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Barbera van Schaik Bioinformatics Laboratory, AMC

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Presentation on theme: "Barbera van Schaik Bioinformatics Laboratory, AMC"— Presentation transcript:

1 Barbera van Schaik Bioinformatics Laboratory, AMC

2 Current sequencing projects Neurogenetics laboratory Somatic mutation detection (Frank Baas, Marja Jakobs) Laboratory of Experimental Virology Virus discovery (Michel de Vries) Dept. Clinical Immunology & Rheumatology TCR-beta variant detection (Niek de Vries, Paul Klarenbeek) Clinical Virology Hepatitis C (Richard Molenkamp) Erasmus MC – Rotterdam Re-sequencing tumor samples (Ernie de Boer, Michael Moorhouse)

3 TCR-beta

4 Recombinatie van gensegmenten : Vanuit de germline: - Van ieder gensegment wordt 1 variant geselecteerd -Deze worden aan elkaar gekoppeld Alleen functionele recombinaties leiden tot functionele T-cellen Paul Klarenbeek

5 Totale theoretische variatie (in vivo blijkt dit veel lager te liggen) Paul Klarenbeek

6 CDR3 region Unique for each clonal expansion How to identify clonal expansions? Germline DNA mRNA Thymocytes Paul Klarenbeek

7 Dept. Clinical Immunology & Rheumatology Goal: identify and enumerate TCR-beta variants VnCDR3JPrimer A J C Primer B Barcode VnCDR3JPrimer A C C Primer B Barcode Paul Klarenbeek

8 Roche (454) sequencing Run ,509 sequences 26,445,844 nucleotides in total Run ,234 sequences 24,983,646 nt

9 Sequence lengths

10 Pipeline Rheumatology Convert sff to fasta+quality scores Chop sequences into: MID, fragment Divide sequences based on MID and region Identify the V, J and C segments Locate highly variable area Count variants Quality control Perl scripts Roche software BLAT Access/Excel

11 Recognize MID and primer MID = barcode for sample Primer = Primer for J or C segment # MIDs for the 3 regions that are sequenced with primer for J segment: MID=(TAGT|ACTA|CGAC|CTCG) # Primer for J segment (first) or C segment (last two): Primer=(CTTACCTACAACGGTTAACCTGGTC|AGCTCAAACACAGCGACCTC|G GAACACCTTGTTCAGGTC)

12 Pipeline Rheumatology Convert sff to fasta+quality scores Chop sequences into: MID, fragment Divide sequences based on MID and region Identify the V, J and C segments Locate highly variable area Count variants Quality control Perl scripts Roche software BLAT Access/Excel

13 Identify V, J and segment IMGT website: reference sequences BLAT all roche sequences against 3 references Selection: only store first hit per reference MID C J CDR3 V MID J CDR3 V

14 Locate highly variable region (CDR3) Get CDR3 sequence -> count Determine deletions from V and J segment Determine reading frame MID C J CDR3 V MID J CDR3 V

15 Pipeline Rheumatology Convert sff to fasta+quality scores Chop sequences into: MID, fragment Divide sequences based on MID and region Identify the V, J and C segments Locate highly variable area Count variants Quality control Perl scripts Roche software BLAT Access/Excel

16 Count variants: BLAT hits

17 Count CDR3 variants regioncdr3_sequencefreq CTCCCTTTTTGGGGG32 1CCCTCAGGATTTCAGGG30 1TGGGTC29 1CAAACATGA23 1GGGACGGAGA20 1GGACAGT20 1CCCAGACAGG19 1AACCGGA18 1CTCCACTGGACACGT18 1ACGGG18 1CGCCCGGGACAGGGCCCTTCGGGG18 1CCACCCCGCGGCAGGAGGG17 1CCCACCGGGACAGGGGCGTC17 1GGTATACGGGCAGCGG16 1GACCTTGTGGTC16 1ACAGGGGGAG16 1GCGGG16 Example of CDR3 sequences

18 Count deleted nt of V and J segment Check where alignment stops wrt reference

19 Pipeline Rheumatology Convert sff to fasta+quality scores Chop sequences into: MID, fragment Divide sequences based on MID and region Identify the V, J and C segments Locate highly variable area Count variants Quality control Perl scripts Roche software BLAT Access/Excel

20 To do next Determine reading frame Quality control Future plans Detection of all TCR-beta variants TCR-alpha receptor variants Same procedure for B-cells Screen patients for receptor variations

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