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Next-Generation Sequencing applied to ancient DNA
Aurélien Ginolhac & Hákon Jónsson18th June 2013
Next Generation Sequence Analysis course, CBS, DTU
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What is ancient DNA?
Museum samples Bones
DNA extracted from fossils, remains of every nature
Coprolites Hairs
Extinct species
Actual species, mainly human
Plague, Y. pestisaborigineOtzï
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Why is ancient DNA interesting?
Provide access to extinct species
Not 2 species but sexual dimorphism, Bunce et al. 2003
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Why is ancient DNA interesting?
Provide access to evolutionary point from the past
Rasmussen et al. 2011
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Why using NGS?
800 mg, Neanderthal379 bp mtDNA, HVR-I
Rasmussen et al. 2011
600 mg, Aborigine6.4X nuclear genome
Sanger Illumina
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Which protocol?
Stoneking and Krause, 2011
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How ancient DNA looks like?
Ancient equid, unpublished
Read length distribution
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How ancient DNA looks like?
H. Jónsson et al, mapDamage 2013
Ancient equid, unpublished
5’-ends C>T G>A 3’-ends
READ
READ
REF REF
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DNA damage mapDamage Usage
mapDamage2.0NGS course at DTU
Hákon Jónsson and Aurélien Ginolhac
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DNA damage mapDamage Usage
DNA
ON N
N
NH2
N
O
POH
O
O
ON O
N
NH2
O
POH
O
O
ON N NH2
NH
O
N
ONO
N
NH2
O
P OH
O
O
ONNNH2
NH
O
N
O
P OH
O
O
ONO
NH
O
H3C
ATGCAAGTATCCGCACCCCTGCATGCAAGTATCCGCACCCTACGTTCATAGGCGTGGGGACGTACGTTCATAGGCGTGGG
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DNA damage mapDamage Usage
DNA depurination
ON N
N
NH2
N
O
POH
O
O
ON O
N
NH2
O
POH
O
O
O
ONO
N
NH2
O
P OH
O
O
O
O
P OH
O
O
ONO
NH
O
H3C
ATGCAAGTATCCGCACCCCTNCATGCAAGTATCCGCACCCTACGTTCATAGGCGTGGGGACNTACGTTCATAGGCGTGGG
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DNA damage mapDamage Usage
Hydrolysis of the backbone
ON N
N
NH2
N
O
POH
O
O
ON O
N
NH2
ONO
NH
O
H3C
ATGCAAGTATCCGCACCCCTNTACGTTCATAGGCGTGGGGAC
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DNA damage mapDamage Usage
Cytosine deamination
ON N
N
NH2
N
O
POH
O
O
ON O
NH
O
ONO
NH
O
H3C
ATGCAAGTATCCGCACCCCTNTACGTTCATAGGCGTGGGGAU
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DNA damage mapDamage Usage
Sequencing
Ref AATGTAGCTTACTAATATAAAGCAAGGCACTGAAAATGCCRead1 ..TGTAGCTTACTAATATAAAGCAAGGCACTGAA......Read2 ....TAGCTTACTAATATAATGCAAGGCACTGAAAA....Read3 .....AGCTTACTAATATAAAGCAAGGCACTGAAAATGC.Read4 .......UTTACTAATATAAAGCAAGGCACTGAAAATGCTRead5 ........TTACTAATATAAAGCAAGGCACTGAAAATACCRead6 ...........UTAATATAAAGCAAGGCACTGAAAATGCCRead7 ............TAATATAAAGCAAGGCACTGAAAATGCCRead8 ..................AAAGCCAGGCACTGAAAATGCCRead9 ......................UAAGGCACTGAAAATGCCRead10 .......................AAGGCACTGAAAATGCC
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DNA damage mapDamage Usage
mapDamageplot
A
●● ● ● ● ● ●
● ●
●
●
● ● ●● ● ● ●
● ●
0.0
0.1
0.2
0.3
0.4
0.5
Fre
quen
cy
A
●
●
●
●
●●
●●
●
●●
●
●●
● ●●
● ● ●
C
● ● ●● ●
●●
●●
● ●● ●
●● ● ●
●● ●
C
● ●● ●
●●
● ●●
●
●
●● ●
●
● ●●
● ●
0.0
0.1
0.2
0.3
0.4
0.5
G
●● ● ●
● ●● ● ●
●
●
● ●●
● ● ●●
● ●
0.0
0.1
0.2
0.3
0.4
0.5
Fre
quen
cy
−10 −
9−
8−
7−
6−
5−
4−
3−
2−
1 1 2 3 4 5 6 7 8 9 10
G
●
●
●
●● ●
●
●●
● ●
●
●
● ●● ●
●● ●
−10 −
9−
8−
7−
6−
5−
4−
3−
2−
1 1 2 3 4 5 6 7 8 9 10
T
●●
●●
●● ● ●
●
●
●
● ● ●● ● ●
●●
●
−10 −
9−
8−
7−
6−
5−
4−
3−
2−
1 1 2 3 4 5 6 7 8 9 10
T
● ● ●●
●
●●
●
●
●
●
● ●
●
●
● ●● ● ●
0.0
0.1
0.2
0.3
0.4
0.5
−10 −
9−
8−
7−
6−
5−
4−
3−
2−
1 1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
0.00
0.05
0.10
0.15
0.20
0.25
0.30−
25−
24−
23−
22−
21−
20−
19−
18−
17−
16−
15−
14−
13−
12−
11−
10 −9
−8
−7
−6
−5
−4
−3
−2
−1
0.00
0.05
0.10
0.15
0.20
0.25
0.30
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DNA damage mapDamage Usage
mapDamage2.0
Cstart
C to T
Single s.
Double s.
Tend
Cend
νi
1− νi
λi
1− λi
δs
1− δs
δd
1− δd
U C T A A T C T A C G G G A C C
A T T A G A T G C C C T G G T
Overhang Nick
5’
3’
3’
5’
SC ,k ∼ Mul (DA , (1, 0, 0, 0) ·Θ(µ) · Pdam(δd , δs , λ, ν, k))
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DNA damage mapDamage Usage
Posterior predictive intervals
●
●
●
●
●
●
●●
●●
●●
● ● ● ● ● ● ● ● ● ● ● ●●
● ● ● ● ● ● ● ● ● ● ●
● ● ●●
●
●
●
●
●
●
●
●
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●0.00
0.05
0.10
0.15
0.20
0.25
1 3 5 7 9 11 −11 −9 −7 −5 −3 −1Relative position
Sub
stitu
tion
rate
Subs. type
●●●
●●●
●●●
C−>T
G−>A
Others
Posterior prediction intervals
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DNA damage mapDamage Usage
Posterior distributions for parameters
Theta
Den
sity
0.0005 0.0010 0.0015
050
015
00
Rho
Den
sity
0 1 2 3 4 5 6
0.0
0.2
0.4
0.6
0.8
DeltaD
Den
sity
0.015 0.020 0.025 0.030
050
100
150
DeltaS
Den
sity
0.5 0.6 0.7 0.8
02
46
8
Lambda
Den
sity
0.30 0.35 0.40 0.45
05
1015
LogLik
Den
sity
−295 −290 −285
0.00
0.10
0.20
Cstart
C to T
Single s.
Double s.
Tend
Cend
νi
1− νi
λi
1− λi
δs
1− δs
δd
1− δd
U C T A A T C T A C G G G A C C
A T T A G A T G C C C T G G T
Overhang Nick
5’
3’
3’
5’
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DNA damage mapDamage Usage
mapDamage −i seq . bam −r ref . fa
You should see something like this
Started with the command : mapDamage −i seq . bam −r ref . faPerforming Bayesian estimatesStarting grid search , starting from random valuesAdjusting the proposal variance iteration 1..Adjusting the proposal variance iteration 10Done burning , starting the iterationsDone with the iterations , finishing upWriting and plotting to files
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DNA damage mapDamage Usage
Go into the results folder
cd results
Take a look at these files
Fragmisincorporation_plot . pdfLength_plot . pdfStats_out_MCMC_hist . pdfStats_out_MCMC_post_pred . pdfStats_out_MCMC_trace . pdfStats_out_MCMC_iter_summ_stat . csv
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Hands On session!
Bos et al. 2011
How different was the Yersinia pestis strain in 14thcentury?
• Small genomes• Capture, enrichment method
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Hands On session!
Fetch the tutorial, open a terminal and type:
cp /home/people/ludovic/HandsOnDTUaDNA/HandsOnDTU* .
in 2h
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Acknowledgments
Ludovic Orlando & the paleomix group
http://geogenetics.ku.dk/
Stinus Lindgreen, Mikkel Schubert, Anders KroghBiocentre, København University
Bent Petersen, Josef Vogt, Thomas Sicheritz-PontenCBS, Technical University of Denmark
Danish High-Troughput Sequencing Centre
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Acknowledgments
Ludovic Orlando & the paleomix group
http://geogenetics.ku.dk/
Stinus Lindgreen, Mikkel Schubert, Anders KroghBiocentre, København University
Bent Petersen, Josef Vogt, Thomas Sicheritz-PontenCBS, Technical University of Denmark
Danish High-Troughput Sequencing Centre
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Illumina – workflow
6
FASTQ files
@HWUSI-EAS1510_0024_FC:7:1:1563:932#0NAGGACAGGGAAGCCGAAGATACCATTTGTGTTCTTCCCAAACTTTATTACTTTTGTAGCAAAAAGAAAA+HWUSI-EAS1510_0024_FC:7:1:1563:932#0BKJKMRRQRQ[[[[[[[[[[______b_________________bbZ_QQ______QQ__BBBBBBBBBB@HWUSI-EAS1510_0024_FC:7:1:1574:952#0NATCATCGCGGGGGTCGGCAGCTTCGACACCGCGCACACGATCCACTCGGCGAAGGGTGCTGCCGCGTTG+HWUSI-EAS1510_0024_FC:7:1:1574:952#0BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB@HWUSI-EAS1510_0024_FC:7:1:1656:932#0ATGATTAGTGCATCAGCCCTTTGAAAAGTGGCCTACAGACATTGTCCTTAGCTAACAACCACAGATCGGA+HWUSI-EAS1510_0024_FC:7:1:1656:932#0JJKJJQQQQN__bbb_____bb________b___b__bb__b_____b___b_b___b____b__RSQRPfastQC
Quality scores Kmers GC content