There have been many attempts to understand population dynamics in fishery resources such as tuna species using an integrated-analysis model with multiple data sources. However, estimating the absolute abundance level in practical stock assessments remains challenging. The close-kin mark–recapture (CKMR) method provides information about the number of adults in a population utilizing close-kinship pairs (i.e., parent–offspring, full-sibling, or half-sibling pairs) identified based on statistical methods that employ genetic markers. To introduce the CKMR method into the stock assessment by integrated analysis, it is necessary to clarify the potential errors obtained from the uncertainties in the CKMR method and other data sources. In this paper, we applied three methods of kinship identification for samples from the wild Pacific bluefin tuna population using genome-wide DNA markers to determine the potential errors in statistical kinship estimates. Herein, one method used a random-forest classification algorithm called fraRF that employed pairwise identity-by-descent values. The other two methods were CKMRsim and COLONY. Comparisons among these three methods revealed differences in the numbers of inferred kinship pairs, especially for sibling relationships. The differences among the three methods seem to occur mainly from uncertainty of the kinship identification in the CKMR method. Therefore, this result provides an understanding of ways to incorporate the CKMR method into the integrated analysis model with the possible CKMR errors.

The Arabidopsis thaliana population has been exposed to unexperienced biotic and abiotic stresses as a result of range expansion or environmental change. To obtain a global picture of the genetic adaptations in the population history of A. thaliana, we constructed a database of the phenotypic-adaptations (p-adaptations) and gene expression-adaptations (e-adaptations). We analysed the dynamics of the allele frequencies at the 23,880 QTLs of 174 traits and 8,618 eQTLs of 1,829 genes with respect to the total SNPs in the genomes, and identified 650 p-adaptations and 3,925 e-adaptations (FDR=0.05). The population underwent large scale p-adaptations and e-adaptations along four lineages, the eastward migration to Central Asia and South Siberia, Russia, the northward migration to Sweden, the migration to Azerbaijan, and the migration of the German population to the United States. Extremely cold winters and short summers prolonged seed dormancy, and expanded the root system architecture. Low temperatures prolonged the growing season and low light intensity required the increased chloroplast activity. The subtropical and humid environment enhanced phytohormone signaling pathways in response to the biotic and abiotic stresses. Exposure to heavy metals selected for alleles underlying low heavy metal uptake from soil, lower growth rate, lower resistance to bacteria, and higher expression of photosynthetic genes were selected. The database of p-adaptations and e-adaptations, which complements studies focusing on specific aspects of adaptation, may be useful for future studies to understand the biological adaptations of A. thaliana throughout its population history.