Next Article in Journal
Insight into the Role of Extracellular Vesicles in Lysosomal Storage Disorders
Previous Article in Journal
Identification of TPX2 Gene Family in Upland Cotton and its Functional Analysis in Cotton Fiber Development
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 10
Issue 7
10.3390/genes10070509
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Improving Species Identification of Ancient Mammals Based on Next-Generation Sequencing Data

by
Tian Ming Lan
1,2,†,
Yu Lin
2,3,†,
Jacob Njaramba-Ngatia
4,
Xiao Sen Guo
2,
Ren Gui Li
5,
Hai Meng Li
2,6,
Sunil Kumar-Sahu
2,3,
Xie Wang
3,
Xiu Juan Yang
7,
Hua Bing Guo
8,
Wen Hao Xu
9,
Karsten Kristiansen
1,2,
Huan Liu
2,10,* and
Yan Chun Xu
4,*
1
Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
2
BGI-Shenzhen, Shenzhen 518083, China
3
China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
4
College of Wildlife Resources, Northeast Forestry University, Harbin 150040, China
5
Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in The Giant Panda National Park, China Conservation and Research Center of Giant Panda, Dujiangyan 611830, China
6
School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China
7
Heilongjiang Provincial Museum, Harbin 150001, China
8
Forest Inventory and Planning Institute of Jilin Province, Changchun 130022, China
9
College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
10
State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen 518083, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Genes 2019, 10(7), 509; https://doi.org/10.3390/genes10070509
Submission received: 14 May 2019 / Revised: 26 June 2019 / Accepted: 3 July 2019 / Published: 5 July 2019
(This article belongs to the Section Technologies and Resources for Genetics)
Browse Figures
Versions Notes

Abstract

The taxonomical identification merely based on morphology is often difficult for ancient remains. Therefore, universal or specific PCR amplification followed by sequencing and BLAST (basic local alignment search tool) search has become the most frequently used genetic-based method for the species identification of biological samples, including ancient remains. However, it is challenging for these methods to process extremely ancient samples with severe DNA fragmentation and contamination. Here, we applied whole-genome sequencing data from 12 ancient samples with ages ranging from 2.7 to 700 kya to compare different mapping algorithms, and tested different reference databases, mapping similarities and query coverage to explore the best method and mapping parameters that can improve the accuracy of ancient mammal species identification. The selected method and parameters were tested using 152 ancient samples, and 150 of the samples were successfully identified. We further screened the BLAST-based mapping results according to the deamination characteristics of ancient DNA to improve the ability of ancient species identification. Our findings demonstrate a marked improvement to the normal procedures used for ancient species identification, which was achieved through defining the mapping and filtering guidelines to identify true ancient DNA sequences. The guidelines summarized in this study could be valuable in archaeology, paleontology, evolution, and forensic science. For the convenience of the scientific community, we wrote a software script with Perl, called AncSid, which is made available on GitHub.
Keywords: species identification; BLAST; ancient DNA; next-generation sequencing species identification; BLAST; ancient DNA; next-generation sequencing

Share and Cite

MDPI and ACS Style

Lan, T.M.; Lin, Y.; Njaramba-Ngatia, J.; Guo, X.S.; Li, R.G.; Li, H.M.; Kumar-Sahu, S.; Wang, X.; Yang, X.J.; Guo, H.B.; et al. Improving Species Identification of Ancient Mammals Based on Next-Generation Sequencing Data. Genes 2019, 10, 509. https://doi.org/10.3390/genes10070509

AMA Style

Lan TM, Lin Y, Njaramba-Ngatia J, Guo XS, Li RG, Li HM, Kumar-Sahu S, Wang X, Yang XJ, Guo HB, et al. Improving Species Identification of Ancient Mammals Based on Next-Generation Sequencing Data. Genes. 2019; 10(7):509. https://doi.org/10.3390/genes10070509

Chicago/Turabian Style

Lan, Tian Ming, Yu Lin, Jacob Njaramba-Ngatia, Xiao Sen Guo, Ren Gui Li, Hai Meng Li, Sunil Kumar-Sahu, Xie Wang, Xiu Juan Yang, Hua Bing Guo, and et al. 2019. "Improving Species Identification of Ancient Mammals Based on Next-Generation Sequencing Data" Genes 10, no. 7: 509. https://doi.org/10.3390/genes10070509

APA Style

Lan, T. M., Lin, Y., Njaramba-Ngatia, J., Guo, X. S., Li, R. G., Li, H. M., Kumar-Sahu, S., Wang, X., Yang, X. J., Guo, H. B., Xu, W. H., Kristiansen, K., Liu, H., & Xu, Y. C. (2019). Improving Species Identification of Ancient Mammals Based on Next-Generation Sequencing Data. Genes, 10(7), 509. https://doi.org/10.3390/genes10070509

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop