Evidence map›Paper›PMID 32206883›Full record

ArticleMolecular genetics and genomics : MGG2020

Next generation sequencing of a set of ancestry-informative SNPs: ancestry assignment of three continental populations and estimating ancestry composition for Mongolians.

Qiong Lan, Yating Fang, Shuyan Mei, Tong Xie, Yanfang Liu, Xiaoye Jin, Guang Yang, Bofeng Zhu

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular genetics and genomics : MGG, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Qiong LanMulti-Omics Innovative Research Center of Forensic Identification; Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Yating FangMulti-Omics Innovative Research Center of Forensic Identification; Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Shuyan MeiMulti-Omics Innovative Research Center of Forensic Identification; Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Tong XieMulti-Omics Innovative Research Center of Forensic Identification; Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Yanfang LiuMulti-Omics Innovative Research Center of Forensic Identification; Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Xiaoye JinKey Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, 710000, China.
Guang YangDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, 19104, USA.
Bofeng ZhuMulti-Omics Innovative Research Center of Forensic Identification; Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China. zhubofeng@i.smu.edu.cn.
Institute of Forensic Science · CNSouthern Medical University · CNXi'an Jiaotong University · CNHospital of the University of Pennsylvania · US

Funding

National Natural Science Foundation of China No. 81525015
6 · The paper itself

Abstract

When traditional short tandem repeat profiling fails to provide valuable information to arrest the criminal, forensic ancestry inference of the biological samples left at the crime scene will probably offer investigative leads and facilitate the investigation process of the case. That is why there are consistent efforts in developing panels for ancestry inference in forensic science. Presently, a 30-plex next generation sequencing-based assay was exploited in this study by assembling well-differentiated single nucleotide polymorphisms for ancestry assignment of unknown individuals from three continental populations (African, European and East Asian). And meanwhile, relatively balanced population-specific differentiation values were maintained to avoid the over-estimation or under-estimation of co-ancestry proportions in individuals with admixed ancestry. The principal component analysis and STRUCTURE analysis of reference populations, test populations and the studied Mongolian group indicated that the novel assay was efficient enough to determine the ancestry origin of an unknown individual from the three continental populations. Besides, ancestry membership proportion estimations for the Mongolian group revealed that a large fraction of the ancestry was contributed by East Asian genetic component (approximately 83.9%), followed by European (approximately 12.6%) and African genetic components (approximately 3.5%), respectively. And next generation sequencing technology applied in this study offers possibility to incorporate more single nucleotide polymorphisms for individual identification and phenotype prediction into the same assay to provide as many as possible investigative clues in the future.

Indexed as

Genetics, PopulationHigh-Throughput Nucleotide SequencingAsia, EasternAsian PeopleBlack PeopleForensic AnthropologyForensic GeneticsGenotypeHumansMicrosatellite RepeatsPolymorphism, Single NucleotideRacial GroupsWhite PeopleAncestry inferenceMongolian groupSingle nucleotide polymorphismSTRUCTURE analysis

Identifiers

PMID32206883
OpenAlexW3012952682

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.