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Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers.

ABSTRACT: The inference of ancestry has become a part of the services many forensic genetic laboratories provide. Interest in ancestry may be to provide investigative leads or identify the region of origin in cases of unidentified missing persons. There exist many biostatistical methods developed for the study of population structure in the area of population genetics. However, the challenges and questions are slightly different in the context of forensic genetics, where the origin of a specific sample is of interest compared to the understanding of population histories and genealogies. In this paper, the methodologies for modelling population admixture and inferring ancestral populations are reviewed with a focus on their strengths and weaknesses in relation to ancestry inference in the forensic context.

SUBMITTER: Tvedebrink T

PROVIDER: S-EPMC8774801 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers.

Tvedebrink Torben T

Genes 20220114 1

The inference of ancestry has become a part of the services many forensic genetic laboratories provide. Interest in ancestry may be to provide investigative leads or identify the region of origin in cases of unidentified missing persons. There exist many biostatistical methods developed for the study of population structure in the area of population genetics. However, the challenges and questions are slightly different in the context of forensic genetics, where the origin of a specific sample is ...[more]

PMID: 35052480

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Project description:BackgroundGenetic ancestry, inferred from genomic data, is a quantifiable biological parameter. While much of the human genome is identical across populations, it is estimated that as much as 0.4% of the genome can differ due to ancestry. This variation is primarily characterized by single nucleotide variants (SNVs), which are often unique to specific genetic populations. Knowledge of a patient's genetic ancestry can inform clinical decisions, from genetic testing and health screenings to medication dosages, based on ancestral disease predispositions. Nevertheless, the current reliance on self-reported ancestry can introduce subjectivity and exacerbate health disparities. While genomic sequencing data enables objective determination of a patient's genetic ancestry, existing approaches are limited to ancestry inference at the continental level.ResultsTo address this challenge, and create an objective, measurable metric of genetic ancestry we present SNVstory, a method built upon three independent machine learning models for accurately inferring the sub-continental ancestry of individuals. We also introduce a novel method for simulating individual samples from aggregate allele frequencies from known populations. SNVstory includes a feature-importance scheme, unique among open-source ancestral tools, which allows the user to track the ancestral signal broadcast by a given gene or locus. We successfully evaluated SNVstory using a clinical exome sequencing dataset, comparing self-reported ethnicity and race to our inferred genetic ancestry, and demonstrate the capability of the algorithm to estimate ancestry from 36 different populations with high accuracy.ConclusionsSNVstory represents a significant advance in methods to assign genetic ancestry, opening the door to ancestry-informed care. SNVstory, an open-source model, is packaged as a Docker container for enhanced reliability and interoperability. It can be accessed from https://github.com/nch-igm/snvstory .

Project description:Assessment of phylogenetic relationships is an important component of any successful crop improvement programme, as wild relatives of the crop species often carry agronomically beneficial traits. Since its domestication in East Africa, Eleusine coracana (2n = 4x = 36), a species belonging to the genus Eleusine (x = 8, 9, 10), has held a prominent place in the semi-arid regions of India, Nepal and Africa. The patterns of variation between the cultivated and wild species reported so far and the interpretations based upon them have been considered primarily in terms of nuclear events. We analysed, for the first time, the phylogenetic relationship between finger millet (E. coracana) and its wild relatives by species-specific chloroplast deoxyribonucleic acid (cpDNA) polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and chloroplast simple sequence repeat (cpSSR) markers/sequences. Restriction fragment length polymorphism of the seven amplified chloroplast genes/intergenic spacers (trnK, psbD, psaA, trnH-trnK, trnL-trnF, 16S and trnS-psbC), nucleotide sequencing of the chloroplast trnK gene and chloroplast microsatellite polymorphism were analysed in all nine known species of Eleusine. The RFLP of all seven amplified chloroplast genes/intergenic spacers and trnK gene sequences in the diploid (2n = 16, 18, 20) and allotetraploid (2n = 36, 38) species resulted in well-resolved phylogenetic trees with high bootstrap values. Eleusine coracana, E. africana, E. tristachya, E. indica and E. kigeziensis did not show even a single change in restriction site. Eleusine intermedia and E. floccifolia were also shown to have identical cpDNA fragment patterns. The cpDNA diversity in Eleusine multiflora was found to be more extensive than that of the other eight species. The trnK gene sequence data complemented the results obtained by PCR-RFLP. The maternal lineage of all three allotetraploid species (AABB, AADD) was the same, with E. indica being the maternal diploid progenitor species. The markers specific to certain species were also identified.

Dataset Information

Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers.

Publications

Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers.

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