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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Evaluating Kinship Estimation Methods for Reduced-Representation SNP Data in Non-model Species.

Eilish S McMaster^1,2, Patricia Lu-Irving², Marlien M van der Merwe²

¹School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia.

Molecular Ecology Resources

|August 26, 2025

Summary

Estimating kinship in wild populations is challenging. Six methods were tested on Australian plants, with PLINK recommended for general use, while others suit specific conditions like low structure or high precision needs.

Keywords:

conservation genetics inbreeding kinship non‐model species plants population genetics—empirical reduced‐representation sequencing

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Area of Science:

Conservation Genetics
Population Genomics
Bioinformatics

Background:

Accurate kinship estimation is vital for wildlife conservation and restoration efforts.
Challenges in wild populations include genetic structure and inbreeding, impacting kinship inference.
The effectiveness of kinship analysis using reduced-representation sequencing data is not fully understood.

Purpose of the Study:

To evaluate the sensitivity and precision of six kinship inference methods.
To assess method performance in detecting parent-offspring and sibling relationships.
To provide recommendations for kinship estimation in non-model plant species.

Main Methods:

Six kinship methods were tested: Goudet's beta dosage, KING Homo, KING Robust, PC-Relate, PLINK, and RelateAdmix.
Analyses were performed on 3395 individuals from 363 families across six Australian plant species.
Method performance was assessed across varying species and filtering parameters.

Main Results:

Method efficacy varied significantly based on species genetic structure and inbreeding levels.
Goudet's beta dosage and RelateAdmix performed well in low-structure, non-inbred populations.
PLINK provided a balance of sensitivity and precision, KING Robust offered high precision but missed relatives, and PC-Relate showed high false positives.

Conclusions:

PLINK is recommended for general kinship estimation in these species.
Goudet's beta dosage and RelateAdmix are suitable for low-structure populations.
KING Robust is best for high-precision requirements, and comparing methods is advisable due to complementary strengths.