Fast and accurate kinship estimation using sparse SNPs in relatively large database searches. (November 2022)

• Record Type: Journal Article
• Authors: Snedecor, June; Fennell, Tim; Stadick, Seth; Homer, Nils; Antunes, Joana; Stephens, Kathryn; Holt, Cydne
• Is Part Of: Forensic science international. Volume 61(2022)
• Publication Date: 2022-11
• Subjects: Forensic genetic genealogy -- Investigative genetic genealogy -- GEDmatch -- ForenSeq Kintelligence -- Extended kinship -- Windowed kinship algorithm -- PCR-based FGG profiles; Forensic genetics -- Periodicals; Génétique légale -- Périodiques; Forensic genetics; Electronic journals; Periodicals; 614.1
• DOI: 10.1016/j.fsigen.2022.102769
• Languages: English
• ISSNs: 1872-4973

Abstract

Abstract: Forensic genetic genealogy (FGG) has primarily relied upon dense single nucleotide polymorphism (SNP) profiles from forensic samples or unidentified human remains queried against online genealogy database(s) of known profiles generated with SNP microarrays or from whole genome sequencing (WGS). In these queries, SNPs are compared to database samples by locating contiguous stretches of shared SNP alleles that allow for detection of genomic segments that are identical by descent (IBD) among biological relatives (kinship). This segment-based approach, while robust for detecting distant relationships, generally requires DNA quantity and/or quality that are sometimes not available in forensic casework samples. By focusing on SNPs with maximal discriminatory power and using an algorithm designed for a sparser SNP set than those from microarray typing, performance similar to segment matching was reached even in difficult casework samples. This algorithm locates shared segments using kinship coefficients in "windows" across the genome. The windowed kinship algorithm is a modification of the PC-AiR and PC-Relate tools for genetic relatedness inference, referred to here as the "whole genome kinship" approach, that control for the presence of unknown or unspecified population substructure. Simulated and empirical data in this study, using DNA profiles comprised of 10, 230 SNPs (10K multiplex) targeted by the ForenSeq™ Kintelligence Kit demonstrate that the windowed kinship approach performs comparably to segment matching for identifying first, second and third degree relationships, reasonably well for fourth degree relationships, and with fewer false kinship associations. Selection criteria for the 10K SNP PCR-based multiplex and functionality of the windowed kinship algorithm are described. Highlights: Robust associations for forensic genetic genealogy are found using sparse SNP panels. Degraded samples can be processed using limited panel to identify relatives. Novel kinship method provides accurate results out to fourth degree relatives with sparse SNPs (down to 10 K)