A targeted ancestry informative InDels panel on capillary electrophoresis for ancestry inference in Asian populations

Abstract

CE is the primary methodology used in forensic DNA typing. Alleles of commonly used types of genetic markers could be separated and detected via CE based on dye color and migration time. Insertion/deletion (InDel) is an ideal genetic marker for forensic DNA analysis due to their abundance in the human genome, low mutation rate, availability of their allele types via CE, and elimination of stutter peaks. Moreover, InDels could be used as ancestry informative markers since allele frequencies of InDels is different among geographically separated populations. Several ancestry informative insertion/deletion panels have been established based on CE platform to achieve the intercontinental populations distinction. However, improvements to differentiate intracontinental populations is few. In this study, 21 InDels with fixation index (FST) > 0.15 were selected and assembled into one ancestry informative insertion/deletion panel. Using well‐designed primers, those 21 InDels could be amplified successfully and genotyped on the CE platform accurately and completely. The panel showed a large FST distance distinction among the ten Asian populations. Using clustering analysis, ten Asian populations were classified into three subgroups: East Asian, Southeast Asian, and South Asian subgroups. To evaluate the panel's capability in ancestry inference, a validation experiment was undertaken with 319 individuals from four geographically separated populations in China. Four Chinese populations were classified into different ancestry subgroups and 81.8% test individuals’ ancestry could be inferred correctly. Our result showed that development of high ancestry informative InDels panel based on CE platform is a potential for individual ancestry inference among intracontinental populations.

An efficient ancestry informative SNPs panel for further discriminating East Asian populations

“…However, the classification accuracy of DAI in SEA is only 53%, of which 46% is assigned as EA_C. The admixture pattern of DAI is also reported in the study of Zhu et al [3], the possible reason for which is that Dai in Kunming is more likely to intermarry with Han Chinese than Dai in Xishuangbanna.…”

“…Currently, AIMs include single-nucleotide polymorphisms (SNPs), short tandem repeats, insertion/deletion polymorphisms, and microhaplotypes [1][2][3][4]. Among them, SNPs are becoming more and more important because of their wide distribution, relatively low mutation rate, and simplicity of analysis [5][6][7].…”

“…Among them, SNPs are becoming more and more important because of their wide distribution, relatively low mutation rate, and simplicity of analysis [5][6][7]. Among the previous AIMs, some, called first-tier global panels, have proven very useful in distinguishing continental populations [8][9][10], whereas others, referred to as second-tier ancestry panels, enable fine-grained discrimination of populations within continental regions [2,3,7,11].…”

Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field

“…After an initial PCA analysis with the Asian continent in its entirety, the Asian was subdivided into its regions due to its breadth -within our dataset, individuals were belonging to different regions of Asia- and the fact that the prediction of the biogeographical origin within the Asian continent has been and is a subject extensively studied in the forensic field 25 , 72 – 76 .…”

“…The best way to assign an individual into a particular population via genetic testing is to use ancestry informative markers (AIMs) –markers characterized by essential differences in allele frequencies between populations 3 – 5 . As proposed by several studies (for example 6 – 25 ), short tandem repeats (STRs), single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (InDels), and microhaplotypes can be used as AIMs for ancestry inference. However, autosomal single nucleotide polymorphisms are the best choices due to their inherent stability, high density of genome-wide distribution, and pronounced frequency variation among populations.…”