Journal ArticleDOI
Selection of highly informative SNP markers for population affiliation of major US populations
Xiangpei Zeng,Ranajit Chakraborty,Jonathan L. King,Bobby LaRue,Rodrigo S. Moura-Neto,Rodrigo S. Moura-Neto,Bruce Budowle,Bruce Budowle +7 more
TLDR
The results showed that the FST panel performed slightly better for population resolution based on principal component analysis (PCA) clustering than did the δ panel and both performed better than the In panel, and indicated that individuals could be correctly assigned to the major population categories.Abstract:
Ancestry informative markers (AIMs) can be used to detect and adjust for population stratification and predict the ancestry of the source of an evidence sample. Autosomal single nucleotide polymorphisms (SNPs) are the best candidates for AIMs. It is essential to identify the most informative AIM SNPs across relevant populations. Several informativeness measures for ancestry estimation have been used for AIMs selection: absolute allele frequency differences (δ), F statistics (F ST), and informativeness for assignment measure (In). However, their efficacy has not been compared objectively, particularly for determining affiliations of major US populations. In this study, these three measures were directly compared for AIMs selection among four major US populations, i.e., African American, Caucasian, East Asian, and Hispanic American. The results showed that the F ST panel performed slightly better for population resolution based on principal component analysis (PCA) clustering than did the δ panel and both performed better than the In panel. Therefore, the 23 AIMs selected by the F ST measure were used to characterize the four major American populations. Genotype data of nine sample populations were used to evaluate the efficiency of the 23-AIMs panel. The results indicated that individuals could be correctly assigned to the major population categories. Our AIMs panel could contribute to the candidate pool of AIMs for potential forensic identification purposes.read more
Citations
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Journal ArticleDOI
Diversity in the breadfruit complex ( Artocarpus , Moraceae): genetic characterization of critical germplasm
Nyree J. C. Zerega,Tyr Wiesner-Hanks,Diane Ragone,Brian M. Irish,Brian E. Scheffler,Sheron A. Simpson,Francis Zee +6 more
TL;DR: Microsatellite markers were found to be more informative than isozyme markers and slightly less informative, with regard to accession discrimination, than AFLP markers.
Journal ArticleDOI
Breast Cancer Disparities. High-Risk Breast Cancer and African Ancestry
TL;DR: Questions are raised regarding an association between African ancestry and inherited susceptibility for certain patterns of mammary carcinogenesis among women from western, sub-Saharan Africa who share ancestry with African Americans.
Journal ArticleDOI
Forensic human identification with targeted microbiome markers using nearest neighbor classification.
August E. Woerner,Nicole M.M. Novroski,Frank R. Wendt,Angie Ambers,Rachel Wiley,Sarah E. Schmedes,Bruce Budowle +6 more
TL;DR: The findings suggest that microbial strain composition is more individualized than that of a phylogeny, perhaps indicating that microbial composition may be more individualizing than recent common ancestry.
Journal ArticleDOI
MAPlex - A massively parallel sequencing ancestry analysis multiplex for Asia-Pacific populations
Christopher Phillips,Dennis McNevin,Kenneth K. Kidd,Robert Lagacé,Sharon Wootton,M. de la Puente,Ana Freire-Aradas,Ana Mosquera-Miguel,Mayra Eduardoff,Theresa E. Gross,L. Dagostino,D. Power,S. Olson,Masaki Hashiyada,C. Oz,Walther Parson,Peter M. Schneider,Maria Victoria Lareu,Runa Daniel +18 more
TL;DR: Preliminary assessment of MAPlex indicates enhanced South Asian differentiation with increased divergence between West Eurasian, South Asian and East Asian populations, compared to previous forensic SNP panels of comparable scale.
Journal ArticleDOI
Consequences of PCA graphs, SNP codings, and PCA variants for elucidating population structure
TL;DR: The main three recommendations are simple and easily implemented: Use PCA biplots, SNP coding 1 for the rare allele and 0 for the common allele, and double-centered PCA (or AMMI1 if main effects are also of interest).
References
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TL;DR: The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance the ability to choose targets for therapeutic intervention.
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