Next generation sequence data and de novo assembly

For human genetics

By Jaap van der Heijden

De novo assembly

Overall idea

Overall idea

Repeats and non random sheering

scaffolding

•Multiple libraries•contigs are directed by mate pairs

-> scaffolding

4 types of assemblers

Greedy algorithms

Overlap-layout-consensus

Align-layout-consensus

Bac by Bac sequencing

Types of assemblers I

Greedy algorithms joins similar reads

easily confused by repeats

Types of assemblers II

Overlap layout consensus assembler nodes represent end of read

lines represent similarity between reads (overlap)

layout step removes redundant information

consensus step is building of genome

Types of assemblers III

Align-layout-consensus. process called comparative assembly.

The overlap stage of assembly is replaced by an alignment step.

The layout stage is also greatly simplified due to the additional constraints provided by the alignment to the reference.

Types of assemblers IV

Bac by bac sequencing genome broken in fragments

Bac’s location is determined in the lab

minimum tiling path (whole genome is covered by at least one Bac

Bac’s sequenced

Lander-Waterman equation

“rain drops” to cover a tile

8-10 fold coverage 5 contigs for 1MB

genome

Timeline 1975 Sanger sequencing

1990 First shotgun/EST assemblers overlap-layout-consensus approach

2000 Human shotgun assembly

2001 Mouse shotgun assembly

2005 454 roche available

2006 Solexa available

2007 short read assembers de Bruijn graphs

The complexity of sequence assembly

• Long reads– better identification– much slower

• Short reads– faster to align– more difficult with

repeats

• Amount of reads

• Length of reads

• Mismatches

• Algorithms can show quadratic or even exponential complexity

ABySS genomes Solexa, SOLiD Simpson, J. et al.

AMOS genomes Sanger, 454 Salzberg, S. et al.

Arachne WGA (large) genomes Sanger Batzoglou, S. et al.

CAP3, PCAP genomes Sanger Huang, X. et al.

Celera WGA Assembler / CABOG (large) genomes Sanger, 454, Solexa Myers, G. et al.; Miller G. et al.

CLC Genomics Workbench genomesSanger, 454, Solexa, SOLiD CLC bio

CodonCode Aligner BACs (,genomes?) Sanger CodonCode Corporation

Euler genomesSanger, 454 (,Solexa ?) Pevzner, P. et al.

Euler-sr genomes 454, Solexa Chaisson, MJ. et al.

MIRA, miraEST genomes, ESTs Sanger, 454, Solexa Chevreux, B.NextGENe (small genomes?) 454, Solexa, SOLiD SoftgeneticsNewbler genomes 454, Sanger 454/Roche

Phrap genomes Sanger, 454 Green, P.

TIGR Assembler genomic Sanger -

Sequencher (small) genomes Sanger Gene Codes CorporationSeqMan NGen (small) genomes Sanger, 454, Solexa DNASTAR

SHARCGS (small) genomes Solexa Dohm et al.

SSAKE (small) genomesSolexa (SOLiD? Helicos?) Warren, R. et al.

Staden gap4 package BACs (, small genomes?) Sanger Staden et al.

VCAKE (small) genomesSolexa (SOLiD?, Helicos?) Jeck, W. et al.

Phusion assembler (large) genomes Sanger Mullikin JC, et.al.Quality Value Guided SRA (QSRA) genomes Sanger, Solexa Bryant DW, et.al.

Velvet (algorithm) (small) genomesSanger, 454, Solexa, SOLiD Zerbino, D. et al.

3 NGS Projects

Dragon fly

Medical Maggots

EST comparison

Dragon Fly (libelle)

Class Odonata

3000 species 90 in Europe

Undergo a morphic change

Pilot study for African Dragon Fly

Morphic change

Some migrate others don't

Genetically divergent

Contain lots of introns in their genome

Project questions

What are the homologies with other species?

How big is the genome?

Are there already sequences in Genbank and are they present in the data?

Dragon fly project data

Genomic Single end

1 x 1147762 reads

Trimmed to 34/51 nucleotides

39.023.908 nucleotides sequenced

CDNA Paired end

2 x 1291901 reads

Read lenght = 51

131.773.902 nucleotides sequenced

Dragon fly methods

Assemble cDNA

Blast resulting contigs to determine homologies

Align genomic DNA to contigs

Calculate genome size

Dragon fly assembly results

total contigs: 3898 average length of contigs: 176

average coverage of contigs: 24

contigs larger than 300 nucleotides: 800

average length of contigs larger then 300: 508

average coverage of contigs larger then 300: 15

Dragon fly genes and homologies

libellula pulchella

Enallagma aspersum

Erythromma najas

Ischnura verticalis

many Drosophila species Criteria used for in this analysis was an e-

value of less then 1*10^-40 and a score of more than 200.

COII gene with accession number GQ256052.1 (partial)

COI gene with accession number GQ256032.1 (partial)

NDI gene with accession number GQ255994.1 (partial) found in the cDNA contigs.

Dragon fly genome size

30 genomic genes selected after blasting

Size 300-1500

Alignment with Bowtie

“calculation”

Medicinal maggots

Treated to non healing wounds

genes revealed Signaling proteins

Inhibitor of apoptosis protein 2

Digestive enzymes Lipases proteinases

antimicrobial peptides (AMPs) Lucilia defensin diptericin

Medicinal maggots data

5 degenerate peptide sequences 36 Peptides

cDNA 8.199.983 reads

read lenght 32

2.623.994.560

Medicinal maggots question

Have we sequenced (pieces) of the genes corresponding to the peptides.

Medicinal maggots methods

Build local library of peptides

Assemble contigs CLCbio

Nextgene

Velvet

Blast contigs to peptides

Find hits

Make coverage plot

Nextgene assembly maggots

aantal contigs = 59048

gemiddelde lengte = 59

gemiddelde coverage = 11

aantal contigs >300 = 719

gemiddelde lengte >300 = 661

gemiddelde coverage >300 = 64

CLC assembly

Aantal contigs = 78

gemiddelde lengte = 2282

gemiddelde coverage = 514

Velvet assembly made

total contigs: 586

length of contigs: 168

coverage of contigs: 55

contigs larger than 300 nucleotides: 62

length of contigs larger then 300: 779

coverage of contigs larger then 300: 63

Found Genes Maggots

C.vicina mRNA for arylphorin subunit A4

Velvet Drosophila willistoni GK21455 (Dwil\GK21455) mRNA

nextgene Lucilia cuprina clone sbsp9 serine proteinase mRNA

nextgene

EST comparison

Traditional EST sequencing

known library

assemblers CLCbio

Nextgene

Velvet

EST comparison method

Assemble cDNA and match with known ESTs

EST results

conclusions

Big differences between assemblers coverage

length

amount of nodes

sequence

x performs best on EST test

Questions?