Research ArticleEVOLUTIONARY BIOLOGY

Genomic evidence for two phylogenetic species and long-term population bottlenecks in red pandas

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Science Advances  26 Feb 2020:
Vol. 6, no. 9, eaax5751
DOI: 10.1126/sciadv.aax5751
  • Fig. 1 Distinguishing morphological differences between two red panda species.

    (A and C) The Chinese red panda. (B and D) The Himalayan red panda. (A and B) The face coat color of the Chinese red panda is redder with less white on it than that of the Himalayan red panda. (C and D) The tail rings of the Chinese red panda are more distinct than those of the Himalayan red panda, with the dark rings being more dark red and the pale rings being more whitish. Photo credit: (A) Yunfang Xiu, Straits (Fuzhou) Giant Panda Research and Exchange Center, China; does not require permission. (B) Arjun Thapa, Institute of Zoology, Chinese Academy of Sciences. (C) Yibo Hu, Institute of Zoology, Chinese Academy of Sciences. (D) Chiranjibi Prasad Pokheral, Central Zoo, Jawalkhel, Lalitpur, Nepal; does not require permission.

  • Fig. 2 Population genetic structure based on whole genomes, Y chromosome SNPs, and mitochondrial genomes of red pandas.

    (A) The geographic distribution of wild red panda samples under the background of habitat suitability. Red, QL population; purple, XXL-LS population; blue, SLL population; pink, EH-GLG; dark red, MH. (B) Maximum likelihood phylogenetic tree based on whole-genome SNPs, with the ferret as the outgroup. The values on the tree nodes indicate the bootstrap support of ≥50%. (C) ADMIXTURE result based on whole-genome SNPs with K = 2 to 7. (D) PCA result based on whole-genome SNPs. (E) Network map based on eight Y chromosome SNP haplotypes. (F) Network map based on 41 mitochondrial genome haplotypes.

  • Fig. 3 Demographic history, divergence, and admixture of two red panda species and their populations.

    (A) PSMC analysis revealed different demographic histories of the two species, with a generation time (g) of 6 years and a mutation rate (μ) of 7.9 × 10−9 per site per generation. The time axis is logarithmic transformed. (B) Fastsimcoal2 simulation reconstructed the divergence, admixture, and demographic history of red panda species and populations. The time axis is logarithmic transformed, and the number of migrants per year between two adjacent populations is shown beside each arrow. (C) TreeMix analysis detected significant gene flow from the EH-GLG to XXL-LS populations. s.e., standard error.

  • Fig. 4 Genetic variation, genetic load, and natural selection of red pandas.

    (A) Genetic variations (nucleotide diversity) of different species and populations based on whole-genome SNPs, mitochondrial genomes, and Y chromosome SNPs. (B) LD of the four populations. (C) Ratios of homozygous derived deleterious or LoF variants to homozygous derived synonymous variants for different populations. The horizontal bars denote population means. (D) Distribution of θπ ratios (non-MH/MH) and Z(FST) values. Data points located to the left of the left vertical dashed lines and the right of the right vertical dashed lines (corresponding to the 5% left and right tails of the empirical θπ ratio distribution, respectively) and above the horizontal dashed line [the 5% right tail of the empirical Z(FST) distribution] were identified as selected regions for the MH (the Himalayan red panda, green points) and non-MH (the Chinese red panda, blue points) populations.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/6/9/eaax5751/DC1

    Fig. S1. PCA plot of red panda whole-genome SNPs data, with PC1, PC2, and PC3 explaining 28.5, 4.1, and 3.6% of the observed variations, respectively.

    Fig. S2. Phylogenetic tree based on 41 mitochondrial genome haplotypes, showing two significant species lineages (A. fulgens and A. styani).

    Fig. S3. Phylogenetic tree based on eight Y chromosome SNPs haplotypes, showing two significant species lineages (A. fulgens and A. styani).

    Fig. S4. Bayesian skyline plot (BSP) analysis results based on mitochondrial genomes.

    Fig. S5. Four alternative population divergence models for Fastsimcoal2 simulations, with the maximum estimated likelihood values shown.

    Fig. S6. Residual fit from the maximum likelihood tree estimated by TreeMix.

    Table S1. Summary of the morphological differences between the Himalayan and Chinese red pandas.

    Table S2. Sample information for whole-genome resequencing, Y chromosome SNP genotyping, mitochondrial genome assembly, and Fastsimcoal2 analysis.

    Table S3. Summary of whole-genome resequencing data for 65 red panda individuals that include the individuals for PSMC analysis.

    Table S4. Summary of SNP calling based on 65 red panda individuals.

    Table S5. Cross-validation error result for varying values of K in the ADMIXTURE analysis.

    Table S6. PCR primer information for validating the six male-specific Y-scaffolds of red pandas.

    Table S7. PCR primer information for amplifying the SNPs on the male-specific Y-scaffolds.

    Table S8. Eight Y-SNP haplotypes identified from 27 Y-SNPs of 49 male red panda individuals.

    Table S9. Confidence intervals of key parameters for the best population divergence and demographic model estimated by Fastsimcoal2.

    Table S10. Genetic diversity of whole genome, Y chromosome, and mitochondrial genome for different species and populations of red pandas.

    Table S11. The 146 genes under selection with top 5% maximum FST values and top 5% minimum θπ1π2 values in the Himalayan red panda (MH).

    Table S12. Significantly enriched KEGG pathways for the 146 genes under selection in the Himalayan red panda (MH).

    Table S13. Significantly enriched GO terms of biological processes for the 146 genes under selection in the Himalayan red panda (MH).

    Table S14. The 178 genes under selection with top 5% maximum FST values and top 5% minimum θπ1π2 values in the Chinese red panda (EH-GLG, XXL-LS, and QL).

    Table S15. Significantly enriched KEGG pathways for the 178 genes under selection in the Chinese red panda (EH-GLG, XXL-LS, and QL).

    Table S16. Significantly enriched GO terms of biological processes for the 178 genes under selection in the Chinese red panda (EH-GLG, XXL-LS, and QL).

  • Supplementary Materials

    The PDF file includes:

    • Fig. S1. PCA plot of red panda whole-genome SNPs data, with PC1, PC2, and PC3 explaining 28.5, 4.1, and 3.6% of the observed variations, respectively.
    • Fig. S2. Phylogenetic tree based on 41 mitochondrial genome haplotypes, showing two significant species lineages (A. fulgens and A. styani).
    • Fig. S3. Phylogenetic tree based on eight Y chromosome SNPs haplotypes, showing two significant species lineages (A. fulgens and A. styani).
    • Fig. S4. Bayesian skyline plot (BSP) analysis results based on mitochondrial genomes.
    • Fig. S5. Four alternative population divergence models for Fastsimcoal2 simulations, with the maximum estimated likelihood values shown.
    • Fig. S6. Residual fit from the maximum likelihood tree estimated by TreeMix.
    • Table S1. Summary of the morphological differences between the Himalayan and Chinese red pandas.
    • Table S2. Sample information for whole-genome resequencing, Y chromosome SNP genotyping, mitochondrial genome assembly, and Fastsimcoal2 analysis.
    • Table S3. Summary of whole-genome resequencing data for 65 red panda individuals that include the individuals for PSMC analysis.
    • Table S4. Summary of SNP calling based on 65 red panda individuals.
    • Table S5. Cross-validation error result for varying values of K in the ADMIXTURE analysis.
    • Table S6. PCR primer information for validating the six male-specific Y-scaffolds of red pandas.
    • Table S7. PCR primer information for amplifying the SNPs on the male-specific Y-scaffolds.
    • Table S8. Eight Y-SNP haplotypes identified from 27 Y-SNPs of 49 male red panda individuals.
    • Table S9. Confidence intervals of key parameters for the best population divergence and demographic model estimated by Fastsimcoal2.
    • Table S10. Genetic diversity of whole genome, Y chromosome, and mitochondrial genome for different species and populations of red pandas.
    • Legends for tables S11 to S16

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    Other Supplementary Material for this manuscript includes the following:

    • Table S11 (Microsoft Excel format). The 146 genes under selection with top 5% maximum FST values and top 5% minimum θπ1π2 values in the Himalayan red panda (MH).
    • Table S12 (Microsoft Excel format). Significantly enriched KEGG pathways for the 146 genes under selection in the Himalayan red panda (MH).
    • Table S13 (Microsoft Excel format). Significantly enriched GO terms of biological processes for the 146 genes under selection in the Himalayan red panda (MH).
    • Table S14 (Microsoft Excel format). The 178 genes under selection with top 5% maximum FST values and top 5% minimum θπ1π2 values in the Chinese red panda (EH-GLG, XXL-LS, and QL).
    • Table S15 (Microsoft Excel format). Significantly enriched KEGG pathways for the 178 genes under selection in the Chinese red panda (EH-GLG, XXL-LS, and QL).
    • Table S16 (Microsoft Excel format). Significantly enriched GO terms of biological processes for the 178 genes under selection in the Chinese red panda (EH-GLG, XXL-LS, and QL).

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