Post on 20-May-2020
Next-Generation Sequencing applied to ancient DNA
Aurélien Ginolhac & Hákon Jónsson18th June 2013
Next Generation Sequence Analysis course, CBS, DTU
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
Why is ancient DNA interesting?
Provide access to extinct species
Not 2 species but sexual dimorphism, Bunce et al. 2003
Why is ancient DNA interesting?
Provide access to evolutionary point from the past
Rasmussen et al. 2011
Why using NGS?
800 mg, Neanderthal379 bp mtDNA, HVR-I
Rasmussen et al. 2011
600 mg, Aborigine6.4X nuclear genome
Sanger Illumina
Which protocol?
Stoneking and Krause, 2011
How ancient DNA looks like?
Ancient equid, unpublished
Read length distribution
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Ancient equid, unpublished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
DNA damage mapDamage Usage
mapDamage2.0NGS course at DTU
Hákon Jónsson and Aurélien Ginolhac
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
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
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
DNA damage mapDamage Usage
Cytosine deamination
ON N
N
NH2
N
O
POH
O
O
ON O
NH
O
ONO
NH
O
H3C
ATGCAAGTATCCGCACCCCTNTACGTTCATAGGCGTGGGGAU
DNA damage mapDamage Usage
Sequencing
Ref AATGTAGCTTACTAATATAAAGCAAGGCACTGAAAATGCCRead1 ..TGTAGCTTACTAATATAAAGCAAGGCACTGAA......Read2 ....TAGCTTACTAATATAATGCAAGGCACTGAAAA....Read3 .....AGCTTACTAATATAAAGCAAGGCACTGAAAATGC.Read4 .......UTTACTAATATAAAGCAAGGCACTGAAAATGCTRead5 ........TTACTAATATAAAGCAAGGCACTGAAAATACCRead6 ...........UTAATATAAAGCAAGGCACTGAAAATGCCRead7 ............TAATATAAAGCAAGGCACTGAAAATGCCRead8 ..................AAAGCCAGGCACTGAAAATGCCRead9 ......................UAAGGCACTGAAAATGCCRead10 .......................AAGGCACTGAAAATGCC
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
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))
DNA damage mapDamage Usage
Posterior predictive intervals
●
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● ● ● ● ● ● ● ● ● ● ● ●●
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●
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●
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●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
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’
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
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
Hands On session!
Bos et al. 2011
How different was the Yersinia pestis strain in 14thcentury?
• Small genomes• Capture, enrichment method
Hands On session!
Fetch the tutorial, open a terminal and type:
cp /home/people/ludovic/HandsOnDTUaDNA/HandsOnDTU* .
in 2h
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
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
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