Comparison of kinship-identification methods for robust stock assessment
using close-kin mark--recapture data for Pacific bluefin tuna
Abstract
Several attempts have been made to understand the population dynamics of
fishery resources, such as tuna species using an integrated analysis
model with multiple data sources. However, estimating absolute abundance
levels in practical stock assessments remains a challenge. Close-kin
mark–recapture (CKMR) methods provide information about the number of
adults in a population using close-kinship pairs identified by genetic
markers and statistical methods. In this study, we compared three
methods for kinship identification using different algorithms in samples
of wild Pacific bluefin tuna genotyped across 5,029 genome-wide single
nucleotide polymorphisms in 4,108 samples. The fraRF method we developed
employs pairwise identity-by-descent values as inputs for random-forest
classification. The other two methods were CKMRsim and COLONY, which
have been published and applied in several studies. These three methods
were applied to the actual genotyping data with moderate missing
genotypes, in addition to the pseudo-generated genotyping data for the
simulation test. The simulation test mimicked genotyping data with
physical linkage as well as genetic characteristics similar to those of
actual samples. The three methods resulted in different numbers of
inferred kinship pairs for both generated and actual data. Particularly
for the half-sibling pairs, considerable number of false-positive and
false-negative existed in the identification results. The differences in
kinship identification results were interpreted based on a simulation
test. This study may promote the understanding of behavior in each
software when applying the software to SNP data with moderate missing
genotypes as in the case of this study.