes) Other novel applications (ie, bisulfite sequencing)

33 enome Sampling Strategies Vary by Species Dependent on Factors that Affect Diversity: Mating System (Outcrosser, inbreeder, clonal?) Ploidy (Haploid, diploid, auto or allopolyploid?) eographical Distribution (Island population, cosmopolitan?)

34 Other Factors enome size The size of the genome has some bearing on the size of the fragment pool Amount of repetitive DNA directly correlated with genome size enome composition The composition of the genome can affect the frequency and distribution of the cut sites

35 Sampling large genomes with methylationsensitive restriction enzymes BS Library Sequenced Fragments Methylated DNA 5 base cutter Unmethylated DNA 6 base cutter

36 Optimizing BS in New Species rape Maize Cacao Sorghum Rice Shrub willow oose Barley Raspberry Deer Mouse Tunicate Vole iant squid Cassava Cassava Solitary Bee Yeast Scrub jay

37 Choosing Appropriate Restriction Enzymes Life is like a bowl of chocolates

38 ApeKI iant Squid PstI oose

39 ApeKI Deer Mouse PstI

40 ApeKI Shrub Willow PstI EcoT22I

41 BS Adapter Design

42 Barcode Design Considerations Barcode sets are enzyme specific Must not recreate the enzyme recognition site Must have complementary overhangs Sets must be of variable length Bases must be well balanced at each position Must different enough from each other to avoid confusion if there is a sequencing error At least 3 bp differences among barcodes Must not nest within other barcodes No mononucleotide runs of 3 or more bases adapters

43 BS SNP calls in Sorghum bicolor c10hmp alleles chrom SC283 BR007B RIL_100 RIL_101 RIL_102 RIL_103 RIL_104 RIL_105 RIL_106 RIL_107 RIL_108 RIL_109 RIL_10 RIL_110 RIL_111 RIL_112 RIL_113 RIL_114 RIL_115 S10_29954 C/A 10 A N A C A N N C C N N N N N N N N C N S10_29963 A/C 10 C N C A C N N A A N N N N N N N N A N S10_29965 T/C 10 C N C T C N N T T N N N N N N N N T N S10_84178 C/ 10 N N C N N N N N N N N N N C N N N N S10_84512 T/C 10 T T N N T N T N N N N C N N N N N N N S10_84513 C/T 10 C C N N C N C N N N N T N N N N N N N S10_85556 /A 10 A A N N N R N A N R S10_85556 /A 10 N N A A N N N N A N S10_ T/C 10 T C T C T C T N N T T N N N C N N T T S10_ T/C 10 T C N N N N N T T N N N N N N N N N N S10_ /A 10 N N A N N N N N N N A A N N S10_ /A 10 A N A A N N N N N N N N N S10_ /A 10 A N A N N N N N N N N N N N S10_ T/ 10 T N T N N N N T T T N N S10_ C/T 10 T C N C T N T N N T T N T C C C N T N S10_ /A 10 A N A N N A A N S10_ C/ 10 N C S C C C C N C C N C N C N S10_ /A 10 N A A A N N N A A N S10_ C/T 10 C N N T N N N N C N C N N N N N N C C S10_ T/ 10 T N T N T T N T T T T T N N T N T S10_ T/ 10 T T T N T T T T T T N T T T S10_ /A 10 N A N A N N N N N N A N N N N S10_ /T 10 T T N N N N N N N T S10_ C/T 10 C T C T C N N C C C N N N N N T C C C S10_ T/C 10 T C T C T C N N T T N N T N N N T N N S10_ C/A 10 N N N N A N A N N N N N N N N N N N N S10_ /A 10 N N N N A N A N N N N N N N N N N N N S10_ C/T 10 N N C N N N N C T C N N C T N N C N C S10_ T/C 10 T N T N N N N N N N N N N N N N N T T S10_ /T 10 N N N N N N N N N N N N N N S10_ A/T 10 A T N N A N N A A A N A A N T T A A A S10_ A/T 10 A T A T N N N A N A N A N N T T A N A S10_ C/T 10 N N C N C N C C C N N N C T N N C N C S10_ C/T 10 C T C T C N N C N C C N C T T N C C N S10_ A/C 10 A C A N A N A A A A A A A C C N A A A S10_ T/C 10 T C T C T C N T T T T N T N C N T T T

44 Missing Data Strategies Impute Technical Options Reduce the multiplexing level Sequence the same library multiple times Molecular Options Choose less frequently cutting enzymes

45 BS Workflow DNA sample info entered to webform Project approved? Samples shipped HTS database Lab BS libraries made Analysis Pipelines DNA sequence data Reference genome Non reference genome Data File SNPs/Sample Data File States/Sample

46 BS Team Rob Elshire Ed Buckler Sharon Mitchell Jeff laubitz James Harriman Qi Sun