2019
DOI: 10.7717/peerj.6861
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Genetic variation and forensic efficiency of 30 indels for three ethnic groups in Guangxi: relationships with other populations

Abstract: Aim In this study, we used a series of diallelic genetic marker insertion/deletion polymorphism (indel) to investigate three populations of Yao, Kelao, and Zhuang groups in the Guangxi region of China and to evaluate their efficiency in forensic application. Result No deviations for all 30 loci were observed from the Hardy–Weinberg equilibrium after Bonferroni correction (p > 0.05/30 = 0.0017). The allele frequencies of the short allele (DIP-) for the above three populations were in the range of 0.0520–0.… Show more

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Cited by 9 publications
(3 citation statements)
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“…The insertion allele frequency differences between loci are huge, which are even more than one order of magnitude. We observed the same results from other East Asian populations (Du et al, 2019;He et al, 2019a,b). On the contrary, the allele frequency distribution is relatively balanced in European and American populations (Kis et al, 2012;Saiz et al, 2014), indicating that the panel of 30 InDels is informative for population substructure dissection and ancestral information inference at the continental level.…”
Section: Linkage Disequilibrium Forensic Parameters and Allele Freqsupporting
confidence: 92%
“…The insertion allele frequency differences between loci are huge, which are even more than one order of magnitude. We observed the same results from other East Asian populations (Du et al, 2019;He et al, 2019a,b). On the contrary, the allele frequency distribution is relatively balanced in European and American populations (Kis et al, 2012;Saiz et al, 2014), indicating that the panel of 30 InDels is informative for population substructure dissection and ancestral information inference at the continental level.…”
Section: Linkage Disequilibrium Forensic Parameters and Allele Freqsupporting
confidence: 92%
“…All the allelic frequency data of 30 InDel markers from 100 populations, including African, (Northern and Southern) American, European, and Asian, were collected as the dataset f. Since the genotype data could not be found in some populations in their reports, we sorted out the genotype data from 52 populations as the dataset g, including an African, 3 European, 7 American, 41 Asian populations, and Guizhou Sui (Fondevila et al, 2012;Friis et al, 2012;Kis et al, 2012;Larue et al, 2012;Akhteruzzaman et al, 2013;Carvalho and Pinheiro, 2013;da silva et al, 2013;Martin et al, 2013;Kim et al, 2014;Ferreira Palha et al, 2015;Hefke et al, 2015;Meng et al, 2015;Guo et al, 2016Guo et al, , 2018Martinez-Cortes et al, 2016;Mei et al, 2016;Du et al, 2017Du et al, , 2019Kong et al, 2017;Li et al, 2018Li et al, , 2019Ma et al, 2018;Chen et al, 2019;He et al, 2019a,c;Jian et al, 2019;Liu Y. et al, 2020). The genome-wide SNP data of the Sui population were merged with the reference dataset including 1240 k, Human Origin, and so on (Patterson et al, 2012;Lipson et al, 2018;Mccoll et al, 2018;Liu D. et al, 2020;Ning et al, 2020;Yang et al, 2020;Wang C. C. et al, 2021) to generate two combined datasets covering 189,177 and 71,989 SNPs for subsequent analyses.…”
Section: Reference Datasets and Data Mergingmentioning
confidence: 99%
“…Hence, InDels are considered to be ideal forensic markers and have attracted attentions from forensic researchers worldwide ( Sheng et al, 2018 ). InDels have been increasingly explored and used in forensic genetics and biogeographical ancestry inferences, and much more extensive forensic and population genetic studies are ongoing ( Bastos-Rodrigues et al, 2006 ; Larue et al, 2014 ; Du et al, 2019 ; He et al, 2019 ).…”
Section: Introductionmentioning
confidence: 99%