Supplemental Material
Direct multiplex sequencing (DMPS) – a novel method
for targeted high-throughput sequencing of ancient and
highly degraded DNA
Mathias Stiller1, Michael Knapp1, Udo Stenzel1, Michael Hofreiter1,2, Matthias Meyer1
1
Departement of Evolutionary Genetics, Max Planck Institute for Evolutionary
Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
2
Department of Biology, University of York, YO10 5YW, York, UK
Table S1. Initial sequencing results for 56 cave bear samples. 31 samples were chosen
for mitochondrial genome sequencing (shown in bold).
barcode
sample
number
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
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
SP233
SP335
SP341
SP350
SP370
SP1843
SP1844
SP1845
SP1846
SP1847
SP1850
SP232
SP234
SP627
SP636
SP1994
SP2019
SP2024
SP2027
SP2021
SP1659
SP2060
SP2062
SP2064
SP2065
SP2070
SP2073
SP2074
SP2106
SP2080
SP2081
SP2083
SP2085
SP2091
SP1324
SP1325
SP1330
SP1333
SP1334
SP1322
SP1323
SP1326
# of reads
Odd
496
280
312
246
266
289
257
241
304
205
239
177
412
233
274
281
253
190
313
198
314
160
235
197
463
244
318
289
203
90
126
217
614
191
167
164
82
104
82
87
185
230
Even
175
311
352
232
193
528
573
192
106
90
141
342
501
578
402
426
85
114
161
61
98
78
83
58
236
231
248
115
146
110
106
60
382
391
333
235
283
284
207
208
239
280
# of reads aligned to
cave bear mt-genome
Odd
428
269
290
196
211
186
213
201
121
174
162
139
271
140
103
117
137
87
297
11
160
31
222
141
438
133
253
217
154
36
95
209
589
163
94
122
73
25
66
11
32
118
Even
152
302
330
77
81
57
238
137
30
49
86
170
264
197
51
103
8
33
157
4
41
9
76
34
223
78
185
75
105
11
64
60
372
283
156
139
230
62
134
38
27
79
% of reads aligned to
cave bear mt-genome
Odd
86
96
93
80
79
64
83
83
40
85
68
79
66
60
38
42
54
46
95
6
51
19
94
72
95
55
80
75
76
40
75
96
96
85
56
74
89
24
80
13
17
51
Even
87
97
94
33
42
11
42
71
28
54
61
50
53
34
13
24
9
29
98
7
42
12
92
59
94
34
75
65
72
10
60
100
97
72
47
59
81
22
65
18
11
28
43
44
45
46
47
48
49
50
51
52
53
54
55
56
SP1327
SP2125
SP2128
SP2129
SP2133
SP2134
SP1617
SP1622
SP1623
SP1624
SP1625
SP1626
SP1629
SP1497
177
276
185
135
187
85
286
238
110
193
184
229
178
250
274
220
217
177
188
168
351
158
244
130
152
178
120
245
69
260
9
57
159
5
113
16
38
59
107
167
106
222
75
213
2
79
110
4
84
13
22
20
55
90
50
203
39
94
5
42
85
6
40
7
35
31
58
73
60
89
27
97
1
45
59
2
24
8
9
15
36
51
42
83
Table S2. Sample numbers and geographical locations of the 31 samples selected for
mitochondrial genome sequencing. Sequences from two pre-existing mitochondrial
genomes, EU327344 (Bon et al. 2008) and NC_011112 (Krause et al. 2008), were taken
from GenBank.
sample
number
SP2091
Eiros, E-T-3013
Spain (Sp)
number
on map
1
SP2083
A Ceza, CEZ-1-2
Spain (Sp)
2
SP2085
A Ceza, CEZ-1-4
Spain (Sp)
2
SP2081
Cova Linares, LIN-1011
Spain (Sp)
3
EU327344
Chauvet
France (Fr)
4
SP1659
Arcy Cure, 4
France (Fr)
5
SP2129
Grotte d'ours, GO 3
France (Fr)
6
SP2027
Geissenkloesterle, TUB-55
Germany (Ger)
7
SP2106
Geissenkloesterle, 78 q69 #183 -228
Germany (Ger)
7
SP1497
Herrmannscave
Germany (Ger)
8
SP1324
Zoolithencave, GL 77-21
Germany (Ger)
9
SP1325
Zoolithencave, GL 77-25
Germany (Ger)
9
SP1330
Zoolithencave, BK 210
Germany (Ger)
9
SP1334
Zoolithencave, Sch-1239
Germany (Ger)
9
SP232
Nixloch, 117 K/J 14
Austria (Au)
10
SP2133
Schneibercave, Schn. 3
Germany (Ger)
11
SP335
Gamssulzen, 3-1
Austria (Au)
12
SP341
Gamssulzen, 3-7
Austria (Au)
12
NC_011112
Gamssulzen
Austria (Au)
12
SP370
Herdengel cave
Austria (Au)
13
SP1844
Divje babe 1, D.b.1993, Kv.54, lz.7, Plasti 2-5
Slovenia (Slo)
14
SP1845
Divje babe 1, D.b.1994, Kv.32, lz.15, Plast 6-7
Slovenia (Slo)
14
SP1850
Divje babe 1, Kv.183, lz.13, Plast 13
Slovenia (Slo)
14
SP233
Potocka zijalka, Grabung II, nr. 404
Slovenia (Slo)
15
SP234
Potocka zijalka, Grabung II, Q5, P2, 189
Slovenia (Slo)
15
SP2125
Medvedia jaskyna, Mj 1
Slovakia (Slv)
16
SP1626
Pestera cu Oase, 9
Romania (Ro)
17
SP1629
Pestera cu Oase, 11
Romania (Ro)
17
SP2073
Hovk 1, 2007, 104/109, layers 4/4
Armenia (Arm)
18
SP2074
Hovk 1, 22-06-2007, 103/107, unit 6
Armenia (Arm)
18
SP2065
Medvezhyia cave, ZIN 34756-10
Russia (Ru)
19
SP2064
Serpievskaya cave, ZIN 34991-6
Russia (Ru)
20
SP2062
Bolshoi Glukhoi grotto, ZIN 34677-9
Russia (Ru)
21
geographical location & sample ID
country
Fig. S1. Geographical locations from the 31 samples selected for mitochondrial genome
sequencing and the two samples sequenced previously.
Fig. S2. Sequence representation among the barcoded cave bear samples, obtained from
the two libraries produced for the first round of amplification and sequencing. For each
sample odd and even multiplex PCR products cannot be distinguished, since the same
barcodes were used.
1st library - 272,303 barcoded reads (98.1% of total reads)
number of sequences
30,000
25,000
20,000
15,000
10,000
5,000
0
1 2 3 5
7 8 11 12 13 19 21 23 24 25 27 28 29 31 32 33 34 35 36 37 39 44 46 47 54 55 56
barcode
2nd library - 306,142 barcoded reads (97.6% of total reads)
number of sequences
30,000
25,000
20,000
15,000
10,000
5,000
0
1 2 3 5
7 8 11 12 13 19 21 23 24 25 27 28 29 31 32 33 34 35 36 37 39 44 46 47 54 55 56
barcode
Supplemental Methods
1. Screening of cave bear DNA extracts for the presence of a 175 bp target.
DNA was extracted from 125 to 800 mg of fossil bones or teeth from 110 cave bear
specimens as described previously (Rohland and Hofreiter 2007). Using a singleplex
PCR assay with the primers “2620” (5´-GCCCCATGCATATAAGCATG-3´) and “2558”
(5´-GGAGCGAGAGGTACACGT-3´), all extracts were screened for the presence of a
175 bp mitochondrial target in a 1:10 dilution. Dilutions were used to avoid stochastic
effects, because sporadic amplification success may occur even if the target is not
consistently present in every unit of undiluted extract.
In final volumes of 25 µl the reactions contained 5 µl of diluted extract, 2 U AmpliTaq
Gold DNA polymerase (Applied Biosystems) and in final concentrations 1x AmpliTaq
Gold buffer, 2.5 mM MgCl2, 250 µM each dNTP, 250 nM each primer, and 0.8 mg/ml
BSA (Sigma). Cycling was performed on a MJ Thermo Cycler with a 12-min activation
step at 95°C, followed by 60 cycles at 94°C for 30 s, 50°C for 40 s, and 72°C for 40 s
with a final extension step of 72°C for 5 min.
2. Multiplex PCRs
Multiplex PCRs were performed in 20 µl reactions on 96-well plates, using 5 µl of
undiluted cave bear extracts, 0.5 µl mammoth extract and 5 ng genomic DNA from polar
bear and African elephant as template. Polar bear blood and African elephant DNA were
kindly provided by the Leipzig Zoo and Alfred Roca. DNA was isolated from blood
using the DNeasy Blood & Tissue kit (Qiagen). Multiplex PCRs contained 2 U AmpliTaq
Gold DNA polymerase, 1x AmpliTaq Gold buffer, 2.5 mM MgCl2, 250 µM of each
dNTP, 150 nM of each primer and 0.8 mg / ml BSA. Cycling conditions were comprised
of an activation step lasting 12 min at 95°C, followed by 12, 15, 18, 20 or 25 cycles of
denaturation at 94°C for 30 s, annealing at 53 °C for 30 s and elongation at 72°C for 30 s,
with a final extension step at 72°C for 10 min.
3. Size selection
To remove primer dimers and other spurious amplification products, the multiplex PCR
products were purified using the AMPure PCR purification system (Agencourt), which
can be used in 96-well plate setup and provides a relatively sharp size cutoff. Since we
previously experienced significant batch-to-batch variation in the size cutoff, we pooled
several batches and tested the size cutoff with a GeneRuler 50 bp DNA Ladder
(Fermentas). Using a 1.8-fold ratio of SPRI beads to the reaction volume, we found a size
cutoff of approximately 100 bp, which we retained throughout all subsequent SPRI
purification steps. The purification reactions were performed as described elsewhere
(Meyer et al. 2008b) with two alterations; Tween-20 was added to the SPRI beads to a
final concentration of 0.05 % and the DNA was eluted in 15 µl TT buffer (10 mM TrisHCl pH 8.0, 0.05 % Tween-20).
4. Preparation and amplification of bar-coded sequencing libraries
Following SPRI purification, the ends of all molecules were blunt end repaired in 30 µl
reactions containing in final concentrations 1x buffer Tango, 1mM ATP, 0.5 U / µl T4
polynucleotide kinase, 0.1 U / µl T4 DNA polymerase (all Fermentas) and 100 µM of
each dNTP. After incubation for 5 min at 12°C and 5 min at 25°C, the reactions were
purified using SPRI beads. The DNA was eluted in 15 µl TT buffer.
Seventy double-stranded barcoding adapters (truncated 454 adapters carrying a 7 bp
barcode sequence) were prepared in separates tubes, each containing 6 µl 10x T4 ligase
buffer (Fermentas), 6 µl water, 24 µl adapter oligo (500 µM) and 24 µl short
complementary adapter oligo (500 µM). The tubes were heated to 95 °C for 1 min in a
thermal cycler and cooled to 20 °C at a rate of 0.1 °C / s.
Adapters were ligated to the blunt end repaired DNA in 30 µl reactions, containing 1x T4
ligase buffer, 5% PEG-4000, 5 U T4 ligase (all Fermentas) and 0.5 µl of each barcoding
adapter. To avoid self-ligation of template DNA, the barcoding adapters were mixed with
the template DNA before adding a master mix with the remaining reagents. After
incubation at 22°C for 20 min, the reactions were purified twice using SPRI beads to
fully remove excess adapters. The DNA was eluted in 15 µl TT buffer after both
purification steps. Repeated purification was necessary to suppress adapter dimer
formation, which occurs in the subsequent fill-in step, to an extremely low level. If this
barcoding protocol is used with larger amounts of input DNA (> 50 ng), a single
purification step is sufficient. In this case it may also be advantageous to use more
adapters (2 µl) to avoid chimera formation.
Following SPRI purification, fill-in reaction were carried out in 30 µl volumes,
containing 1x Thermopol buffer, 8 U Bst polymerase, large fragment (both NEB) and
250 µM of each dNTP. After incubation for 20 min at 37 °C, the reactions were purified
using SPRI beads. The DNA was eluted in 25 µl EB buffer (10 mM Tris, pH 8.0).
To produce sequencing libraries with full-length universal 454 adapter sequences, 10 µl
of each eluate were used as template in a 20 µl amplification reactions containing 1.25 U
AmpliTaq Gold DNA polymerase, 1x AmpliTaq Gold buffer, 2.0 mM MgCl2, 250 µM of
each dNTP, and 250 nM of primers (MP-make454-A and MP-make454-B). Cycling
conditions were comprised of an activation step lasting 12 min at 95°C, followed by 15
cycles of at 94°C for 30 s, annealing at 60 °C for 30 s and 72°C for 40 s, with a final
extension step at 72°C for 5 min. All PCRs were purified using SPRI beads. The DNA
was eluted in 20 µl TET buffer (10 mM Tris pH 8.0, 1 mM EDTA, 0.05 % Tween-20).
The copy number in each library was determined by quantitative PCR following the exact
methodology described previously (Meyer et al. 2008a), but using the HS SYBR® Green
qPCR Kit (NEB) according to the manufacturer’s instructions and TET buffer to store the
qPCR standard.
Following quantification, the double-stranded libraries were pooled in equimolar ratios
and submitted to the standard 454 sequencing procedure.
5. Data analysis and consensus calling
Sequence reads were sorted into separate files according to their barcode using the
program “untag”. Using perl scripts the following steps were performed to extract
consensus sequences from the data. (i) A reference target sequence for each primer pair
was created, representing only the sequence between the priming sites. All reads were
mapped against all targets using the software runMapper. (ii) Parts of the sequence reads
extending beyond the reference sequence were trimmed, thereby removing priming sites
from the sequence reads. (iii) Using MUSCLE (Edgar 2004), multiple sequence
alignments were constructed for all reads from each target, replicate and sample. (iv)
Consensus sequences were called from each alignment according to the following
criteria. Gaps were called if half or more of the sequences at a position contained a gap.
Not taking gaps further into account, unambiguous base calls were made, if 80 % or more
of the sequence reads supported the same base. In all other cases ambiguous bases (e.g.
Y, R, N etc.) were called to represent all sequence reads at the given position. (v)
Assisted by the complete reference sequence, multiple sequence alignments were created
for each sample, containing the consensus sequences from each target and replicate. (vi)
A final superconsensus sequence was called for each sample, considering only positions
that were covered by two replicates (or more, as four replicates were available in the
overlapping regions of the targets). Gaps were called according to the majority rule as
stated above. If the consensus sequence of one replicate contained an ambiguous base
(e.g. R), we required the position to be unambiguously resolved in the other replicate in
order to call a final consensus base (e.g. RG => G; RA => A). Consistent differences
between replicates were called N (three observations). The following exceptions were
made to account for uracil-derived ancient DNA damage (deamination of C to U leads to
C=>T and G=>A substitutions). First, consistent C/T and G/A changes were called C and
G, respectively. Second, Y/Y and R/R were called C and G, respectively.
Annotations for the cave bear mitochondrial genomes were transferred from the reference
sequence in the database (NC_011112). Single base pair insertions and deletions around
homopolymer stretches, which are typical for 454 sequencing, were manually corrected
in the protein coding regions to retain open reading frames (40 insertions, 1 deletion at 27
different positions). Single base pair insertions / deletions outside these regions were not
removed from the consensus sequences (11 positions).
6. Phylogenetic reconstructions
To test the stability of phylogenetic reconstructions under different tree-building
approaches, we performed analyses under the distance and maximum likelihood (ML)
optimality criteria. As search algorithms we used neighbor-joining (NJ) for the distance
criterion and a heuristc search for ML. Furthermore we used a Markov chain Monte
Carlo (MCMC) - based Bayesian approach. The best-fitting nucleotide substitution model
was determined with ModelTest 3.7 (Posada and Crandall 1998). Both the hierarchical
likelihood ratio test (hLRT) and the Akaike information criterion (AIC) supported
GTR+I+Γ as the best-fitting model. Therefore all analyses used GTR+I+Γ as the
substitution model.
Phylogenetic trees were reconstructed with paup version 4.0b10 (Wilgenbusch and
Swofford 2003) using NJ and ML. The paup-ML tree was reconstructed using the NJ tree
as the starting tree, followed by tree-bisection-and-reconnection (TBR) optimization
using the parameters from the above ModelTest analyses. For both analyses, bootstrap
analyses were performed with paup using the same settings as before, but using 1,000
pseudosamples summarized with a 50%-majority-rule consensus (M50). A Bayesian
analysis was run as implemented in MrBayes 3.1.2(Ronquist and Huelsenbeck 2003).
Two independent runs were performed with one cold and three hot MCMC chains each.
The chains were run for 10 million generations sampling every 100th generation after
discarding the first 2.5 million generations as burn-in. The results were checked for
convergence using Tracer 1.4 (http://tree.bio.ed.ac.uk/software/tracer/).
References
Bon, C., Caudy, N., de Dieuleveult, M., Fosse, P., Philippe, M., Maksud, F., BeraudColomb, E., Bouzaid, E., Kefi, R., Laugier, C., Rousseau, B., Casane, D., van der
Plicht, J. and Elalouf, J.M. 2008. Deciphering the complete mitochondrial genome
and phylogeny of the extinct cave bear in the Paleolithic painted cave of Chauvet.
Proc Natl Acad Sci USA 105: 17447-17452.
Edgar, R.C. 2004. MUSCLE: multiple sequence alignment with high accuracy and high
throughput. Nucleic Acids Res 32: 1792-1797.
Krause, J., Unger, T., Nocon, A., Malaspinas, A.S., Kolokotronis, S.O., Stiller, M.,
Soibelzon, L., Spriggs, H., Dear, P.H., Briggs, A.W., Bray, S.C., O'Brien, S.J.,
Rabeder, G., Matheus, P., Cooper, A., Slatkin, M., Paabo, S. and Hofreiter, M.
2008. Mitochondrial genomes reveal an explosive radiation of extinct and extant
bears near the Miocene-Pliocene boundary. BMC Evol Biol 8: 220
Meyer, M., A.W. Briggs, T. Maricic, B. Hober, B. Hoffner, J. Krause, A. Weihmann, S.
Paabo, and M. Hofreiter. 2008a. From micrograms to picograms: quantitative
PCR reduces the material demands of high-throughput sequencing. Nucleic Acids
Res 36: e5.
Meyer, M., U. Stenzel, and M. Hofreiter. 2008b. Parallel tagged sequencing on the 454
platform. Nat Protoc 3: 267-278.
Posada, D. and K.A. Crandall. 1998. MODELTEST: testing the model of DNA
substitution. Bioinformatics 14: 817-818.
Rohland, N. and M. Hofreiter. 2007. Ancient DNA extraction from bones and teeth. Nat
Protoc 2: 1756-1762.
Ronquist, F. and J.P. Huelsenbeck. 2003. MrBayes 3: Bayesian phylogenetic inference
under mixed models. Bioinformatics 19: 1572-1574.
Wilgenbusch, J.C. and D. Swofford. 2003. Inferring evolutionary trees with PAUP*.
Curr Protoc Bioinformatics Chapter 6: Unit 6 4.
APPENDIX: Oligonucleotide sequences
All oligos used in this study were purified by basic desalting unless otherwise stated.
Sequences are given in 5’-3’ direction.
3F
5F
7F
9F
11F
13F
15F
17F
19F
21F
23F
25F
27F
29F
31F
33F
35F
37F
39F
41F
43F
45F
47F
49F
51F
53F
55F
57F
59F
61F
63F
65F
67F
69F
71F
73F
75F
77F
79F
81F
83F
85F
cave bear multiplex PCR primers, set "ODD"
GCACGCGTTTTTAGATATT
3R
ATGTGGGATTTTGGATATGA
AAATTAAGATCTATCTATAGATATTTTTTT
5R
AACTCGTCTAGGCATTTTCA
AGATTACACATGYAAGTCTCC
7R
TCGTTCATGGCTTAATTTTT
ATTGACCCGAGTTAATAGGC
9R
GGATCTTAGCTRTCGTGTGG
ACAAAATTATTCGCCAGAGA
11R
ATTCCTTTTAAGGGTTTGCT
TTTTCTATTCAAGAACAACTTACG
13R
CTTGCGTTTTATTTGGTTTC
TTACACCCAGAGGATTTCAC
15R
AATCTTTCATCATTCCCTTG
CTAACAAAGAGAACTTAAGCTAGGT
17R
AAATTCTATTCTGGGCAACC
GGATACAACCTTACTTAGAGAGTA
19R
TCATATTAGCATTGTTGCTTCT
AACGTAGAAATAATCCAACAA
21R
CTCCAATACTGGGAATGCT
AGGTAGCATAATCATTTGTTCTC
23R
TAAAGCTCCATAGGGTCTTCT
CGACCTCGGAGCATAAA
25R
TCGTAAACCCTATTGTCGAT
TCCAGGTCGGTTTCTATC
27R
TCTGCCACCCTAACAAGGC
CTAGTYGTACCCATTCTCCTC
29R
CAAGGGTTCTTTGGTAAAAA
GTGAGTTCCTCTACCAATGC
31R
CATATGAAATTGTYTGGGCTA
CTGACTAATTTTCCCCACA
33R
TGTTGGTATATTCTGCTAAGAAA
CTTCACTGTAAAAACACTMCTCCT
35R
GGAATGCTTGCTGTGATAAT
ATAGGAATCGAACCTAATCTT
37R
AGGATAATGGTGGATGTGAT
TTAATCCACGRGCCATA
39R
TTATTGCTAGGGCAATRGTGA
AAAAATCGCACCTCTATCC
41R
CTATRATGGCAGCTATTCAGC
TTATCTACAACAACACTATCACTAT
43R
GGCTATGAATATGGGTATAAYA
GTTTCCCTCRGCAAACAATA
45R
ACTTACTTAGGGCTTTGAAGG
GCAAAACAACCGCTTTAAT
47R
GCAAATTCAAAGAAGCAGA
CCATTTTACCTATGTTCATAAATC
49R
GATCTGATCATCCCCCAA
GGTGCYCCCGACATA
51R
TTAGGTCTATTGATGCTCCTG
CCCTGCAATATCTCAATATCA
53R
TGTTGATATAAAATAGGRTCTCC
AAAAGAACCTTTTGGCTATAT
55R
AAATACTTTGACTCCTGTYGG
CTGTTTACAGTAGGAGGCCTT
57R
AGCGTGTAGCCTGAAAATAG
CGGCGATATTCCGACTA
59R
TCCATGASGTCATTCAATGTT
AACCCTCTGGAATTGGTTT
61R
TGATAGGAGAAGTTGCRTCT
ACCAAACTAACGCACACAA
63R
CACTGGTGACCTATGGTTTT
GGCTATTAGAAGTAGACAATCGAG
65R
CCGTAATATAGCCCYGGTC
CGCCTCAGTACTATAGAATCAT
67R
TTGAGACTTTTAACTGGAGAA
AATTTATTTACCTCTTTTATCACC
69R
CTTGTGGTTGTGAATGGATA
CTGTCRATGAACCTAGGAAT
71R
AGGCCATAGGTTGGATAAAT
AACAAGTATTAGYACTATTACAGC
73R
GGGCTTGGATTGACTATATG
ATACTCTTGTTATTACTAGGTCTTAC
75R
GAATCCTGCGAAAAAGAAC
AAGTGCCACTTCTCAACA
77R
ATGGTAAAGGATGCCTCATA
TCCTACGACAACTACACTTTCA
79R
AGAGCTTATTGATTGGAAGTC
CCTTTTGGCTACCACAAT
81R
TTGTGATGCTCAGGGAAG
AATGGGCCGAATATGATAA
83R
CAAAGCAGGGAGGATATTAGA
CTGGTATTCGCTGCCTG
85R
CCAAATTATATTGGGYTTTGA
87F
89F
91F
93F
95F
97F
99F
101F
103F
105F
107F
109F
111F
113F
115F
117F
119F
121F
123F
125F
127F
129F
1F
4F
6F
8F
10F
12F
14F
16F
18F
20F
22F
24F
26F
28F
30F
32F
34F
36F
38F
40F
42F
44F
46F
48F
50F
CTTCTCATTATTATTCTTTACCGAC
87R
GCAGAAAAGGTTATGATCAGG
CTAAACGCGGGCCTTT
89R
TGCTATTATACATGCCAGTCA
GCCGCCGTACTCCTAAA
91R
GGAGTAAGCGATTAGGGAC
TAACGTCCTCCATGCTATTC
93R
GTTCTCCGATAAGGTTGATG
TACTRATCACCACACAACGA
95R
CACAATCTAATGTTTTTGTTAAACT
TCATGGCTTTTTCAACTTTT
97R
GTTTTTATGTGTTGAAGTGCT
ATTCCTTTACTCAGGGCAAG
99R
ATGTTGGGGTCAGTGTGTAT
TGAGARGGAGTAGGGATCA
101R
GCAAAGATTTGTTGGAAGTC
TCCCATCAGCTATAGAAGGA
103R
GGCTGCTGTAAATAGGGTRG
AACCAGCCCCACCTAG
105R
AAGTGCTAGAGCTCCGATAA
AACAACTCTCATTGCTACATC
107R
AATTAGGTATCCTGCGAAAATA
GTTTTATCCTAGCATTAGAACTCA
109R
ATGTCTAGTARTATAGATGCCATTTT
AATCATAGTCTCTAATCAGAAAGG
111R
GCGGCTTTATACAGTTATGG
CACAATCTCAACTTCATCATC
113R
TTATTTGGGTGGGATACTTG
GTARATGGGAGAAGGCTTA
115R
GGATGTTGGTCATTAAGG
ATCCCTCCTCGGAGTATG
117R
CAGATAAAGAAKATGGAGGCT
ATAGCCACCGCATTYATA
119R
AAAGAATCGTGTTAGAGTYGC
AATCCCATCTRACTCAGACAAA
121R
GATGTGGGGTGGGGTAC
GCTATCATTCCTCTTCTACACAC
123R
TGTAAAGTAGAGAATGGAGGCTA
TGGTCTTGTAAGCCAAAAAC
125R
TGGTACAGTACATGAGATGGT
GTGCCCCATGCATATAA
127R
GGAGCGAGAAGAGGTACAC
GGCCATGAYAGCTCTAGATT
129R
ACTGCGACGAGACCTTTAC
cave bear multiplex PCR primers, set "EVEN"
GTGGTGTCATGCATTTGG
1R
CTATATGTCCTGCGACCATT
AATGTACATGCAAACATGAAG
4R
AAAATCAATAGGAGGGAAGC
TTGTAGCTTAATAGTAAAGCAAGG
6R
TTCAAATCGCTTTAAGATCC
CACGGGATACAGCAGTG
8R
TTCTTTCACACGCTTTACG
CTACGAAAGTGACTTTAATRCTCTC
10R
CTTTGAGTTTTAAGCTGTTGC
ATTCAGTCTATATACCGCCATC
12R
TCCACCTTTAGTTTTTARTTTCA
TGACATAAGCCAAACATAACC
14R
CTAGCTCTGGGTTCAAAGTG
TCGGAGCTATAGAGARAGTACC
16R
TCATAGGTAGCTCGTCTGGT
TAACGAGCCTGGTGATAGC
18R
TTCTAAGCCTACTATGGTTTAAT
AACAACTGGGCTAATCTATTT
20R
AACAATTGGTTTGGTAGGTG
GCCTGTTTACCAAAAACATC
22R
GTGTGGCCTTTCATACAAGT
GCGGGAATAAAAYAATAAGA
24R
TTAATACCACTCGGAGGTTG
CGCAATCCTATTYAAGAGT
26R
TGGGAGAGGTCATTTRAA
CAATGTTGCCCAAGAAAC
28R
TAGTGTTARGAAGGCTACGG
CCTATCGCAGATGCTAYAAAA
30R
TTTATGTTGACAAGGGGGTA
CTCTAATTGGAGCTCTACGA
32R
TCATATTATGGCCAGAGGTC
AGCAGGYCCATTCGC
34R
CACGGATTCATAGGAAAGAA
GCCCTGTGCATGTGAC
36R
GCACGAAGATTTTTGAGTTC
AAAACCACCCATTCTTATCA
38R
TGAGGAAATATTTTGTAGAAGC
CCAATCGCATCAACYGTA
40R
GATGGATGGTGAAATTTGATA
ATACTCTTCAATCGCTCACA
42R
GGTRATTTATTTCATGTGTGG
AATYATTCAAGAGTTGACAAAA
44R
TTTTTATGCTTTCAAAYTGTCA
AATCATGRACTAGAGATTTAGGC
46R
AAAAGCCCACCGATCTA
AAGCCCCGGCAGAAT
48R
TGTCTTTATGGTTCGTAGAGAA
AGCTGGGTCAGCCYG
50R
GTTATTCATTCGAGGAAACG
52F
54F
56F
58F
60F
62F
64F
66F
68F
70F
72F
74F
76F
78F
80F
82F
84F
86F
88F
90F
92F
94F
96F
98F
100F
102F
104F
106F
108F
110F
112F
114F
116F
118F
120F
122F
124F
126F
128F
1F
2F
3F
4F
5F
6F
7F
8F
CTCTAGCGGGTAATCTGG
52R
AGGACTGATCATACAAAYAGAGG
TTTTGACCCAGCAGGAG
54R
CATTATCGCTCAGACTATTCC
TTCACTTCAGCYACCATAAT
56R
GAGTTAGCTAGGACAATTCCTG
GGGTTTGTCCACTGATTC
58R
TTTCATGTTGTRTAGGCATC
GGTGGCAGTRGTAGAACTCAC
60R
TGAGAGAGACATAGTGGTTATGA
GCATACCCCTTCCAAATAG
62R
CTACTTCTTGTGCGTCYATT
TGAAATCAATAATCCCTCACT
64R
GTTATTTCTATGGGCAGCAC
CCAGACAGCTCTTATAGCCA
66R
GGTTAATGCTGTGTTAGCTTC
TCTATCCATAGTTCTAACATTATTTAT
68R
TAGGAATTCCCAYTATCGTT
CGGCTAACATCAAAACAAAT
70R
TGCCCAYAAGGGAATAG
GTAATTATYGAAACAATCAGC
72R
GTAGCACTAGAATGGTGAAGG
ATGACTCACCAAACACATGC
74R
CCACCATTGATACATGGTAAGTA
TCCTATTTATCGTATCGGAAG
76R
CGGATGCAAGAAGTACTGAA
CCTGCAAGCTTCAGAGTA
78R
GAAATGGTGACTTGATGTG
TTGCTTCTTTAGTATTGATCAG
80R
TGCTTTCTCTGCGTARATATT
CTAGAAATTGCACTACTCCTC
82R
CGAAATCAYTTGTTTTGGTT
GACTGCTCATYTATCGATCC
84R
GACAGTCCTAGTGCTGCYTC
CCCACTATAATATTARTACCTCTTAC
86R
TAATAGRGGGGCTGATAGGG
TCACTATACTAATCCTCCTACAAT
88R
ACCCCACTAGGGTGTAAAAT
AACTCCTGATCCAGTATCTTTC
90R
TATTATGCCGTAGCCTCCTA
GCTTACGCCAAACAGATTTA
92R
CGTAGTTGGAGTTTGCAAGA
AGTCTCACTAATCTAKCACTCC
94R
GATGTGGTCTGTGCACTTG
AATTCTAGGACCYATTTACTGT
96R
GACCAATGGATTACTTCYATCC
TTAATGATACCAATTATCCTCAC
98R
ATAGTTATTCAATGTCAGTTTGARA
GATCGATCATGGAATTTTCT
100R
ACCCRATAAGGAGGAAAGAT
TTTACTCAATACRAATGCATG
102R
TAGGGCTGAAACAGGAGTA
ACAGCCACTTTATGCCTAGG
104R
TGTGTGCAGATATGAAGGAA
CCTRCCACTTACCACTACCG
106R
GTACTGTAGGCAGCGGTTAT
CCATCAAACGTCTACTTCTAGG
108R
CAAGTTTGAGAGTTTGTGAGA
CCTCCTRCCAATAATGAGCTT
110R
TGTGATCATGAAGGAGAGAA
CCACCCAGTGACAATAACTAA
112R
ATTGATTGCCTGTTATGTCC
GGCCATRGCCGTAGTATAA
114R
GGGTTTTGTAGGGTTTTCTT
AAAAATCACYGTTGTACTTCA
116R
GCCTGTTAGGATCTGTAGAACT
TCCGATACATACATGCAAAC
118R
CATTTGGCCTCAGGGTA
GGRGGCTTTTCCGTAGATAA
120R
TTGTATAGTATGGGTGAAATGG
CCCCGCAAAYCCAC
122R
GGAATATCATTCCTCGTTGT
CCTTCATCATTATCGGACAG
124R
TGAGTCTTAGGGAGGGTAAA
CATACCATTATTTTACTCTACACTCT
126R
TCATGTAAAGCCAAGCATAA
GAAACCAGCAAYCCTTG
128R
GGCTGATTAGTCATTAGTCCA
elephant multiplex PCR primer set
TTTCTATTCTCCATGAATGAACCA
1R
CAAACAAATTGAGAAAACAGTGC
CACTCCCAGCACACCAGAC
2R
GAGTGGGTTCATTGTCACCA
TGAACTCAGAGTGTAAGTGTGGG
3R
TTGGACAATAAGAAATAGCTGGC
AACCACCATTGTCCACTTTG
4R
CAGCTGCCAGCAACAATG
GACATCCAAACATTTTCAGGC
5R
TGGAAGGTGCTCAGTGCTTA
GTGGGTCTACAAATCACCGC
6R
CACAGTGATTGAAAGCGGAA
GGGACTCCTAGGACAATCCAG
7R
AAACTGCACCTGGCCTTATG
AGGAATCGGGTGAGTGAGTG
8R
CCACACTAAAAGGGACCCAA
9F
10F
11F
12F
13F
14F
15F
16F
17F
18F
19F
20F
21F
22F
23F
24F
25F
26F
27F
MP-A1
MP-A2
MP-A3
MP-A4
MP-A5
MP-A6
MP-A7
MP-A8
MP-A9
MP-A10
MP-A11
MP-A12
MP-A13
MP-A14
MP-A15
MP-A16
MP-A17
MP-A18
MP-A19
MP-A20
MP-A21
MP-A22
MP-A23
MP-A24
MP-A25
MP-A26
MP-A27
MP-A28
GTCTCTTCTGATGGTGGGCT
9R
CATGTGGAGAACTTCCTTTGC
TCTTGCTTTGGGACGGATAC
10R
ATGACGGGGCTTCTTTCTTT
GCATGTGTGAGCTCTTCCCT
11R
GCAGGATTCTTGCTTGCTTC
GCTCCACTGTGTGAGTCATCAT
12R
TGCTGCAGAGACAGAAGGAA
ACACCTCTGAGCTTCCCTGA
13R
TGCTGTGTCGACTCCTCTTG
AGCAGGTGGTTGAGTGTGTG
14R
GTGCTTGGCCTAGGAAACAA
AGGAGTTGCCAGACCTGACC
15R
TTGTGCACTGCTCCTCACTT
GAAGCATTGAAATAGCTGCCT
16R
TTGGACTTTTTAAACCATCTACCTG
GCAGGCACACAAAGGGGTCT
17R
GGCGCGGGGCCTAGATTT
ACTCTGCAAGGCGGTACATC
18R
ATCAGCATAATACGCCCGAC
ATGGGCTGCAAAATAAGTGG
19R
GATCCGGACTTAGGAGCCC
CCCCTCTCCTGTGGTTTGTA
20R
GATGTGTTTCATCAAAGACTCAGTA
TGAGTATCTTCACCCCTGGC
21R
GCAGCCAGCCAAATAGGTAG
CAATTGTGGAAACATCAAAACTG
22R
CCATTGGCTAGTCCCAACAT
GACCCAAGTGACCCCTCTCT
23R
CATGGAGCTGCAGTGAGTTG
AACTGACTGACAGGGTGCG
24R
GGGATGGTCCCATAGATCAC
CCCCCTATGGGATACCTTGA
25R
GCAAAAGCTCAGACTCTTTGTAA
CACAGCTGAGGGAAGAGAGG
26R
CACATGGCCTAACCAAGTTAAT
AAGTAATGGCATGCGGAATC
27R
AGAAGCCCCTATCCTTCCAA
barcoding adapter oligos
CCCATCTGTTCCCTCCCTGTCTCAGTGACGTG
MP-A1c
CACGTCACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGACAGCTG
MP-A2c
CAGCTGTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGAGCACTG
MP-A3c
CAGTGCTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTACTATG
MP-A4c
CATAGTACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTCTGATG
MP-A5c
CATCAGACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGATGCATG
MP-A6c
CATGCATCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGACTGTCG
MP-A7c
CGACAGTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTACGTCG
MP-A8c
CGACGTACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTGTCTCG
MP-A9c
CGAGACACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGAGCTGCG
MP-A10c
CGCAGCTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTCATGCG
MP-A11c
CGCATGACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTATAGCG
MP-A12c
CGCTATACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGACGAGCG
MP-A13c
CGCTCGTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGATCGACG
MP-A14c
CGTCGATCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTGAGACG
MP-A15c
CGTCTCACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTAGCACG
MP-A16c
CGTGCTACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGACACACG
MP-A17c
CGTGTGTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGAGAGTAG
MP-A18c
CTACTCTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTCACTAG
MP-A19c
CTAGTGACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTAGATAG
MP-A20c
CTATCTACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGATGTGAG
MP-A21c
CTCACATCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGAGTCGAG
MP-A22c
CTCGACTCTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTGCAGAG
MP-A23c
CTCTGCACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTCGTCAG
MP-A24c
CTGACGACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTGTGCAG
MP-A25c
CTGCACACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTCGTGTC
MP-A26c
GACACGACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGTGCTCTC
MP-A27c
GAGAGCACTGAG
CCCATCTGTTCCCTCCCTGTCTCAGAGATATC
MP-A28c
GATATCTCTGAG
MP-A29
MP-A30
MP-A31
MP-A32
MP-A33
MP-A34
MP-A35
MP-A36
MP-A37
MP-A38
MP-A39
MP-A40
MP-A41
MP-A42
MP-A43
MP-A44
MP-A45
MP-A46
MP-A47
MP-A48
MP-A49
MP-A50
MP-A51
MP-A52
MP-A53
MP-A54
MP-A55
MP-A56
MP-A57
MP-A58
MP-A59
MP-A60
MP-A61
MP-A62
MP-A63
MP-A64
MP-A65
MP-A66
MP-A67
MP-A68
MP-A69
MP-A70
MP-B
CCCATCTGTTCCCTCCCTGTCTCAGTATCATC
MP-A29c
CCCATCTGTTCCCTCCCTGTCTCAGTGAGTGC
MP-A30c
CCCATCTGTTCCCTCCCTGTCTCAGTCGATGC
MP-A31c
CCCATCTGTTCCCTCCCTGTCTCAGTAGTCGC
MP-A32c
CCCATCTGTTCCCTCCCTGTCTCAGACTGCGC
MP-A33c
CCCATCTGTTCCCTCCCTGTCTCAGTGTACGC
MP-A34c
CCCATCTGTTCCCTCCCTGTCTCAGACGTAGC
MP-A35c
CCCATCTGTTCCCTCCCTGTCTCAGTACGAGC
MP-A36c
CCCATCTGTTCCCTCCCTGTCTCAGATAGAGC
MP-A37c
CCCATCTGTTCCCTCCCTGTCTCAGAGTCAGC
MP-A38c
CCCATCTGTTCCCTCCCTGTCTCAGTCACAGC
MP-A39c
CCCATCTGTTCCCTCCCTGTCTCAGTATGTAC
MP-A40c
CCCATCTGTTCCCTCCCTGTCTCAGATGCTAC
MP-A41c
CCCATCTGTTCCCTCCCTGTCTCAGAGTATAC
MP-A42c
CCCATCTGTTCCCTCCCTGTCTCAGTGATGAC
MP-A43c
CCCATCTGTTCCCTCCCTGTCTCAGTAGCGAC
MP-A44c
CCCATCTGTTCCCTCCCTGTCTCAGACACGAC
MP-A45c
CCCATCTGTTCCCTCCCTGTCTCAGTCTAGAC
MP-A46c
CCCATCTGTTCCCTCCCTGTCTCAGATCAGAC
MP-A47c
CCCATCTGTTCCCTCCCTGTCTCAGATATCAC
MP-A48c
CCCATCTGTTCCCTCCCTGTCTCAGAGCGCAC
MP-A49c
CCCATCTGTTCCCTCCCTGTCTCAGTCAGCAC
MP-A50c
CCCATCTGTTCCCTCCCTGTCTCAGACGACAC
MP-A51c
CCCATCTGTTCCCTCCCTGTCTCAGTACACAC
MP-A52c
CCCATCTGTTCCCTCCCTGTCTCAGATAGTAC
MP-A53c
CCCATCTGTTCCCTCCCTGTCTCAGACTGTAC
MP-A54c
CCCATCTGTTCCCTCCCTGTCTCAGATGCAGC
MP-A55c
CCCATCTGTTCCCTCCCTGTCTCAGAGCGAGC
MP-A56c
CCCATCTGTTCCCTCCCTGTCTCAGTGTGAGC
MP-A57c
CCCATCTGTTCCCTCCCTGTCTCAGTGCTAGC
MP-A58c
CCCATCTGTTCCCTCCCTGTCTCAGATCTAGC
MP-A59c
CCCATCTGTTCCCTCCCTGTCTCAGATCACGC
MP-A60c
CCCATCTGTTCCCTCCCTGTCTCAGAGAGCGC
MP-A61c
CCCATCTGTTCCCTCCCTGTCTCAGTGCGCGC
MP-A62c
CCCATCTGTTCCCTCCCTGTCTCAGTATGCGC
MP-A63c
CCCATCTGTTCCCTCCCTGTCTCAGACATCGC
MP-A64c
CCCATCTGTTCCCTCCCTGTCTCAGTGATCGC
MP-A65c
CCCATCTGTTCCCTCCCTGTCTCAGAGCTCGC
MP-A66c
CCCATCTGTTCCCTCCCTGTCTCAGATGTCGC
MP-A67c
CCCATCTGTTCCCTCCCTGTCTCAGTGCATGC
MP-A68c
CCCATCTGTTCCCTCCCTGTCTCAGATGATGC
MP-A69c
CCCATCTGTTCCCTCCCTGTCTCAGTATATGC
MP-A70c
GCCTATCCCCTGTTGCGTGTCTCAG
MP-Bc
library amplification oligos (HPLC purified)
MP-make454-A
CCATCTCATCCCTGCGTGTCCCATCTGTTCCCTCCCTGT
MP-make454-B
CCTATCCCCTGTGTGCCTTGCCTATCCCCTGTTGCGTGT
GATGATACTGAG
GCACTCACTGAG
GCATCGACTGAG
GCGACTACTGAG
GCGCAGTCTGAG
GCGTACACTGAG
GCTACGTCTGAG
GCTCGTACTGAG
GCTCTATCTGAG
GCTGACTCTGAG
GCTGTGACTGAG
GTACATACTGAG
GTAGCATCTGAG
GTATACTCTGAG
GTCATCACTGAG
GTCGCTACTGAG
GTCGTGTCTGAG
GTCTAGACTGAG
GTCTGATCTGAG
GTGATATCTGAG
GTGCGCTCTGAG
GTGCTGACTGAG
GTGTCGTCTGAG
GTGTGTACTGAG
GTACTATCTGAG
GTACAGTCTGAG
GCTGCATCTGAG
GCTCGCTCTGAG
GCTCACACTGAG
GCTAGCACTGAG
GCTAGATCTGAG
GCGTGATCTGAG
GCGCTCTCTGAG
GCGCGCACTGAG
GCGCATACTGAG
GCGATGTCTGAG
GCGATCACTGAG
GCGAGCTCTGAG
GCGACATCTGAG
GCATGCACTGAG
GCATCATCTGAG
GCATATACTGAG
CTGAGACACGCA