Abstract:Kinship analysis from very low-coverage ancient sequences has been possible up to the second degree with large uncertainties. We propose a new, accurate, and fast method, correctKin, to estimate the kinship coefficient and the confidence interval using low-coverage ancient data. We perform simulations and also validate correctKin on experimental modern and ancient data with widely different genome coverages (0.12×–11.9×) using samples with known family relations and known/unknown population structure. Based on… Show more
“…To investigate the kinship relationships between individuals, we utilized the kinship analysis developed by Nyerki et al. 2023, 51 which has been shown to reliably identify relatedness up to the 4th degree from low coverage genome data. We performed the kinship analysis using the 1240K dataset and the PCAngsd software (version 0.99) from the ANGSD package, 35 with the “-inbreed 1 -kinship” options.…”
“…To investigate the kinship relationships between individuals, we utilized the kinship analysis developed by Nyerki et al. 2023, 51 which has been shown to reliably identify relatedness up to the 4th degree from low coverage genome data. We performed the kinship analysis using the 1240K dataset and the PCAngsd software (version 0.99) from the ANGSD package, 35 with the “-inbreed 1 -kinship” options.…”
“…In particular, many ancient DNA kinship estimation methods currently address the challenge of inferring kinship from low coverage samples either (i) by computing P(IBD) from genotype likelihoods, to account for the inherent uncertainty of the available genotype calls [7,8], or (ii) by estimating the average pairwise mismatch rate (PMR), usually from randomly sampled pseudohaploid genotypes, and subsequently normalizing these results across all available pairwise comparisons [9,10,11,12]. Despite promising advances in recent years [12,13,14], the current state-ofthe-art regarding the assessment of genetic relatedness from ancient DNA still faces multiple challenges, which most of the currently available methods fail to fully address. On the one hand, maximum likelihood methods such as lcMLkin [7] and NgsRelate-v2 [8] are able to provide precise estimates of kinship well beyond the second degree.…”
Section: State Of the Art And Current Challenges Of Ancient Dna Kinsh...mentioning
confidence: 99%
“…Finally, most ancient DNA kinship estimation methods fail to explicitly account for the presence of modern contamination, sequencing errors, and/or the presence of recent inbreeding amongst studied individuals (KIN and NgsRelate-v2 being notable exceptions). Thus, accurately estimating more distant genetic ties between low-coverage samples, while accounting for the inherent biases of ancient DNA, often remains in practice -despite the promising recent proposals of the KIN [12] and correctKIN [14] methods -an arduous prospect, as evidenced by the fact that several methods explicitly refrain from venturing beyond the second degree of relatedness [11,13].…”
Section: State Of the Art And Current Challenges Of Ancient Dna Kinsh...mentioning
Background: The study of fine-grain genetic kinship ties (parents, siblings, cousins, etc.) from ancient remains is now gaining significant interest within the field of paleogenetics, as a means of deciphering the social organization of past societies. However, kinship analyses are in practice often quite difficult to apply within paleogenetic studies, and may carry a high degree of uncertainty in the results they provide, especially when applied on low coverage and/or highly degraded samples, or when studying poorly characterized populations. To overcome these challenges, most of the available kinship estimation methods either refrain from inferring ties beyond the second degree (e.g., half-siblings), and/or rely on the use of a cohort of individuals to obtain a satisfactory statistical significance. Thus, the current state of the art remains intrinsically limited when attempting to estimate kinship on a small number of individuals, or when trying to detect more distant relationships (e.g., cousins).
Methods:Here, we present GRUPS-rs:an update and complete reimplementation of GRUPS (Get Relatedness Using Pedigree Simulations), an ancient DNA kinship estimation software based on the methods originally developed in (Martin et al. 2017).GRUPS-rs both computes an estimate of relatedness from randomly sampled pseudo-haploidized variant calls, and leverages high-definition pedigree simulations to bypass the use of a cohort of individuals.
Results: We highlight that GRUPS and GRUPS-rs are especially suitable to perform kinship analysis on a restricted number of ancient samples, and can provide a sufficient statistical significance to estimate genetic relatedness past the second degree, while taking into account user-defined contamination and sequencing error estimates. Importantly, GRUPS-rs offers an estimated 14000-fold speed-up in runtime performance compared to its predecessor — allowing the joint estimation of kinship between dozens of individuals in a matter of minutes — and is now bundled with a user-friendly Shiny interface, in which users can interactively visualize their results.
Conclusions: The GRUPS kinship estimation method is now fully operational in its "GRUPS-rs" implementation, whose use is particularly recommended when analyzing a restricted number of low coverage DNA samples.
“…Independently filtered variant and invariant sites were then combined in a single VCF file using BCFtools v1.16 (Li, 2011) resulting in a total of 650,772 loci. As a final step, we "haploidized" the diploid individuals by randomly assigning heterozygote alleles as either homozygote reference or homozygote alternative using the "pseudoHaploidize" function included in the correctKin package (Nyerki et al, 2023). This procedure was implemented to create a bias-free SNP data set to be processed by algorithms that do not deal with mixed-ploidy populations.…”
Section: Sequencing Mapping and Genotypingmentioning
Insect pollination is fundamental for natural ecosystems and agricultural crops. The bumblebee species Bombus terrestris has become a popular choice for commercial crop pollination worldwide due to its effectiveness and ease of mass rearing. Bumblebee colonies are mass produced for the pollination of more than 20 crops and imported into over 50 countries including countries outside their native ranges, and the risk of invasion by commercial non‐native bumblebees is considered an emerging issue for global conservation and biological diversity. Here, we use genome‐wide data from seven wild populations close to and far from farms using commercial colonies, as well as commercial populations, to investigate the implications of utilizing commercial bumblebee subspecies in the UK. We find evidence for generally low levels of introgression between commercial and wild bees, with higher admixture proportions in the bees occurring close to farms. We identify genomic regions putatively involved in local and global adaptation, and genes in locally adaptive regions were found to be enriched for functions related to taste receptor activity, oxidoreductase activity, fatty acid and lipid biosynthetic processes. Despite more than 30 years of bumblebee colony importation into the UK, we observe low impact on the genetic integrity of local B. terrestris populations, but we highlight that even limited introgression might negatively affect locally adapted populations.
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