Dataset Information

Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations.

ABSTRACT: The knowledge of ancestral origin is monumental in conservation of endangered animals since it can aid in preservation of population level genetic integrity and prevent inbreeding among related individuals. Despite maintenance of studbook, the biogeographical affiliation of most captive gorillas is largely unknown, which has constrained management of captive gorillas aiming at maximizing genetic diversity at the population level. In recent years, ancestry informative markers (AIMs) has been successfully employed for the inference of genomic ancestry in a wide range of studies in evolutionary genetics, biomedical research, genetic stock identification, and introgression analysis and forensic analyses. In this study, we sought to derive the AIMs yielding the most cohesive and faithful understanding of biogeographical affiliation of query gorillas. To this end, we compared three commonly used AIMs-determining methods namely, Infocalc, F ST , and Smart Principal Component Analysis (SmartPCA) with ADMIXTURE, using gorilla genome data available through Great Ape Genome Project database. Our findings suggest that the SNPs that were detected by at least three of the four AIMs-determining approaches (N = 1,531), is likely most suitable for delineation of gorilla AIMs. It recapitulated the finer structure within western lowland gorilla genomes with high degree of precision. We further have validated the robustness of our results using a randomized negative control containing the same number of SNPs. To the best of our knowledge, this is the first report of an AIMs panel for gorillas that may aid in developing cost-effective resources for large-scale demographic analyses, and greatly help in conservation of this charismatic mega-fauna.

SUBMITTER: Das R

PROVIDER: S-EPMC6375890 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations.

Das Ranajit R Roy Ria R Venkatesh Neha N

Frontiers in genetics 20190208

The knowledge of ancestral origin is monumental in conservation of endangered animals since it can aid in preservation of population level genetic integrity and prevent inbreeding among related individuals. Despite maintenance of studbook, the biogeographical affiliation of most captive gorillas is largely unknown, which has constrained management of captive gorillas aiming at maximizing genetic diversity at the population level. In recent years, ancestry informative markers (AIMs) has been succ ...[more]

PMID: 30800141

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Project description:Introduction: Human populations are often highly structured due to differences in genetic ancestry among groups, posing difficulties in associating genes with diseases. Ancestry-informative markers (AIMs) aid in the detection of population stratification and provide an alternative approach to map population-specific alleles to disease. Here, we identify and characterize a novel set of African AIMs that separate populations of African ancestry from other global populations including those of European ancestry. Methods: Using data from the 1000 Genomes Project, highly informative SNP markers from five African subpopulations were selected based on estimates of informativeness (In) and compared against the European population to generate a final set of 46,737 African ancestry-informative markers (AIMs). The AIMs identified were validated using an independent set and functionally annotated using tools like SIFT, PolyPhen. They were also investigated for representation of commonly used SNP arrays. Results: This set of African AIMs effectively separates populations of African ancestry from other global populations and further identifies substructure between populations of African ancestry. When a subset of these AIMs was studied in an independent dataset, they differentiated people who self-identify as African American or Black from those who identify their ancestry as primarily European. Most of the AIMs were found to be in their intergenic and intronic regions with only 0.6% in the coding regions of the genome. Most of the commonly used SNP array investigated contained less than 10% of the AIMs. Discussion: While several functional annotations of both coding and non-coding African AIMs are supported by the literature and linked these high-frequency African alleles to diseases in African populations, more effort is needed to map genes to diseases in these genetically diverse subpopulations. The relative dearth of these African AIMs on current genotyping platforms (the array with the highest fraction, llumina's Omni 5, harbors less than a quarter of AIMs), further demonstrates a greater need to better represent historically understudied populations.

Project description:BACKGROUND:Recent work has shown that population stratification can have confounding effects on genetic association studies and statistical methods have been developed to correct for these effects. Subsets of markers that are highly-differentiated between populations, ancestry-informative markers (AIMs), have been used to correct for population stratification. Often AIMs are discovered in one set of populations and then employed in a different set of populations. The underlying assumption in these cases is that the population under study has the same substructure as the population in which the AIMs were discovered. The present study assesses this assumption and evaluates the portability between worldwide populations of 10 SNPs found to be highly-differentiated within Britain (BritAIMs). METHODS:We genotyped 10 BritAIMs in approximately 1000 individuals from 53 populations worldwide. We assessed the degree to which these 10 BritAIMs capture population stratification in other groups of populations by use of the Fst statistic. We used Fst values from 2750 random markers typed in the same set of individuals as an empirical distribution to which the Fst values of the 10 BritAIMs were compared. RESULTS:Allele frequency differences between continental groups for the BritAIMs are not unusually high. This is also the case for comparisons within continental groups distantly related to Britain. However, two BritAIMs show high Fst between European populations and two BritAIMs show high Fst between populations from the Middle East. Overall the median Fst across all BritAIMs is not unusually high compared to the empirical distribution. CONCLUSION:We find that BritAIMs are generally not useful to distinguish between continental groups or within continental groups distantly related to Britain. Moreover, our analyses suggest that the portability of AIMs across geographical scales (e.g. between Europe and Britain) can be limited and should therefore be taken into consideration in the design and interpretation of genetic association studies.

Dataset Information

Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations.

Publications

Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations.

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