Optimizing Multiplex PCR for a Set of Malay Ancestry Informative Marker-Single Nucleotide Polymorphisms (AIM-SNPs) and Preliminary Analysis of Genotypes Between Malay and non-Malay Population.

Background: Inference of genetic ancestry is of great interest in many fields and one of the markers in these analyses is ancestry informative marker single nucleotide polymorphisms (AIMSNPs). The Malay population is an ethnic group located mainly in South East Asia and comprises the largest ethnicity in Malaysia. Objectives: To determine Malay ancestry, Yahya et al, 2017 selected 37,487 SNPs from the genotyping data collected by the Malaysian Node of the Human Variome Project and Singapore Genome Variation Project and referenced them against the data from the International HapMap Project Phase 3. The SNPs determined to be informative for ancestry were compiled into AIM-SNP panels, and from these a few SNPs were selected for optimization in preparation for single base extension reaction multiplexing. Methodology: The chosen AIMSNPs were optimized and validated on Malay and non-Malay populations. Genotyping was carried out on participants of self-reported Malay and non-Malay ancestry respectively and the data were compared for Malay and non-Malay population to investigate for significant differences in the genotype between Malay and non-Malay participants. Findings: The results showed great similarities between the Malay and non-Malay population, which may arise from many factors, and further optimization of more SNPs and genotyping is required to definitively conclude the validity of the AIM-SNP panels for Malay population Conclusion: Knowledge of ancestry is important to minimise spurious association. This pilot study gives a brief account of the optimization process and offers an insight into how this may be done in South East Asian populations.

Genetic Structural Differentiation Analyses of Intercontinental Populations and Ancestry Inference of the Chinese Hui Group Based on a Novel Developed Autosomal AIM-InDel Genotyping System

In the present study, we investigated the genetic polymorphisms of 39 ancestry informative marker-insertion/deletion (AIM-InDel) loci in the Chinese Hui group using a previously self-developed panel, further clarified the genetic relationships between the Hui group and other reference populations, and assessed the ancestry inference efficiency of the AIM-InDel panel based on the worldwide population data from 1000 Genomes Phase 3. The results of the locus-specific informativeness (In) and pairwise fixation index (Fst) values, multidimensional scaling analysis, and success ratio of estimation with cross-validation showed that the novel panel could well reveal the genetic structural differentiations of the East Asian, European, African, and South Asian populations. Besides, the biogeographical ancestry origin inference both at the individual and population levels was conducted on the Chinese Hui group by principal component analysis and STRUCTURE analysis, and the results revealed that the Hui group had the East Asian origin, and the East Asian component ratio of Hui group was approximately 88.87%. Furthermore, the population genetic analyses among the Hui group and reference populations were performed based on the insertion allele frequency heat map, population pairwise Fst values and phylogenetic tree, and the results indicated that the Hui group was genetically closer to East Asian populations, especially two Chinese Han populations (CHS and CHB populations).

Identification of Ancestry Informative Marker (AIM) Panels to Assess Hybridisation between Feral and Domestic Sheep

Hybridisation of wild populations with their domestic counterparts can lead to the loss of wildtype genetic integrity, outbreeding depression, and loss of adaptive features. The Mediterranean island of Sardinia hosts one of the last extant autochthonous European mouflon (Ovis aries musimon) populations. Although conservation policies, including reintroduction plans, have been enforced to preserve Sardinian mouflon, crossbreeding with domestic sheep has been documented. We identified panels of single nucleotide polymorphisms (SNPs) that could act as ancestry informative markers able to assess admixture in feral x domestic sheep hybrids. The medium-density SNP array genotyping data of Sardinian mouflon and domestic sheep (O. aries aries) showing pure ancestry were used as references. We applied a two-step selection algorithm to this data consisting of preselection via Principal Component Analysis followed by a supervised machine learning classification method based on random forest to develop SNP panels of various sizes. We generated ancestry informative marker (AIM) panels and tested their ability to assess admixture in mouflon x domestic sheep hybrids both in simulated and real populations of known ancestry proportions. All the AIM panels recorded high correlations with the ancestry proportion computed using the full medium-density SNP array. The AIM panels proposed here may be used by conservation practitioners as diagnostic tools to exclude hybrids from reintroduction plans and improve conservation strategies for mouflon populations.

An ancestry informative marker panel design for individual ancestry estimation of Hispanic population using whole exome sequencing data

Background Europeans and American Indians were major genetic ancestry of Hispanics in the U.S. These ancestral groups have markedly different incidence rates and outcomes in many types of cancers. Therefore, the genetic admixture may cause biased genetic association study with cancer susceptibility variants specifically in Hispanics. For example, the incidence rate of liver cancer has been shown with substantial disparity between Hispanic, Asian and non-Hispanic white populations. Currently, ancestry informative marker (AIM) panels have been widely utilized with up to a few hundred ancestry-informative single nucleotide polymorphisms (SNPs) to infer ancestry admixture. Notably, current available AIMs are predominantly located in intron and intergenic regions, while the whole exome sequencing (WES) protocols commonly used in translational research and clinical practice do not cover these markers. Thus, it remains challenging to accurately determine a patient’s admixture proportion without additional DNA testing. Results In this study we designed an unique AIM panel that infers 3-way genetic admixture from three distinct and selective continental populations (African (AFR), European (EUR), and East Asian (EAS)) within evolutionarily conserved exonic regions. Initially, about 1 million exonic SNPs from selective three populations in the 1000 Genomes Project were trimmed by their linkage disequilibrium (LD), restricted to biallelic variants, and finally we optimized to an AIM panel with 250 SNP markers, or the UT-AIM250 panel, using their ancestral informativeness statistics. Comparing to published AIM panels, UT-AIM250 performed better accuracy when we tested with three ancestral populations (accuracy: 0.995 ± 0.012 for AFR, 0.997 ± 0.007 for EUR, and 0.994 ± 0.012 for EAS). We further demonstrated the performance of the UT-AIM250 panel to admixed American (AMR) samples of the 1000 Genomes Project and obtained similar results (AFR, 0.085 ± 0.098; EUR, 0.665 ± 0.182; and EAS, 0.250 ± 0.205) to previously published AIM panels (Phillips-AIM34: AFR, 0.096 ± 0.127, EUR, 0.575 ± 0.290, and EAS, 0.330 ± 0.315; Wei-AIM278: AFR, 0.070 ± 0.096, EUR, 0.537 ± 0.267, and EAS, 0.393 ± 0.300). Subsequently, we applied the UT-AIM250 panel to a clinical dataset of 26 self-reported Hispanic patients in South Texas with hepatocellular carcinoma (HCC). We estimated the admixture proportions using WES data of adjacent non-cancer liver tissues (AFR, 0.065 ± 0.043; EUR, 0.594 ± 0.150; and EAS, 0.341 ± 0.160). Similar admixture proportions were identified from corresponding tumor tissues. In addition, we estimated admixture proportions of The Cancer Genome Atlas (TCGA) collection of hepatocellular carcinoma (TCGA-LIHC) samples (376 patients) using the UT-AIM250 panel. The panel obtained consistent admixture proportions from tumor and matched normal tissues, identified 3 possible incorrectly reported race/ethnicity, and/or provided race/ethnicity determination if necessary. Conclusions Here we demonstrated the feasibility of using evolutionarily conserved exonic regions to infer admixture proportions and provided a robust and reliable control for sample collection or patient stratification for genetic analysis. R implementation of UT-AIM250 is available at https://github.com/chenlabgccri/UT-AIM250.

Polymorphisms of xenobiotic-metabolizing and transporter genes and the risk of gastric and colorectal cancer in an admixed population of Brazil.

Introduction Colorectal (CRC) and Gastric (GC) cancers are responsible for considerable morbidity and mortality worldwide. In the North region of Brazil, these neoplasms are among the three most incident and aggressive types of cancer, constituting a severe problem of public health. Single Nucleotide Polymorphisms (SNPs) of xenobiotic metabolism and transporter genes may play a role in individual response to exposure to some of the compounds implicated in the cancer susceptibility. However, few studies have demonstrated the role of polymorphisms of xenobiotic metabolism and transporter genes in the susceptibility to CRC or GC in admixed populations. In this context, the study of variation in the activation and detoxification processes of xenobiotics may help to clarify the development of either GC or CRC in substructured populations, providing new insights about predictive diagnostic criteria in oncological investigations. MethodsWe performed an association study using 31 SNPs in 15 xenobiotic metabolism and transporter genes. The study was carried out in 121 CRC and 95 GC cases and 140 control individuals from Belém, a city which comprises a population with high levels of miscegenation, located in the Brazilian Amazon. Samples were genotyped using the QuantStudio™12K Flex Real-Time PCR System. Due to the high level of genetic admixture in the studied population, we applied a panel of 61 Ancestry Informative Marker standardized by our research group in an earlier study. Statistical analyses were performed in SPSS v.20.0 and Structure v.2.3.4ResultsThe results revealed a significant association between the increased CRC or GC risk and polymorphisms of ABCG2 (rs2231142) and DPYD genes (rs17116806, rs1801159). ConclusionsOur data suggest that polymorphisms in xenobiotic-metabolizing and transporter genes may be relevant to the susceptibility to both CRC and GC.

Feature Extraction And Classification On Single Nucleotide Polymorphism

Malay in Peninsular Malaysia can be divided into eight sub-ethnics which are Malay Bugis, Malay, Malay Champa, Malay Jawa, Malay Kelantan, Malay Kedah, Malay Minang and Malay Pattani. Ancestry informative marker (AIM) can be used to represent the eight subethnic of Malay population in Peninsular Malaysia. In this research, single nucleotide polymorphism (SNP) datasets of eight sub-ethnics are analyses in order to obtain the AIM for Malays population in Peninsular Malaysia. However, the dataset may have outlier, missing data and redundancy that may impact the accuracy of the result. Pre-processing data is an important step that will remove the entire problem. Iterative pruning principal component analysis (ipPCA) is one of the techniques that usually use in analysis on genome datasets to extract the information. It can be applied on the high structured data and can improve the resolution of the data. It also used for structure a sub-population. Random Forest and Hidden Naïve Bayes is used to classify the SNP that can be used as AIM. Information Gain Ratio will rank the chosen AIM based on the value of each attribute