Genetic Analysis Of Tissue Samples From Mummies Found In Peru - Alternative View

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Genetic Analysis Of Tissue Samples From Mummies Found In Peru - Alternative View
Genetic Analysis Of Tissue Samples From Mummies Found In Peru - Alternative View

Video: Genetic Analysis Of Tissue Samples From Mummies Found In Peru - Alternative View

Video: Genetic Analysis Of Tissue Samples From Mummies Found In Peru - Alternative View
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Report on the results of genetic analysis of tissue samples from mummies found in Peru. This report was prepared in November 2018.

Performers

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  • CEN4GEN labs (6756 - 75 Street NW Edmonton, AB Canada T6E 6T9) - Sample preparation and sequencing.
  • ABRAXAS BIOSYSTEMS SAPI DE CV (Mexico) - computer data analysis.

After a preliminary analysis for quality, 3 samples were taken out of 7 submitted samples for further analysis.

Samples for analysis

Designation original name Conditional name Picture
Ancient-0002 Neck Bone Med Seated 00-12 Victoria 4 Victoria Fig. 3.117
Ancient-0003 1 Hand 001 Separate hand with 3 fingers Figure 3.118
Ancient-0004 Momia 5 - DNA Victoria Fig. 3.117

For these samples, the following operations were performed:

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  1. Extraction of DNA.
  2. DNA quality check.
  3. DNA multiplication.
  4. DNA library creation.
  5. DNA sequencing.
  6. Formation of purified sequenced data.
  7. Quality control.
  8. Preliminary analysis by overlaying DNA reads on the human genome.
  9. Analysis for the isolation of short DNA reads typical of ancient DNA.
  10. Overlay of Ancient0003 DNA reads on existing human genome libraries.
  11. Mitochondrial analysis for the detection of D-loop variants and other informative sites for the determination of mitochondrial haplotypes.
  12. Determination of the sex of samples Ancient0003.
  13. Identification of possible foreign organisms in samples.
  14. Analysis of DNA databases to identify similarities with known organisms.
Figure 3.117. Extracting samples from Victoria's neck
Figure 3.117. Extracting samples from Victoria's neck

Figure 3.117. Extracting samples from Victoria's neck.

To identify possible types of organisms present in the samples Ancient0004 and Ancient0002 (Victoria), DNA sketching was carried out (Ondov et al., 2016), in which groups of short fragments, k-mers, were compared with the available databases. The BBTools software was used.

The following organisms were tested:

  1. Bacteria.
  2. Virus.
  3. Plasmids.
  4. Phages.
  5. Fungi.
  6. Plastid.
  7. Diatoms.
  8. Human.
  9. Bos Taurus.
  10. H penzbergensis.
  11. PhaseolusVulgaris.

  12. Mix2: Label for the following genomes:

    • Lotus japonicus chloroplast, complete genome.
    • Canis lupus familiaris cOR9S3P olfactory receptor family 9 subfamily S pseudogene (cOR9S3P) on chromosome 25.
    • Vigna radiata mitochondrion, complete genome.
    • Millettia pinnata chloroplast, complete genome.
    • Curvibacter lanceolatus ATCC 14669 F624DRAFT_scaffold00015.15, whole genome shotgun sequence.
    • Asinibacterium sp. OR53 scaffold1, whole genome shotgun sequence.
    • Bacillus firmus strain LK28 32, whole genome shotgun sequence.
    • Bupleurum falcatum chloroplast, complete genome.
    • Alicycliphilus sp. B1, whole genome shotgun sequence.
    • Bacillus litoralis strain C44 Scaffold1, whole genome shotgun sequence.
    • Chryseobacterium takakiae strain DSM 26898, whole genome shotgun sequence.
    • Paenibacillus sp. FSL R5-0490.
    • Bacillus halosaccharovorans strain DSM 25387 Scaffold3, whole genome shotgun sequence.
    • Rhodospirillales bacterium URHD0017, whole genome shotgun sequence.
    • Bacillus onubensis strain 10J4 10J4_trimmed_contig_26, whole genome shotgun sequence.
    • Radyrhizobium sp. MOS004 mos004_12, whole genome shotgun sequence.
    • Bacillus sp. UMB0899 ERR1203650.17957_1_62.8, whole genome shotgun sequence.

  13. Vertebrates: Label for the following genomes:

    • Amblyraja-radiata_sAmbRad1_p1.fasta.
    • bStrHab1_v1.p_Kakapo.fasta.
    • bTaeGut1_v1.p_ZebraFinch.fasta.
    • GCA_000978405.1_CapAeg_1.0_genomic_CapraAegagrus.fna.
    • GCA_002863925.1_EquCab3.0_genomic_Horse.fna.
    • GCF_000002275.2_Ornithorhynchus_anatinus_5.0.1_genomic.fna.
    • GCF_000002285.3_CanFam3.1_genomic.fna.
    • Macaco_GCF_000772875.2_Mmul_8.0.1_genomic.fna.
    • rGopEvg1_p1_Gopherus_evgoodei_tortuga.fasta.
  14. Protozoa.
Figure 3.118. Image and radiograph of two three-fingered hands
Figure 3.118. Image and radiograph of two three-fingered hands

Figure 3.118. Image and radiograph of two three-fingered hands.

After all the filters, 27974521 reads for Ancient0002 and 304785398 reads for Ancient0004 were received. This shows that 27% of the DNA from the Ancient0002 sample and 90% of the DNA from the Ancient0004 sample cannot be identified with the analyzed organisms' DNA samples from the available databases.

The next stage of the analysis was performed using the megahit v1.1.3 software (Li et al., 2016). The following result was obtained:

  • Ancient0002: 60852 contigs, total 50459431 bp, min 300 bp, max 24990 bp, avg 829 bp, N50 868 bp, 884.385 (5.39%) assembled reads.
  • Ancient0003: 54273 contigs, total 52727201 bp, min 300 bp, max 35094 bp, avg 972 bp, N50 1200 bp, 20,247,568 (65.69%) assembled reads.

The analysis result is shown in the figure.

Image
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Figure 3.116. Ratio of classified reads for 28073655 Ancient0002 reads (top graph) and 25084962 Ancient0004 reads (bottom graph) in comparison with 34904805 DNA base representing 1109518 taxonomic groups
Figure 3.116. Ratio of classified reads for 28073655 Ancient0002 reads (top graph) and 25084962 Ancient0004 reads (bottom graph) in comparison with 34904805 DNA base representing 1109518 taxonomic groups

Figure 3.116. Ratio of classified reads for 28073655 Ancient0002 reads (top graph) and 25084962 Ancient0004 reads (bottom graph) in comparison with 34904805 DNA base representing 1109518 taxonomic groups.

Conclusion

As a result of the analysis, it was shown that the samples Ancient0002 and Ancient0004 (Victoria) do not correspond to the human genome, while the sample Ancient0003 corresponds well to the human one.

Commentary by Korotkov K. G

Note that the three-fingered hand belonged to a large creature, comparable in size to Maria, and the result obtained corresponds to the result of Maria's DNA analysis. Victoria is a representative of the "little creatures" and the result shows that their DNA does not match any modern earthly creatures. Naturally, we do not have data on ancient creatures that have disappeared over millions of years.

Links

  • Corvelo, A., Clarke, WE, Robine, N., & Zody, MC (2018). taxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time. Genome Research, 28 (5), 751-758.
  • Gamba, C., Hanghøj, K., Gaunitz, C., Alfarhan, AH, Alquraishi, SA, Al-Rasheid, KAS, … Orlando, L. (2016). Comparing the performance of three ancient DNA extraction methods for high-throughput sequencing. Molecular Ecology Resources, 16 (2), 459-469.
  • Huang, W., Li, L., Myers, JR, & Marth, GT (2012). ART: a next-generation sequencing read simulator. Bioinformatics, 28 (4), 593-594.
  • Li, D., Luo, R., Liu, C.-M., Leung, C.-M., Ting, H.-F., Sadakane, K., … Lam, T.-W. (2016). MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods, 102, 3-11.
  • Ondov, BD, Treangen, TJ, Melsted, P., Mallonee, AB, Bergman, NH, Koren, S., & Phillippy, AM (2016). Mash: fast genome and metagenome distance estimation using MinHash. Genome Biology, 17 (1), 132.
  • Schubert, M., Ermini, L., Der Sarkissian, C., Jónsson, H., Ginolhac, A., Schaefer, R., … Orlando, L. (2014). Characterization of ancient and modern genomes by SNP detection and phylogenomic and metagenomic analysis using PALEOMIX. Nature Protocols, 9 (5), 1056-1082.
  • Weissensteiner, H., Forer, L., Fuchsberger, C., Schöpf, B., Kloss-Brandstätter, A., Specht, G., … Schönherr, S. (2016). mtDNA-Server: next-generation sequencing data analysis of human mitochondrial DNA in the cloud. Nucleic Acids Research, 44 (W1), W64-W69.
  • Zhang, J., Kobert, K., Flouri, T., & Stamatakis, A. (2014). PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics, 30 (5), 614-620.

Materials provided by Konstantin Georgievich Korotkov (Doctor of Technical Sciences, Professor, University of Information Technologies, Mechanics and Optics) and Dmitry Vladislavovich Galetsky (Candidate of Medical Sciences, I. P. Pavlov First St. Petersburg State Medical University)