MHC Region. MHC expression: Class I: All nucleated cells and platelets Class II: Antigen presenting cells

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1 DNA based HLA typing methods By: Yadollah Shakiba, MD, PhD

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3 MHC Region MHC expression: Class I: All nucleated cells and platelets Class II: Antigen presenting cells

4 Nomenclature of HLA Alleles

5 Assigned as of April 2016 HLA class I Alleles Gene A B C Allelesl 3, ,242 2,950 Proteins 2,396 3,131 2,089 Nulls

6 DNA Based HLA typing SSP SSOP Sanger SBT Next generation sequencing

7 PCR SSP maximum, GA, CT, TT; strong, CC; medium, AA, GG; Weak, CA, GT; AT, GC

8 HLA-A Exon 3 Sequences

9 HLA-A*01 PCR-SSP Internal control: GH F-TGCCAAGTGGAGCACCCAA R-GCATCTTGCTCTGTGCAGAT 796 bp HLA-A*01 Allele group specific primer Forward: TCTCACACCATCCAGATA Reverse: ACCGGCCCTCCAGGTAGA 220 bp

10 HLA-A*36 PCR-SSP Mix A*36 F1: GTGGGAGGCGGTCCATGC 36:01 36:05 R1:AGGTATCTGCGGAGCCAC 03:187/11:155/31:62 PCR product 80 bp

11 HLA-A*36 A PCR-SSP primer blast

12 Applications of PCR-SSP Rapid HLA screening (Low resolution) Allele group amplification before SBT HLA and disease study (AS: B*27, RA:DRB1*04, narcolepsy: DQB1*06:02, 02 Bh Behçetdisease: B*51) High resolution typing (sub-typing)

13 The more alleles The more problems!!

14 Sequence Based Typing (SBT) Sanger SBT SBT by NGS

15 Sanger Sequencing The chain-termination method invented by Fred Sanger. DNA polymerase always adds new bases to the 3 end of a primer that is base-paired to the template DNA. dideoxy nucleotides (ddntps)

16 Manual Sanger DNA sequencing

17 Sanger platforms

18 Recent advances in Sanger sequencing (automated) ddntp's with fluorescent markers we can mix all four types together and do one reaction instead of four Theresultingfragmentsarestillof are still different lengths Separate fragments via electrophoresis in gelfilled capillary tubes. Automatic sequencing machines read output

19 Sanger HLA Sequencing

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25 HLA typing by automated SBT Unrelated HSCT Cord blood transplantation (DRB1) HSCT from sibling with ambiguities Kidney transplant? HLA match maker

26 NGS platforms Illumina MiSeq Ion Torrent PGM Pacific Biosciences RSII Illumina MiniSeq ThermoFisher 26 Ion S5 PacBio Sequel

27 Illumina sequencing Amplification lf strategies Amplicon sequencing Target Library Amplify Shotgun sequencing Sequence Sequence Analyse

28 HLA amplicon quantification Target Pooling UT R UT R Gelelectrophoresis Qubit Fragment Equimolar amplicon pooling Adapter e.g. 96 samples, 11 loci => 96 amplicon pools Index Quant. Amplify NGSgo AmpX amplicon Concentration (ng/µl) #1 #2 #3 Average concentration (ng/µl) Amplicon length (bp) Amplicon volume (µl) in pool HLA A ,0 HLA B ,1 HLA C ,8 HLA DRB ,6 HLA DQB Sequence Analyse

29 Pooling of HLA amplicons Target Pooling Fragment Adapter Index Quant. Amplify Sequence Analyse Illumina MiSeq Workflow

30 HLA library preparation Reaction #1: Enzymatic fragmentation, end repair, A tailing

31 library preparation Step 2: Ligation of Illumina compatible adapter Illumina MiSeq Workflow

32 Paired end Sequencing Illumina approach 300 nt P5 ID Rd1 SP DNA fragment Rd2 SP ID P7 G T C C R A G A G G G C C G C G G G M G C C.... A A G C...

33 Paired end Sequencing Illumina approach In silico linking of information for larger fragment sizes 150 nt 150 nt P5 ID Rd1 SP DNA fragment Rd2 SP ID P7 G T C C R A G A G G G C C G C G G G M G C C.... A A G C...

34 DNA clean up and size selection Target Pooling Fragment Adapter Index Quant. Crowding agents (20% PEG, 2.5M NaCl) Beads : DNA ratio > affects size selection Amplify Sequence Analyse Illumina MiSeq Workflow

35 Indexing PCR Target Pooling Fragment Adapter Index Quant. Amplify Sequence Analyse Illumina MiSeq Workflow

36 HLA library preparation Dual indexing PCR: insert index sequencing primer binding sites flow cell attachment sites index Illumina MiSeq Workflow

37 Indexing PCR: Dual Indexing Target Pooling Fragment Adapter Index Quant. Amplify Sequence Analyse Illumina MiSeq Workflow

38 Dual indexing 4x24 rxn 2x96 rxn 1x384 rxn N 50 IndX kits: One adapter Panel of indices (Illumina specific) Combination of indices sufficient for dual indexing of4x24 4x24, 2x96, or1x384libraries Illumina MiSeq Workflow

39 HLA library pooling Target Pooling LIB 1 LIB 2 LIB 3 LIB 384 Fragment Adapter 1500 bp 1000 bp 500 bp Library > 400 bp Index Quant. Amplify 100 bp Sequence Analyse Illumina MiSeq Workflow

40 Agrose gel electrophoresis Good quality DNA fragments with a size range of bp

41 Library quantification with KAPA P5 P7 Target Pooling Fragment Adapter Index Quant. 95 o C 95 o C Amplify Sequence 60 o C Analyse Illumina MiSeq Workflow

42 Library quantification with KAPA Target Pooling Fragment Adapter Index Quant. Amplify Sequence Analyse Illumina MiSeq Workflow

43 MiSeq run Target Denature library Prepare Sample Sheet Load denatured library on MiSeq cartridge Pooling Fragment Adapter Index Quant. Amplify Sequence 300 cycle kit run => hours Analyse

44 MiSeq reagent kit Box 1 ( 20 C): 1) Pre filled ready to use reagent cartridge 2) Tb Tube of HT 1 buffer Box 2 (+4 C): 3) Container with flow cell 4) Incorporation buffer

45 Selection of MiSeq reagent cartridge MiSeq Reagent kit Kit size (cycles) Differences between cartridges are: MiSeq Reagent 50, 300, Kit v2 500 MiSeq Reagent 150, 600 quality Kit v3 Reagents Read length and quality Run time Costs Recommended for NGSgo => 300 cycle, v2

46 Paired end sequencing strategies 300 vs. 500 cycle kit 2x150 bp P5 ID Rd1 SP DNA fragment (~400 bp) Rd2 SP ID P7 NGSengine: optimal pairs 2x250 bp P5 ID Rd1 SP DNA fragment (~400 bp) Rd2 SP ID P7

47 Three MiSeq flow cell types Standard Micro Nano Standard Micro Nano SURFACE: Top Bottom SURFACE: Top Bottom SURFACE: Top Bottom 28 tiles 8 tiles 2 tiles Same DNA input concentration and same chemistry Different number of tiles for imaging g=> different read output

48 Flow cell guidelines

49 Summary MiSeq chemistry Target generation Library preparation p Clonal amplification Sequencing Data analysis Illumina MiSeq Chemistry

50 Summary MiSeq chemistry Target generation Library preparation p Clonal amplification Sequencing Data analysis Illumina MiSeq Chemistry

51 Sequencing data A image C image G image T image Illumina MiSeq Chemistry

52 Ion torrent Workflow Target generation Library preparation NGSgo reagents Clonal amplification Enrichment ISPs Ion One Touch 2 / Ion Chef Sequencing Ion Torrent tpgm Data analysis NGSengine Ion Torrent workflow

53 Target generation Target generation UT R UT R HLA A (3.1 kb) Library preparation UT UT HLA B (3.4 kb) R UT R R UT R HLA C (3.4 kb) UT R UT R HLA DRB1 ( kb) Amplified exon Exon not amplified UT R UT R UT R UT R UT R UT R HLA DQB1 ( kb) HLA DPB1 (5.0 & 5.7 kb) HLA DPA1 (4.7 kb) UT R UT R HLA DQA1 ( kb) UT R UT R HLA DRB3 (3.8 kb) UT R UT R HLA DRB4 (0.4 & 1.3 kb) UT R UT R HLA DRB5 (4.0 kb) Ion Torrent workflow

54 Pooling of HLA amplicons Target generation Library preparation Measurement with ihqubit Equimolar pooling of HLA amplicons for each sample Ion Torrent workflow

55 Library preparation Fragmentation, end repair and da tailing Adapter ligation X adapter contains barcode Ion Torrent workflow

56 Library preparation LIB 1 LIB 2 LIB 3 LIB 24 Equivolume pooling Size selection with SPRI beads Ion Torrent workflow

57 Library preparation 10 kb 3 kb 1kb 500 bp Size of generated fragments > 400 bp Quantification by KAPA, qpcr Using adapter specific primers 9 pm of final library pool needed Ion Torrent workflow

58 Workflow Target generation Library preparation Clonal amplification Enrichment ISPs Ion One Touch 2 Ion Chef Sequencing Data analysis Ion Torrent workflow

59 Clonal amplification DNA fragments bind ion sphere particles (ISPs) with P adapter. Amplification of bound DNA fragments. Biotinylation of X adapter Quality control: %ISPs covered with DNA QC kit for Qubit Ion Torrent workflow

60 Template preparation systems Ion One Touch 2 System Ion Chef System Clonal amplification system Performs all steps from clonal Enrichment system amplification to chip loading Chip loading manually Can perform two chips simultaneously Ion Torrent workflow

61 Clonal amplification Ion Torrent workflow

62 Clonal amplification Ion Torrent workflow

63 Enrichment ISPs Streptavidin coated magnetic beads bind to biotinylated DNA Polyclonal ISPs are not removed Empty ISPs are removed Ion Torrent workflow

64 Enrichment ISPs Touch pad Mechanical arm Pipet tip loader Strip (flanked by magnets) Ion Torrent workflow

65 Workflow Target generation Library preparation Clonal amplification Enrichment ISPs Sequencing Ion Torrent tpgm Data analysis Ion Torrent workflow

66 Ion Torrent sequencers Ion Proton Ion PGM Ion S5 Ion Torrent workflow

67 Ion Torrent sequencers Nitrogen Hands on Capacity Mean supply work read length Ion Yes 1 hour High 200 bp Yes Proton Ion PGM Yes 1 hour Low 300 bp Yes Ion S5 No 5 minutes Very high 300 bp NGSgo compati ble Yes Ion Torrent workflow

68 Chip loading Ion 314 Ion 316 Ion Mb 100 Mb thousand reads per run 300 Mb 1 Gb 2 3 million reads per run 600 Mb 2 Gb 4 5,5 million reads per run 6samples 5 loci 24 samples 5 loci 24 samples 11 loci Ion Torrent workflow

69 Chip loading Incubation with sequence primer sequence polymerase Each ISP fits in a hole on chip Amount of loaded ISPs measured by loading density (%) Ion Torrent workflow

70 Sequencing A flow is the event of exposing the chip to one of the 4 dntps, followed by a wash step The flows of all 4 dntps is called a cycle T A C G is one cycle Ion Torrent workflow

71 Data analysis: Torrent Browser Ion Torrent Workflow

72 Data analysis with NGSengine Target Pooling Fragment Adapter Index Quant. Amplify Sequence Analyse

73 NGSengine analysis Align reads with IMGT/HLA Highly polymorph Phase data Determine cis trans Perform typing Determine the matching genotype(s) New allele Illumina workflow

74 Sample overview: Analyze NGSengine

75 Sample overview: Determine locus NGSengine

76 Sample overview: Aligning reads NGSengine

77 Sample overview: Phasing NGSenginer

78 Sample overview: Typing NGSenginer

79 Sample overview: Analysis finished NGSengine

80 Analyzed data: Overview NGSengine

81 Analyzed data: Gene NGSengine

82 Analyzed data: Coverage Coverage Read Depth NGSengine

83 Analyzed data: Phasing NGSengine

84 Analyzed data: Matching alleles NGSengine

85 Analyzed data: Read overview NGSengine

86 Quality Statistics: Percentage most frequent base call versus rest NGSengine

87 Quality Statistics: Percentage most frequent base call versus rest Homozygous 2 alleles ~50% Noise 87

88 Analyzed data: Genotype Ranking NGSengine

89 Analyzed ddt data:reporting ti NGSengine

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