| Literature DB >> 34795357 |
Tappei Mishina1,2, Hirohiko Takeshima3,4, Mikumi Takada5, Kei'ichiro Iguchi6, Chunguang Zhang7, Yahui Zhao7, Ryouka Kawahara-Miki8, Yasuyuki Hashiguchi9, Ryoichi Tabata10,11, Takeshi Sasaki12, Mutsumi Nishida13, Katsutoshi Watanabe14.
Abstract
Asexual vertebrates are rare and at risk of extinction due to their restricted adaptability through the loss of genetic recombination. We explore the mechanisms behind the generation and maintenance of genetic diversity in triploid asexual (gynogenetic) Carassius auratus fish, which is widespread in East Asian fresh waters and exhibits one of the most extensive distribution among asexual vertebrates despite its dependence on host sperm. Our analyses of genetic composition using dozens of genetic markers and genome-wide transcriptome sequencing uncover admixed genetic composition of Japanese asexual triploid Carassius consisting of both the diverged Japanese and Eurasian alleles, suggesting the involvement of Eurasian lineages in its origin. However, coexisting sexual diploid relatives and asexual triploids in Japan show regional genetic similarity in both mitochondrial and nuclear markers. These results are attributed to a unique unidirectional gene flow from diploids to sympatric triploids, with the involvement of occasional sexual reproduction. Additionally, the asexual triploid shows a weaker population structure than the sexual diploid, and multiple triploid lineages coexist in most Japanese rivers. The generated diversity via repeated interploidy gene flow as well as an increased establishment of immigrants is assumed to offset the cost of asexual reproduction and might contribute to the successful broad distribution of this asexual vertebrate.Entities:
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Year: 2021 PMID: 34795357 PMCID: PMC8602411 DOI: 10.1038/s41598-021-01754-w
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Tested hypotheses about the origin of the Japanese triploid C. auratus-complex investigated in this study and expected analysis outcomes.
Figure 2Genetic composition of triploid Carassius. (A) Locality, ploidy, and mitochondrial lineages of specimens used for target resequencing. Triangles indicate diploids, circles represent triploids, and a square represents C. cuvieri with colors corresponding to the mitochondrial lineages of the specimens. The map was generated using the R package mapdata. (B) PCA plot and (C) triangle plots of interspecific heterozygosity versus hybrid index based on the SNPs obtained from targeted resequencing. (D) Genetic composition across chromosomes in selected specimens of major mtDNA lineages of triploid Carassius in Japan based on dSNPs generated from RNA-seq. The ratios of genotype categories from dSNPs between the Japanese and Eurasian lineages are colored as Japanese homozygote (blue), Eurasian homozygote (red), and heterozygote (green).
Figure 3Population structure of Carassius, showing weaker geographical population structure of gynogenetic triploids than that of sexual conspecific diploids. (A) Geographic distribution of mitochondrial lineages of diploid and triploid Carassius in Japan. (B, C) Isolation by distance (IBD) in Carassius fish based on mtDNA haplotypes from 54 river systems in Japan. (B) IBD among diploids (blue) and triploids (red). (C) IBD between diploids and triploids. The maps were generated using the R package mapdata.
Figure 4PCoA on mixed-ploidy populations of diploid and triploid Carassius using Bruvo’s distance performed in POLYSAT. Triangles indicate diploids, and circles represent triploids, with colors corresponding to the mitochondrial lineages of the specimens.
Figure 5STRUCTURE results for diploid (K = 10, left) and triploid (K = 6, right) Carassius based on microsatellites. Relative sample sizes of clusters are shown as a pie chart on the map. NJ trees indicate allele frequency divergence between genetic groups inferred by STRUCTURE, and the tips are colored corresponding to the colors of clusters. In most of the river systems, triploid individuals are identified in multiple clusters. The maps were generated using the R package mapdata.