10 Billion Piece Jigsaw Puzzles John Cleary Netvalue Ltd. Real Time Genomics

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Genome Transcriptome Cancer

Genomes of … human reference species mouse, chimp, arabidopsis… agricultural species cattle, sheep, pig, … rice, wheat, grape … bacterial disease, human “ecosystem”

Differences between … Individuals Populations disease and “quantitative traits” Somatic and tumor genomes Transcriptome of child and parents Bacterial populations of individuals

Human Genome 3 billion Nucleotides

Shapes of the Jigsaw Pieces CompanyLengths (nt) Illumina Complete Genomics36 Ion Torrentupto 200 Oxford Nanopore(?)upto 50,000 Pacific Biosciences100*

Differences between genomes - SNPs A C G T T A G T G A A C G T T C G T G A A C G T T G G T G A ~ 1 / 1,000 3,000,000 nt

REF: aatgttttctcagaatgtggagaaccttggtgcggacgatgcgcaat_atagggtgggtaccgtccggatac_gctgc______aat______ctgcaatgggaacgacatgatacaatcctgacgggcggtatagaggttctgttgcgtagttagtgttcgtgctgg SIM: T AAGAAT CALL: T G CALL: T T READ: ATGTTTTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GC READ: TTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA READ: TCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG READ: CTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______A READ: AATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAAT READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA-______GAATAATC READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAATC READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCA READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCA READ: TGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAAT READ: GAACCTTGGTGCGGACGATGCGCAATTATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAAT READ: AACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGG READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAA READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAA READ: TGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACA READ: TGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAAT READ: GCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATC READ: CAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTG READ: _ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGG READ: TAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGG READ: GGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCG READ: TGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTA READ: GGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTAT READ: GTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAG READ: TACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGA READ: CGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGT READ: TTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTT READ: CGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTG READ: TGCAAGAAT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGT READ: AC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCG READ: AT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTT READ: ______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTTCG

Differences between human genomes - MNPs A C G T T A G T G A A C G T T C A G A A C G T T G T G A

Differences between human genomes - indels A C G T T A G T G A A C G T T G T G A A C G T T G G T G A ~ 1 / 10, ,000

Differences between genomes - inserts A C G T T A G T G A Up to 1,000,000 nt total 3,000,000 nt T T A G G A C C C A

Differences between genomes – structural variants Tandem Repeat Inversion Copy

Solving the Jigsaw Indexing Alignment SNP/MNP/Indel/SV calling Mapping

Indexing A C G T T A G T G A A G A C G T T C G T G A A G A C G T T C G T G A A G A C G T T A G T G A A G 4.5 billion

Aligning A C G T T A G T G A A G A C G T T C G T G A A G 1.6 billion

Cutting Edge Run Human genome (3 billion nt) 1 billion reads of 100 nt coverage of 30 Indexing + Aligning in 27 minutes

i7 Quad Core

2 sockets X 4 cores X 2 hyperthreads = GB RAM 10 computers 1 TB disk/genome = 500GB + 200GB + 200GB + 0.3GB X thousands of genomes

Shapes of the Jigsaw Pieces CompanyLengths (nt) Illumina Complete Genomics36 Ion Torrentupto 200 Oxford Nanopore(?)upto 50,000 Pacific Biosciences100*

Paired End Reads 100 nt ,000 nt Index Align Index Align Match 100 nt

Solving the Jigsaw without the picture Indexing Alignment Assembly

T A G T G A A G A A T T A C G T T C G T G A A G A C G T T C G T G A A G T A G T G A A G A A T T A C G T T ? G T G A A G A A T T

SNP calling 15A13CAC heterozygous SNP 15A4C 5A2C 1A2C Bayesian statistics (SNPs 1/1,000) 31A42C Throw it out

REF: aatgttttctcagaatgtggagaaccttggtgcggacgatgcgcaat_atagggtgggtaccgtccggatac_gctgc______aat______ctgcaatgggaacgacatgatacaatcctgacgggcggtatagaggttctgttgcgtagttagtgttcgtgctgg SIM: T AAGAAT CALL: T G CALL: T T READ: ATGTTTTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GC READ: TTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA READ: TCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG READ: CTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______A READ: AATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAAT READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA-______GAATAATC READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAATC READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCA READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCA READ: TGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAAT READ: GAACCTTGGTGCGGACGATGCGCAATTATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAAT READ: AACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGG READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAA READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAA READ: TGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACA READ: TGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAAT READ: GCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATC READ: CAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTG READ: _ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGG READ: TAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGG READ: GGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCG READ: TGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTA READ: GGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTAT READ: GTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAG READ: TACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGA READ: CGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGT READ: TTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTT READ: CGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTG READ: TGCAAGAAT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGT READ: AC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCG READ: AT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTT READ: ______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTTCG

Comparing twins 3,000,000 SNPs Do any of them differ between the twins? 15A 4C 3A 10C 3G

DNA mRNA protein Gene

Cancer comparison

Copy Number Variants Varying levels of extraction of reads across genome (use differences) Locate boundaries (as accurately as possible) Extract number of variants Use SNPs

Metagenomics or what is living on you Mapping reads back onto a database of known bacteria/viruses Many are ambiguous Many don’t map at all Estimate frequency of each species Remove human “contamination”

TS gi| |ref|NC_ | Bacteroides thetaiotaomicron VPI-5482 plasmid p gi| |ref|NC_ | Akkermansia muciniphila ATCC BAA gi| |ref|NC_ | Bacteroides vulgatus ATCC gi| |ref|NC_ | Bifidobacterium adolescentis ATCC TS gi| |ref|NC_ | Bacteroides thetaiotaomicron VPI-5482 plasmid p gi| |ref|NC_ | Bacteroides vulgatus ATCC gi| |ref|NC_ |Bacteroides fragilis NCTC 9343 plasmid pBF gi| |ref|NC_ |Campylobacter jejuni subsp. jejuni plasmid pTet gi| |ref|NC_ |Eubacterium rectale ATCC TS gi| |ref|NC_ | Bacteroides thetaiotaomicron VPI-5482 plasmid p gi| |ref|NC_ | Bacteroides vulgatus ATCC gi| |ref|NC_ |Campylobacter jejuni subsp. jejuni plasmid pTet gi| |ref|NC_ |Bifidobacterium longum NCC gi| |ref|NC_ |Bifidobacterium longum DJO10A

Metagenomics Map reads to database Estimate most likely frequencies a hill climbing estimation problem Can anything be done about unmapped reads?