Comparing genome‐based estimates of relatedness for use in pedigree‐based conservation management

Abstract

Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome‐based relatedness estimators (kinship genetic distance [KGD], Wang maximum likelihood [TrioML], Queller and Goodnight [Rxy], Kinship INference for Genome‐wide association studies [KING‐robust), and pairwise relatedness [RAB], allele‐sharing coancestry [AS]) across five species bred in captivity–including three birds and two mammals–with varying degrees of reliable pedigree data, using reduced‐representation and whole genome resequencing data. Genome‐based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome‐based estimator that is ideal across different species and data types. To determine the most appropriate genome‐based relatedness estimator for each new data set, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first‐order relationships. These recommendations are broadly applicable to conservation breeding programmes, particularly where genome‐based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results are also applicable to in situ wildlife management.

Species-wide genomics of kākāpō provides tools to accelerate recovery

“…As relationships between founders were unknown, the kākāpō studbook (pedigree) was enhanced by incorporating genomic-based estimates of founder relatedness 35 . The R XY estimator 58 was chosen after comparisons with several other estimators for precision with known first-order relationships -including KING 59 , KGD 60 , KGD with a correction for self-relatedness (as per 61 ), and TrioML 62 -as outlined in 63 . The final SNP data set used to estimate relatedness included a stringent filtering protocol using BCFtools and VCFtools to include only biallelic SNPs, coverage between 3 and 100, a minimum GQ score of 10, minimum allele frequency cutoff of 0.05, and a genotyping rate >90%.…”

“…Worldwide, many conservation programs struggle to incorporate founder relatedness into pedigrees 139 , but thanks to the long-lived nature of kākāpō and the sustained efforts of the Kākāpō Recovery Team, genomes for almost all kākāpō founders were available, and we were able to use the high-density SNPs developed in this manuscript to estimate relatedness among 35 founding individuals, representing all but a singular breeding member of the original population. In 2020, these estimates were incorporated into the kākāpō pedigree to enable better informed decisions using mean kinship and the Mate Suitability Index (MSI) in PMx 140 .…”

Ex situ conservation of two rare oak species using microsatellite and SNP markers

“…This is because several traits key to species survival, such as disease resistance, often occur at low frequencies in wild populations (Sniezko & Koch, 2017). However, if the conservation goal of ex situ collections is instead the representation of more common alleles, then our results demonstrate that microsatellites remain a relevant marker for measurements of that representation, and provide an accurate, efficient, and cost‐effective assessment of the overall genetic diversity represented ex situ (Hauser et al., 2022; Hodel et al., 2016).…”

Whole group tracking reveals that relatedness drives consistent subgrouping patterns in white-nosed coatis

“…Although a variety of relatedness estimators exist for analysing SNP data, we implemented the triadic maximum likelihood estimator (TrioML; Wang, 2007) to calculate relatedness coefficients among each unique coati pair. We made this decision as each of the seven estimators available in COANCESTRY software were highly correlated for the coati dataset (r > 0.93 for each comparison between relatedness estimators), and hence the TrioML estimator was selected as the most suitable option as it is also considered robust to inbreeding, small sampling sizes, and genotyping error (Hauser et al, 2022; Wang, 2007).…”