1. Genetics and Genomics

Mitochondrial genomes of Pleistocene megafauna retrieved from recent sediment layers of two Siberian lakes

  1. Peter Andreas Seeber  Is a corresponding author
  2. Laura Batke
  3. Yury Dvornikov
  4. Alexandra Schmidt
  5. Yi Wang
  6. Kathleen Stoof-Leichsenring
  7. Katie Moon
  8. Samuel H Vohr
  9. Beth Shapiro
  10. Laura S Epp  Is a corresponding author
  1. Department of Biology, University of Konstanz, Germany
  2. Agroengineering Department/Department of Landscape Design and Sustainable Ecosystems, Agrarian and Technological Institute, RUDN University, Russian Federation
  3. Laboratory of Carbon Monitoring in Terrestrial Ecosystems, Institute of Physicochemical and Biological Problems of Soil Science of the Russian Academy of Sciences, Russian Federation
  4. Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Polar Terrestrial Environmental Systems, Germany
  5. Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, United States
  6. Howard Hughes Medical Institute, University of California, Santa Cruz, United States
  7. Embark Veterinary, Inc, United States
https://doi.org/10.7554/eLife.89992.3
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Cite this article
  1. Peter Andreas Seeber
  2. Laura Batke
  3. Yury Dvornikov
  4. Alexandra Schmidt
  5. Yi Wang
  6. Kathleen Stoof-Leichsenring
  7. Katie Moon
  8. Samuel H Vohr
  9. Beth Shapiro
  10. Laura S Epp
(2024)
Mitochondrial genomes of Pleistocene megafauna retrieved from recent sediment layers of two Siberian lakes
eLife 12:RP89992.
https://doi.org/10.7554/eLife.89992.3
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  3. Download .RIS
3 figures, 16 tables and 1 additional file

Figures

Figure 1
Download asset Open asset
aDNA of Mammuthus in recent lake sediments.

(A) Read counts assigned to Mammuthus (square-root-transformed proportion of the respective number of raw reads per library) after hybridization capture enrichment of aeDNA of core LK-001 (shown are results of 22 libraries; one library was excluded as it did not produce any reads assigned to mammals); square-root transformation of percentage. Indicated are sample depths (in cm; 1.5–80 cm) and approximate ages as per 210Pb chronology (Appendix 1—table 7; to a maximum depth of 39.5 cm). The solid line indicates the general trend. Across the 22 libraries: (B) Fragment length distribution and (C) damage patterns (red indicates C-to-T transitions, blue G-to-A transitions. the Y-axis indicates the percentage of positions with a nucleotide change, the X-axis indicates the position along the fragment).

Figure 2
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Locations of the sediment cores of the present study (Yamal peninsula, Siberia) and previously retrieved mammoth remains and their haplo(sub)groups (Appendix 1—table 6).

The bar chart indicates a maximum-likelihood estimate of the haplogroup proportions derived from the reads from the three sediment core libraries with the most mammoth reads.

Appendix 1—figure 1
Download asset Open asset
Comparison of transformed metabarcoding read counts (A) and ddPCR concentration estimations (B) of Mammuthus primigenius DNA in sediment cores LK-001 and LK-007 from the Yamal peninsula.

Tables

Table 1
Sediment cores retrieved from two lakes on the Yamal peninsula, Siberia.
LakeCoordinatesm above sea levelAreaWater depthCore length
LK-00170°16'45.6" N, 68°53'02.8" E2838 ha17 m80 cm
LK-00770°16'02.8" N, 68°59'35.7" E3639 ha14 m75 cm
Appendix 1—table 1
Sample depths and extraction protocols.
(a) LK-001(b) LK-007
Sample depth (cm)Extraction protocol*Sample depth (cm)Extraction protocol*
1.5PowerLyzer2.0PowerLyzer
4.04.0PowerSoil Pro
7.06.0PowerLyzer
11.08.0PowerSoil Pro
12.010.0PowerLyzer
15,512.0PowerSoil Pro
18.014.0PowerSoil Pro
21.518.0PowerLyzer
23.020.PowerSoil Pro
28.024.0PowerLyzer
31.526.0PowerSoil Pro
35.030.0PowerSoil Pro
40.032.0PowerSoil Pro
44.036.0PowerLyzer
46.538.0PowerSoil Pro
49.042.0PowerSoil Pro
51.044.0PowerLyzer
62.048.0PowerLyzer
65.550.0PowerLyzer
66.554.0PowerLyzer
69.556.0PowerLyzer
73.560.0PowerLyzer
80.062.0PowerSoil Pro
64.0PowerLyzer
66.0PowerSoil Pro
68.0PowerLyzer
70.0PowerSoil Pro
  1. *

    Kits from Qiagen (Hilden, Germany).

Appendix 1—table 2
PowerLyzer DNA extraction.
Day 1:

  • 1. Add 750 μL PowerBead Solution to the PowerBead Tube

  • 2. Transfer 0.25–0.35 g manually homogenized sediment to PowerBead Tube

  • 3. FastPrep bead beating: two times Quickprep protocol (20 s at 4.0 m/s); briefly centrifuge to eliminate foam

  • 4. Lysis mix (per sample):

    • Solution C1 60 µL

    • Proteinase K (20 mg/mL) 2 µL

    • 1 M DTT 25 µL

    • Vortex and briefly centrifuge.

  • 5. Add 87 μL lysis mix to each PowerBead Tube; vortex for 5 min; invert the tube, flick and vortex to dissolve pellet, if present.

  • 6. Incubate overnight at 56 °C and 12 rpm

Day 2:

  • 1. Remove PowerBead Tube from the incubator oven and allow to cool to room temperature

  • 2. Centrifuge at 10,000 x g for 1 min

  • 3. Add 250 μL Solution C2 to a 2 mL collection tube

  • 4. Avoiding the pellet, pour the supernatant from step 2 into the collection tube containing Solution C2; vortex for 5 s

  • 5. Incubate at 2–8 °C for 10 min

  • 6. Centrifuge at 10,000 x g for 1 min

  • 7. Label a new clean 2 mL collection tube and add 250 μL Solution C3

  • 8. Avoiding the pellet, pour up to 800 μL of supernatant to the collection tube containing Solution C3; vortex for 5 s

  • 9. Incubate at 2–8 °C for 10 min

  • 10. Centrifuge at 10,000 x g for 1 min

  • 11. Label a new clean 5 mL collection tube and add 1,400 μL Solution C4

  • 12. Avoiding the pellet, pour 880 μL of supernatant to the collection tube containing Solution C4; vortex for 5 s; briefly centrifuge

  • 13. Load 650 μL of the Solution C4-supernatant mix on a Spin Column

  • 14. Centrifuge the Spin Column at 10,000 x g for 1 min

  • 15. Transfer the Spin Column to a new 2 mL collection tube

  • 16. Repeat steps above until all Solution C4-supernatant mix has been loaded onto the Spin Column

  • 17. Centrifuge the Spin Column at 10,000 x g for 1 min

  • 18. Load 500 μL of Solution C5 on the Spin Column

  • 19. Centrifuge the Spin Column at 10,000 x g for 1 min

  • 20. Transfer the Spin Column to a new 1.5 mL collection tube

  • 21. Centrifuge the Spin Column at 10,000 x g for 1 min

  • 22. Transfer the Spin Column to a new, labelled, and sterile 1.5 mL collection tube

  • 23. Add 65 μL of elution buffer to the center of the filter membrane

  • 24. Incubate at room temperature for 10 min

  • 25. Centrifuge the Spin Column at 10,000 x g for 1 min

  • 26. Repeat steps above for a final elution volume of 120–125 μL

PowerSoil Pro DNA extraction was performed as follows:
Day 1:

  • 1. Spin the PowerBead Pro Tube briefly; add up to 500 mg soil and 800 μL Solution CD1. Vortex briefly to mix. Add 20 µL Proteinase K (2 mg/mL).

  • 2. FastPrep bead beating: two times 20 s at 4.0 m/s; briefly centrifuge to eliminate foam. Incubate at 56 °C overnight.

Day 2:

  • 3. Centrifuge the PowerBead Pro Tube at 15,000 x g for 1 min.

  • 4. Transfer the supernatant to a clean 2 mL microcentrifuge tube.

  • 5. Add 200 μL Solution CD2 and vortex for 5 s.

  • 6. Centrifuge at 15,000 x g for 1 min at room temperature. Transfer up to 700 μL supernatant to a clean 2 mL microcentrifuge tube.

  • 7. Add 600 μL Solution CD3 and vortex for 5 s.

  • 8. Load 650 μL of the lysate on an MB Spin Column and centrifuge at 15,000 x g for 1 min.

  • 9. Discard the flow-through and repeat step 8 to ensure that all of the lysate has passed through the MB Spin Column.

  • 10. Place the MB Spin Column in a clean 2 mL collection tube.

  • 11. Add 500 μL Solution EA to the MB Spin Column. Centrifuge at 15,000 x g for 1 min.

  • 12. Discard the flow-through and place the MB Spin Column back into the same collection tube.

  • 13. Add 500 μL Solution C5 to the MB Spin Column. Centrifuge at 15,000 x g for 1 min.

  • 14. Discard the flow-through and place the MB Spin Column in a new 2 mL collection tube

  • 15. Centrifuge at 16,000 x g for 2 min. Place the MB Spin Column in a new 1.5 mL elution tube.

  • 16. Add 50–100 μL Solution C6 to the center of the white filter membrane; incubate for 5 min, and centrifuge at 15,000 x g for 1 min.

Appendix 1—table 3
Library preparation.
End repairper library
Mix following components in a sterile low-binding PCR tube
NEBNext End Repair Buffer (10 X)5 µL
NEBNext End Repair Enzyme Mix2.5 µL
genomic DNA42.5 µL
Incubate in a thermal cycler for 30 mins at 20 °C.
Purify using QIAquick/MinElute PCR purification kit. Elution: add 32 µl buffer EB and incubate at 37 °C for 5 min before spinning down the DNA at 13,000 rpm for 1 min.
Adapter ligation
Mix following components in a sterile low-binding PCR tube
Quick Ligation Reaction Buffer (10 X)10 µL
nuclease-free water4 µL
P5/P7 adapter mix (50 µM stock)1 µL
DNA as purified in step above30 µL
Quick T4 DNA ligase4.8 µL
*final adapter concentrations for ancient samples should be between 0.25–0.5 µM.
**it is vital to add ligase after mixing DNA with adaptors.
Incubate for 15 min at 25 °C; purify using a QIAquick/MinElute PCR purification kit. Elution: 42 µL buffer EB and incubate at 37 ºC for 5 min before spinning down the DNA at 13,000 rpm for 1 min.
Fill-In Reaction
Add the following reagents into a low-binding PCR tube
ThermoPol Reaction Buffer5 µL
dNTPs (10 mM)2 µL
Bst DNA polymerase3 µL
DNA as eluted above40 µL
Incubate:
20 mins at 65 °C
20 mins at 80 °C
No purification is needed after this step.
Appendix 1—table 4
Indexing PCR.
ReagentµL
H2O3.45
Platinum Hifi Taq Buffer 10 X (Thermo Fisher Scientific)2.50
dNTPs (25 mM)0.25
bovine serum albumin (New England Biolabs)1.00
MgSO4 (50 mM)1.00
Platinum HiFi (5 U/µL; Thermo Fisher Scientific)0.20
total8.40
Index P5 (10 µM)0.80
Index P7 (10 µM)0.80
template DNA15.00
Thermocycling
°Ct
941 min
9415 s8 cycles
6020 s
6860 s
683 min
20store
Appendix 1—table 5
Mitogenome templates of 17 mammal species for design of RNA baits.
OrderSpeciesNCBI accession# of baits
ArtiodactylaBison bisonNC_012346.1446
Bos primigeniusNC_020746.1456
Saiga tataricaNC_013996.1538
Ovis canadensisNC_015889.1522
Ovibos moschatusNC_020631.1542
Cervus elaphusNC_007704.2523
Rangifer tarandusNC_007703.1526
Alces alcesNC_020677.1520
Camelus ferusNC_009629.2583
PerissodactylaEquus przewalskiiNC_024030.1575
Coelodonta antiquitatisNC_012681.1571
LagomorphaLepus arcticusNC_044769.1586
Ochotona collarisNC_003033.1591
ProboscideaMammuthus primigeniusNC_007596.2588
EulipotyphlaSorex tundrensisNC_025327.1584
RodentiaCastor canadensisNC_033912.1584
Dicrostonyx torquatusNC_034646.1575
9,310
Appendix 1—table 6
Cladonia rangiferina sequences for RNA bait design (shown are the NCBI accessions).
ITS-1
MN756840.1; DQ394367.1; JQ695919.1; MK179592.1; KP031549.1; KP001202.1; AF458306.1; KT792792.1; MK811970.1; KT792788.1; MK508944.1; GU169225.1; KP001197.1; KP001201.1; MK812260.1; MK811708.1; KY119381.1; MK508952.1; KT792789.1; EU266113.1; KY266884.1; KP001192.1; KP001190.1; JQ695918.1; KT792790.1; JQ695920.1; KP001191.1; AF458307.1; KP001200.1; MK508943.1; MK812460.1; MK508937.1; KT792791.1
resulting in 23 baits
ITS-2
KT792789.1; KP001190.1; AF458307.1; JQ695919.1; MK179592.1; DQ394367.1; KP001194.1; KP001193.1; KY266884.1; KP001199.1; KP001192.1; MK300750.1; MN756487.1; MK508937.1; KP001200.1; MK812460.1; MK508943.1; KP001191.1; KP031549.1; KP001202.1; AF458306.1; MK811970.1; KY119381.1; KP001198.1; MK812260.1; MK811708.1; GU169225.1; JQ695918.1; KP001201.1
resulting in 6 baits
Appendix 1—table 7
Reference mitogenomes used for mapping.
NC_020679.1Antilocapra americanaNC_018783.1Equus ovodovi
NC_012346.1Bison bisonHM118851.1Equus hemionus
NC_020746.1Saiga tataricaMK982180.1Equus asinus
NC_013996.1Bos primigeniusNC_012681.1Coelodonta antiquitatis
NC_015889.1Ovis canadensisNC_007596.2Mammuthus primigenius
NC_020630.1Oreamnos americanusFR691686.1Castor fiber
NC_020631.1Ovibos moschatusNC_033912.1Castor canadensis
NC_027233.1Bison priscusNC_034313.1Dicrostonyx groenlandicus
NC_009629.2Camelus ferusNC_034646.1Dicrostonyx torquatus
KR822422.1Camelops cf. hesternusJN181159.1Peromyscus leucopus
NC_013836.1Cervus elaphus xanthopygusNC_006853.1Bos taurus
NC_007704.2Cervus elaphusKM093871.1Capra hircus
NC_013840.1Cervus elaphus yarkandensisNC_015241.1Microtus fortis fortis
KP405229.1Alces alces cameloidesKP200876.1Vulpes lagopus
NC_020677.1Alces alcesHM236180.1Ovis aries
NC_020729.1Odocoileus hemionusKT448275.1Canis latrans
NC_015247.1Odocoileus virginianusJN632610.1Capreolus capreolus
NC_007703.1Rangifer tarandusKJ681493.1Capreolus pygargus
KY987554.1Platygonus compressusJN632629.1Dama dama
NC_002008.4Canis lupus familiarisKM982549.1Lynx lynx
NC_009686.1Canis lupus lupusKP202265.1Panthera pardus
NC_013445.1Cuon alpinusNC_026460.1Rhinolophus macrotis
NC_026529.1Vulpes lagopusY07726.1Ceratotherium simum
NC_028302.1Panthera leoNC_005089.1Mus musculus
NC_022842.1Panthera oncaAM711900.1Meles meles
NC_010642.1Panthera tigrisKM091450.1Mustela erminea
NC_014456.1Lynx rufusNC_005358.1Ochotona princeps
NC_020642.1Martes americanaNC_012095.1Sus scrofa domesticus
NC_020641.1Neovison visonDQ480489.1Canis lupus familiaris
NC_024942.1Mustela nigripesNC_020670.1Crocuta crocuta
NC_020664.1Martes pennantiNC_011116.1Arctodus simus
NC_020639.1Mustela nivalisNC_027963.1Sorex araneus
NC_009685.1Gulo guloNC_025327.1Sorex tundrensis
NC_011112.1Ursus spelaeusKJ397607.1Lepus arcticus
NC_003426.1Ursus americanusNC_001640.1Equus caballus
NC_003427.1Ursus arctosNC_024030.1Equus przewalskii
NC_003428.1Ursus maritimus
Appendix 1—table 8
Command lines and software used for initial mapping, processing, and taxonomic assignment.
adapter trimming, filtering, and merging: leeHom Renaud et al., 2014:src/leeHom -t 120 –ancientdna –auto -fq1 file_R1.fastq.gz -fq2 file_R2.fastq.gz -fqo leehom_out
mapping: BWA Li and Durbin, 2009 against 75 mammal mitogenomes Appendix 1—table 3:bwa index reference_mitogenomes.fasta
bwa aln reference_mitogenomes.fasta leehom_out.fq.gz -l 16,000 n 0.01 -O 2 -o 2 t 8>bwa_out.sai
bwa samse reference_mitogenomes.fasta bwa_out.sai leehom_out.fq.gz>bwa_out.sam
samtools view -q ≥ 30 S -b bwa_out.sam>bwa_out.bam
remove duplicates: samtools Li and Durbin, 2009samtools collate -o bwa_out_col.bam bwa_out.bam
samtools fixmate -m bwa_out_col.bam bwa_out_fixmate.bam
samtools sort -o bwa_out_pos.bam bwa_out_fixmate.bam
samtools markdup bwa_out_pos.bam bwa_out_mark.bam
samtools fastq bwa_out_mark.bam>bwa_out.fastq
fastq to fastased -n ‘1~4 s/^@/>/p;2~4 p’ bwa_out.fastq>bwa_out.fasta
#alignment: blastn Altschul et al., 1990
blastn -db ncbi_nt -query bwa_out.fasta -evalue 0.01 -out
blastn_out.fasta
aDNA damage: mapDamage Ginolhac et al., 2011bwa index reference.fasta
bwa aln reference.fasta sample.fasta >sample.sai
bwa samse referecne.fasta sample.sai sample.fasta >sample.sam samtools view -q 25 S -b sample.sam >sample.bam
mapDamage -i sample.bam -r reference.fasta
mapDamage -d results_ sample/ -y 0.1 --plot-only
mapDamage -i sample.bam -r reference.fasta –rescale
mapDamage -d results_sample / --forward --stats-only -v -r reference.fasta
Appendix 1—table 9
Reference mammoth mitogenomes used for panel.
CladeHaplogroupSubgroupAccession numbersProportion of reads assigned to haplogroup
IIAEU153451, EU153450-
IIIBB0KX027526, KX027531-
B1KX0275260.1615
B2KX027531-
ICKX027498, KX027565, KX027567, JF912200, KX027499, KX027502-
ID&ED0DQ316067, EU153454, EU153447, EU153456, EU153449, EU153455,
EU153446		-
D1DQ316067-
D2EU153454-
D3EU1534470.2790
D4EU153456-
D5EU1534490.0765
D6EU1534550.4829
D7EU153446-
IFKX027503, KX027512, NC_015529, KX027511, KX027548, KX027547, KX027556, KX027559, KX027550-
Krestovka mammothKPRJEB42269 (European Nucleotide Archive)-
Conventional PCR
94 °C2 min
94 °C30 s55 cycles
54 °C30 s
68 °C20 s
68 °C1 min
Appendix 1—table 10
Conventional PCR.
ReagentµL
H2O14.85
Platinum Hifi Taq Buffer 10 X (Thermo Fisher Scientific)2.5
bovine serum albumin (New England Biolabs)0.2
MgSO4 (50 mM)1.00
dNTPs (25 mM)0.25
Platinum HiFi (5 U/µL; Thermo Fisher Scientific)0.20
Blocking primer R (1 µM)0.5
Blocking primer F (1 µM)0.5
total20.00
template DNA3.00
Thermocycling
°Ct
945 min
9430 s40 cycles
5030 s
6830 s
6810 min
RTstore
Appendix 1—table 11
Conventional PCR.
Load dataobi import --quality-sanger file_R1.fastq reads1
obi import --quality-sanger file_R2.fastq reads2
Import tagsobi import --ngsfilter-input taglist.txt ngsfile
Align paired-end readsobi alignpairedend -R reads2 reads1 aligned_reads
Grep entries whose mode are alignmentobi grep -a mode:alignment aligned_reads good_sequences
Assign alignments to individual PCRsobi ngsfilter -t ngsfile -u unidentified_sequences good_sequences identified_sequences
Filter out sequencesobi grep -p "sequence[’score']>50" identified_sequences identified_sequences_filtered
obi grep -p "sequence[’score_norm']>0.9"
identified_sequences_filtered identified_sequences_filtered_adj
Dereplicate Sequencesobi uniq -m sample identified_sequences_filtered_adj dereplicated_sequences_filtered
Keep only useful tagsobi annotate -k COUNT -k MERGED_sample
dereplicated_sequences_filtered cleaned_metadata_sequences
Discard sequences that are shorter than 60 bp (based on primer pair)obi grep -p "len(sequence) ≥ 60 and sequence['COUNT'] ≥ 10" cleaned_metadata_sequences denoised_sequences
Clean the sequences from PCR/sequencing errorsobi clean -s MERGED_sample -r 0.05 H denoised_sequences cleaned_sequences
Load databasecp STD_MAM_1.dat.gz ~/edna_LauraB/master/mammalia/database/
Import it into DMSobi import /data/scc/edna/LauraBa/master/mammalia/database/STD_MAM_1.dat.gz database_mam
obi import --embl EMBL embl_refs
Download the taxonomywget https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/taxdump.tar.gz
Import the taxonomy in the DMSobi import --taxdump /data/scc/edna/LauraBa/master/mammalia/taxdump.tar.gz taxonomy/my_tax
Cleaning the database with in silico PCRobi ecopcr -e 3 l 50 L 150 F CGAGAAGACCCTATGGAGCT -R CCGAGGTCRCCCCAACC --taxonomy taxonomy/my_tax embl_refs mam_refs
Filter sequencesobi grep --require-rank=species --require-rank=genus --require-rank=family --taxonomy taxonomy/my_tax mam_refs
mam_refs_clean
Dereplicate identical sequencesobi uniq --taxonomy taxonomy/my_tax mam_refs_clean
mam_refs_uniq
Add taxid at the family levelobi grep --require-rank=family --taxonomy taxonomy/my_tax mam_refs_uniq
Build the reference databaseobi build_ref_db -t 0.97 --taxonomy taxonomy/my_tax mam_refs_uniq_clean mam_db_97
Assign each sequence to a taxonobi ecotag -m 0.97 --taxonomy taxonomy/my_tax -R mam_db_97 cleaned_sequences assigned_sequences
Align the sequencesobi align -t 0.95 assigned_sequences aligned_assigned_sequences
Export tables for downstream data analysisobi grep -A SCIENTIFIC_NAME assigned_sequences
assigned_for_metabR
Output two tables required by metabaRobi annotate -k MERGED_sample assigned_for_metabR assigned_for_metabR_reads_tableobi export --tab-output --output-na-string 0
assigned_for_metabR_reads_table >mam_reads_01.txtobi annotate --taxonomy taxonomy/my_tax \
--with-taxon-at-rank superkingdom \
--with-taxon-at-rank kingdom \
--with-taxon-at-rank phylum \
--with-taxon-at-rank subphylum \
--with-taxon-at-rank class \
--with-taxon-at-rank subclass \
--with-taxon-at-rank order \
--with-taxon-at-rank suborder \
--with-taxon-at-rank infraorder \
--with-taxon-at-rank superfamily \
--with-taxon-at-rank family \
--with-taxon-at-rank genus \
--with-taxon-at-rank species \
--with-taxon-at-rank subspecies \ assigned_for_metabR assigned_for_metabR_taxInfo
obi annotate \
-k BEST_IDENTITY -k TAXID -k SCIENTIFIC_NAME -k COUNT -k seq_length \
-k superkingdom_name \
-k kingdom_name \
-k phylum_name \
-k subphylum_name \
-k class_name \
-k subclass_name \
-k order_name \
-k suborder_name \
-k infraorder_name \
-k superfamily_name \
-k family_name \
-k genus_name \
-k species_name \
assigned_for_metabR_taxInfo assigned_for_metabR_motus
obi export --tab-output assigned_for_metabR_motus >mam_motus_01.txt
Further processing of the data sets was done using RStudio.
Editing files for metabarreads<- dt_reads %>%
dplyr::select(-c("DEFINITION", "NUC_SEQ"))%>% as.data.frame() %>%
janitor::row_to_names(row_number = 897, remove_rows_above = FALSE, remove_row = TRUE) %>% mutate_if(is.integer,as.numeric)
Assign name to first columnreads <- cbind(rownames(reads),reads)
rownames(reads) <- NULL
colnames(reads) <- c(names(reads))
colnames(reads)(1) <- "pcr_id"
Edit the names of the columnreads$pcr_id = strsplit(reads$pcr_id,"[.]") reads$pcr_id = sapply(reads$pcr_id, function(x) x[length(x)]) rownames(reads)<- reads$pcr_id
Organizing the MOTUs tablemotus<- dplyr::select(dt_motus, 'ID', 'NUC_SEQ', 'COUNT','BEST_IDENTITY', 'TAXID', 'SCIENTIFIC_NAME', ’superkingdom_name', ’species_name', 'class_name', 'order_name', 'family_name', 'genus_name', 'kingdom_name', 'phylum_name', ’subphylum_name', ’subclass_name', ’suborder_name')
names(motus)[names(motus) == 'NUC_SEQ'] <- ’sequence'
Appendix 1—table 12
Conventional PCR.
ReagentµL
ddPCR Supermix for probes11
H2O (DEPC)6.8
20 x Target-Primers/Probe (FAM)1.1
20 x Target-Primers/Probe (HEX)1.1
total20
template DNA2.0
Thermocycling
°Ct
9510 min
9430 sec40 cycles
5030 sec
6030 sec
Appendix 1—table 13
210Pb chronology of Yamal lake sediment core LK-001.
DepthChronologySedimentation Rate
DateAge
cmg cm–2ADy±g cm–2 y–1cm y–1
0.000.0201900
0.250.22018110.340.37
1.251.12016320.340.37
2.251.92013620.340.37
3.252.82010920.340.37
4.253.820081120.340.37
5.254.720051420.340.37
6.255.720021720.340.37
7.256.719992030.360.37
8.257.619962330.390.41
10.259.719922730.490.47
12.2511.819883140.530.49
14.2514.019843540.550.51
14.7514.519833640.550.51
15.5015.419813840.550.51
16.5016.519803940.550.51
17.5017.619784140.550.51
18.5018.619764340.550.51
20.5020.719714850.550.51
22.5022.719685160.550.51
23.5023.719665360.550.51
24.5024.819645560.550.51
25.5025.919625770.440.42
26.5027.019615870.370.36
27.5028.019576280.300.29
28.5029.019526790.280.22
29.5030.2194970100.230.19
31.5032.6193881100.230.19
33.5034.7193386100.230.19
35.5036.9192792110.230.19
37.5039.11913106130.230.19
39.5041.41895124170.230.19
Appendix 1—table 14
Radiocarbon dating results.
Sample labelF14C± (abs)Age (y)± (y)Weight (µg C)Comment
LK-001_36.5 cm0.95950.00953327935
LK-001_51 cm0.33960.00568677132148Off; lateral input
LK-001_74 cm0.82480.0234154722813
Appendix 1—table 15
Numbers of sequences assigned to mammals (core LK-001).
depth
sum1.54.07.011.012.015.518.021.523.028.031.535.040.046.549.051.062.065.566.569.573.580.0
Mammuthus primigenius19,64019116252429012056051946662778003697305118813741923631674519111010838141408
Rangifer tarandus18,05525363-3432868864418165459022186124015711574862842714563459911141,621
Dicrostonyx torquatus16,8702111123411112116142711035522104985012983147611933186562002763101114081928
Lepus63711481341052358424540369336630382231404799285141116126352330293298
Coelodonta antiquitatis273733--2811915334755-9712846729814127103152-2501444191
Homo sapiens387------38217--23-25-69-15-----
Ovibos moschatus moschatus145-69-------38---38--------
Castor fiber135----18----15---2751-61---17
Bos105--------------105-------
Cervinae92-------33----3128--------
Saiga tatarica91---------57-34----------
Sus scrofa cristatus85-------34------24----27--
Ochotona74-----------------14---60
Ovis aries musimon70----70-----------------
Bison54----24-30---------------
Crocuta crocuta53------------------53---
Chrotopterus auritus43-----43----------------
Sorex tundrensis32---------------32------
Equus32-----------------7---25
Peromyscus maniculatus bairdii29-------------29--------
Murinae28--------------------28-
Capra21---------------21------
Myopus schisticolor18-------18--------------
Lemmus trimucronatus1616---------------------

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  1. Peter Andreas Seeber
  2. Laura Batke
  3. Yury Dvornikov
  4. Alexandra Schmidt
  5. Yi Wang
  6. Kathleen Stoof-Leichsenring
  7. Katie Moon
  8. Samuel H Vohr
  9. Beth Shapiro
  10. Laura S Epp
(2024)
Mitochondrial genomes of Pleistocene megafauna retrieved from recent sediment layers of two Siberian lakes
eLife 12:RP89992.
https://doi.org/10.7554/eLife.89992.3