Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND).

Background The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample. Results A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy. Conclusions The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2654-x) contains supplementary material, which is available to authorized users.

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PID https://www.doi.org/10.1186/s12864-016-2654-x
PID pmc:PMC4855449
PID pmid:27142425
URL https://dx.doi.org/10.1186/s12864-016-2654-x
URL https://bmcgenomics.biomedcentral.com/track/pdf/10.1186/s12864-016-2654-x
URL https://academic.microsoft.com/#/detail/2346312249
URL http://europepmc.org/abstract/MED/27142425
URL https://jhu.pure.elsevier.com/en/publications/selecting-snps-informative-for-african-american-indian-and-europe
URL https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-2654-x
URL https://link.springer.com/article/10.1186/s12864-016-2654-x
URL https://www.ncbi.nlm.nih.gov/pubmed/27142425
URL http://europepmc.org/articles/PMC4855449
URL https://moh-it.pure.elsevier.com/en/publications/selecting-snps-informative-for-african-american-indian-and-europe
URL http://link.springer.com/content/pdf/10.1186/s12864-016-2654-x.pdf
URL https://ucdavis.pure.elsevier.com/en/publications/selecting-snps-informative-for-african-american-indian-and-europe
URL https://paperity.org/p/76186982/selecting-snps-informative-for-african-american-indian-and-european-ancestry-application
URL http://www.ncbi.nlm.nih.gov/pubmed/27142425
URL https://figshare.com/collections/Selecting_SNPs_informative_for_African_American_Indian_and_European_Ancestry_application_to_the_Family_Investigation_of_Nephropathy_and_Diabetes_FIND_/3608633
URL http://link.springer.com/article/10.1186/s12864-016-2654-x/fulltext.html
URL http://link.springer.com/content/pdf/10.1186/s12864-016-2654-x
URL https://escholarship.org/uc/item/75f580zv
URL http://dx.doi.org/10.1186/s12864-016-2654-x
URL https://scholars.uthscsa.edu/en/publications/selecting-snps-informative-for-african-american-indian-and-europe
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Author Rebekah Rasooly, 0000-0002-6357-5528
Author Marina Scavini, 0000-0002-7983-6905
Author Sudha Iyengar, 0000-0001-7488-250X
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Collected From Europe PubMed Central; PubMed Central; eScholarship - University of California; ORCID; Datacite; UnpayWall; Crossref; Microsoft Academic Graph; CORE (RIOXX-UK Aggregator)
Hosted By Europe PubMed Central; SpringerOpen; eScholarship - University of California; BMC Genomics
Publication Date 2016-05-04
Publisher eScholarship, University of California
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::28396ebf7beff33b77c8694e945a6bb8
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Last Updated 24 December 2020, 14:52 (CET)
Created 24 December 2020, 14:52 (CET)