Inferring ethnicity using 15 autosomal STR loci—Comparisons among populations of similar and distinctly different physical traits

Graydon, Matthew; Cholette, François; Ng, Lay-Keow

doi:10.1016/j.fsigen.2009.03.002

Cited by 28 publications

(21 citation statements)

References 23 publications

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“…For people with records linked in this way, CODIS genotypes would reveal genomic SNP genotypes that could, in turn, reveal much more information than the CODIS genotypes themselves-such as precise ancestry estimates, health and identification information that accompanies SNP records, and predictions for genetically influenced phenotypes. In this sense, contrary to the view that CODIS genotypes expose no phenotypes (17,20,21), a CODIS profile on a person together with a SNP database-if the person is in the database-in principle may contain all of the phenotypic information that can be reliably predicted from the SNP record. Conversely, participants in biomedical research or personal genomics who have consented to share their SNP genotypes may be subject to a previously unappreciated risk: identification in a forensic STR database.…”

Section: Discussionmentioning

confidence: 91%

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Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets

Edge

Algee‐Hewitt

Pemberton

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Combining genotypes across datasets is central in facilitating advances in genetics. Data aggregation efforts often face the challenge of record matching-the identification of dataset entries that represent the same individual. We show that records can be matched across genotype datasets that have no shared markers based on linkage disequilibrium between loci appearing in different datasets. Using two datasets for the same 872 people-one with 642,563 genome-wide SNPs and the other with 13 short tandem repeats (STRs) used in forensic applications-we find that 90-98% of forensic STR records can be connected to corresponding SNP records and vice versa. Accuracy increases to 99-100% when ∼30 STRs are used. Our method expands the potential of data aggregation, but it also suggests privacy risks intrinsic in maintenance of databases containing even small numbers of markers-including databases of forensic significance.forensic DNA | genomic privacy | imputation | population genetics | record matching

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Section: Discussionmentioning

confidence: 91%

“…To test this premise, many investigations have examined phenotypic associations with the CODIS markers, mostly concluding that such associations are small enough to be unimportant (17,20,21). Record matching of CODIS and SNP data would make it possible to link a CODIS profile to a whole-genome SNP…”

mentioning

confidence: 99%

Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets

Edge

Algee‐Hewitt

Pemberton

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…Autosomal STRs are the markers of choice due to their highly polymorphic nature and significant potential for distinguishing individual identity 32 . These markers have also been used infer the ancestry of profiles 54, 60–62 . The accuracy of assignment depends on marker efficiency and the number of markers.…”

Section: Resultsmentioning

confidence: 99%

Genetic variation and population structure of Botswana populations as identified with AmpFLSTR Identifiler short tandem repeat (STR) loci

Tau

Wally²,

Fanie³

et al. 2017

Sci Rep

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Population structure was investigated in 990 Botswana individuals according to ethno-linguistics, Bantu and Khoisan, and geography (the nine administrative districts) using the Identifiler autosomal microsatellite markers. Genetic diversity and forensic parameters were calculated for the overall population, and according to ethno-linguistics and geography. The overall combined power of exclusion (CPE) was 0.9999965412 and the combined match probability 6,28 × 10−19. CPE was highest for the Khoisan Tuu ethnolinguistic group and the Northeast District at 0.9999582029 and 0.9999922652 respectively. CMP ranged from 6.28 × 10−19 (Khoisan Tuu) to 1,02 × 10−18 (Northwest district). Using pairwise genetic distances (FST), analysis of molecular variance (AMOVA), factorial correspondence analysis (FCA), and the unsupervised Bayesian clustering method found in STRUCTURE and TESS, ethno-linguistics were found to have a greater influence on population structure than geography. FCA showed clustering between Bantu and Khoisan, and within the Bantu. This Bantu sub-structuring was not seen with STRUCTURE and TESS, which detected clustering only between Bantu and Khoisan. The patterns of population structure revealed highlight the need for regional reference databases that include ethno-linguistic and geographic location information. These markers have important potential for bio-anthropological studies as well as for forensic applications.

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“…Su elevada tasa de mutación promueve la estabilización de las frecuencias alélicas entre poblaciones [13]. Además, se han observado grandes diferencias en la estimación del origen biogeográfico según el grupo ancestral [15].…”

Section: Marcadores Informativos De Ancestralidad (Aim)unclassified

Revisión sobre los marcadores del origen biogeográfico y su aplicación en la investigación forense

Popa¹,

Pardo²,

López-Parra³

2017

Colomb. forense

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Cómo citar este artículo: Popa DM, Arroyo-Pardo E, López-Parra AM. Revisión sobre los marcadores del origen biogeográfico y su aplicación en la investigación forense. Colomb Forense. 2016;4(1):15-26. doi: http://dx.doi.org/10. 16925/cf.v4i1.1958 Resumen. Propósito: actualmente, los marcadores que determinan el origen biogeográfico están teniendo mucho auge, especialmente en el ámbito forense. Estos marcadores permiten analizar el adn de un individuo y determinar su origen biogeográfico. Estos análisis se llevan a cabo con frecuencia a través de snp (Single Nucleotide Polymorphisms), pero más recientemente también a través de InDels. Debido a este auge, la finalidad de la revisión es recopilar información sobre los marcadores que actualmente se están utilizando, su diferente rendimiento y su problemática, así como las posibles soluciones. Periodo que se abarcó, origen y tipos de publicaciones: el periodo abarcado para el análisis es del año 2006 al 2016, con artículos recopilados de PubMed y Web of Science, sin ninguna preferencia en cuanto al origen. Punto de vista: aunque se han empleado para diferentes poblaciones y con diferentes marcadores, muestran resultados similares. Los artículos versan desde los tipos de marcadores seleccionados para el análisis, como marcadores autosómicos o de linaje, hasta comparaciones entre marcadores de la misma categoría, como los snp y los InDels entre los autosómicos. Se han seleccionado así para poder obtener una visión comparativa de los más eficaces para la detección del origen biogeográfico. Conclusiones: se ha comprobado que los más marcadores eficaces son los aim-snp autosómicos, en cuanto a diferenciación entre grupos poblacionales, y los aim-InDels, de forma suplementaria en los casos de mezcla poblacional.Palabras clave: InDels, origen biogeográfico, snp, str.

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Inferring ethnicity using 15 autosomal STR loci—Comparisons among populations of similar and distinctly different physical traits

Cited by 28 publications

References 23 publications

Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets

Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets

Genetic variation and population structure of Botswana populations as identified with AmpFLSTR Identifiler short tandem repeat (STR) loci

Revisión sobre los marcadores del origen biogeográfico y su aplicación en la investigación forense

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