Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jan 9;9(1):217-228.
doi: 10.1534/g3.118.200779.

Medaka Population Genome Structure and Demographic History Described via Genotyping-by-Sequencing

Affiliations
Free PMC article

Medaka Population Genome Structure and Demographic History Described via Genotyping-by-Sequencing

Takafumi Katsumura et al. G3 (Bethesda). .
Free PMC article

Abstract

Medaka is a model organism in medicine, genetics, developmental biology and population genetics. Lab stocks composed of more than 100 local wild populations are available for research in these fields. Thus, medaka represents a potentially excellent bioresource for screening disease-risk- and adaptation-related genes in genome-wide association studies. Although the genetic population structure should be known before performing such an analysis, a comprehensive study on the genome-wide diversity of wild medaka populations has not been performed. Here, we performed genotyping-by-sequencing (GBS) for 81 and 12 medakas captured from a bioresource and the wild, respectively. Based on the GBS data, we evaluated the genetic population structure and estimated the demographic parameters using an approximate Bayesian computation (ABC) framework. The genome-wide data confirmed that there were substantial differences between local populations and supported our previously proposed hypothesis on medaka dispersal based on mitochondrial genome (mtDNA) data. A new finding was that a local group that was thought to be a hybrid between the northern and the southern Japanese groups was actually an origin of the northern Japanese group. Thus, this paper presents the first population-genomic study of medaka and reveals its population structure and history based on chromosomal genetic diversity.

Keywords: RAD-seq; bioresource; demography; freshwater fish; local population.

Figures

Figure 1
Figure 1
Map of the original locations of the wild lab stocks and wild-captured medakas. In the upper central map, the enlarged red frame shows the boundary region between S.JPN and N.JPN. Each color represents the mtDNA and allozyme-based groups shown in the left upper inset box. The numbers on the map are consistent with the population IDs, with the names on the right bottom inset box.
Figure 2
Figure 2
Results of principle component analysis (PCA) using SNPs in East Asia (A) and the Japanese archipelago (B). Each plot shows PC1 vs. PC2. The population names of each point are described in Figure S7.
Figure 3
Figure 3
Phylogenetic tree using the maximum likelihood method and an ancestry barplot with ADMIXTURE analysis. Red closed and open circles represent the northern and southern Kyushu populations, respectively. “Taj-Tan” in the tree is the abbreviation for Tajima-Tango.
Figure 4
Figure 4
Shared allele distribution among boundary populations. The gray rectangle represents the total length of each medaka chromosome. The table in the figure shows the number of alleles shared between the groups observed on each chromosome. Mark represents the state whose group shares that allele. *1 and *2 are the total number from chromosomes 1 to 12 and from chromosomes 13 to 24, respectively.
Figure 5
Figure 5
Scenarios for estimation of the demographic parameters. Possible scenarios for the population history of the Tajima-Tango group (A) and the “Out of northern Kyushu (NK)” event (B) are shown. The TMRCAs estimated using ABC are in scenario III (C), scenario IV (D) and Out of NK (E).
Figure 6
Figure 6
Map representing the ancestry proportions from ADMIXTURE analysis at K = 6. Solid and dashed lines represent the spreading patterns of S.JPN and N.JPN inferred by GBS data, respectively.

Similar articles

See all similar articles

Cited by 1 article

References

    1. Alexander D. H., Novembre J., Lange K., 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19: 1655–1664. 10.1101/gr.094052.109 - DOI - PMC - PubMed
    1. Andrews K. R., Good J. M., Miller M. R., Luikart G., Hohenlohe P. A., 2016. Harnessing the power of RADseq for ecological and evolutionary genomics. Nat. Rev. Genet. 17: 81–92. 10.1038/nrg.2015.28 - DOI - PMC - PubMed
    1. Ansai S., Kinoshita M., 2014. Targeted mutagenesis using CRISPR/Cas system in medaka. Biol. Open 3: 362–371. 10.1242/bio.20148177 - DOI - PMC - PubMed
    1. Asai T., Senou H., Hosoya K., 2011. Oryzias sakaizumii, a new ricefish from northern Japan (Teleostei: Adrianichthyidae). Ichthyol. Explor. Freshwat. 22: 289–299.
    1. Beaumont M. A., Zhang W., Balding D. J., 2002. Approximate Bayesian computation in population genetics. Genetics 162: 2025–2035. - PMC - PubMed

Publication types

Substances

LinkOut - more resources

Feedback