Inbreeding and relatedness in wild panda populations are important parameters for panda conservation. Habitat loss and fragmentation are expected to increase inbreeding but the actual inbreeding levels in natural panda habitats were unknown. Using 150,025 SNPs and 14,926 SNPs selected from published whole-genome sequences, we estimated genomic inbreeding coefficients and relatedness of 49 pandas including 34 wild pandas sampled from six habitats. Qinling and Liangshan pandas had the highest levels of inbreeding and relatedness measured by genomic inbreeding and coancestry coefficients, whereas the inbreeding levels in Qionglai and Minshan were 28-45% of those in Qinling and Liangshan. Genomic coancestry coefficients between pandas from different habitats showed that panda populations from the four largest habitats, Minshan, Qionglai, Qinling and Liangshan, were genetically unrelated. Pandas between these four habitats on average shared 66.0- 69.1% common alleles and 45.6-48.6% common genotypes, whereas pandas within each habitat shared 71.8-77.0% common alleles and 51.7-60.4% common genotypes. Pandas in the smaller populations of Qinling and Liangshan were more similarly to each other than pandas in the larger populations of Qionglai and Minshan according to three genomic similarity measures. Panda genetic differentiation between these habitats was positively related to their geographical distances. Most pandas separated by 200 kilometers or more shared no common ancestral alleles. The results provided a genomic quantification of the actual levels of inbreeding and relatedness among pandas in their natural habitats, provided genomic confirmation of the relationship between genetic diversity and geographical distances, and provided genomic evidence to the urgency of habitat protection.
Bibliographical noteFunding Information:
This research was supported by project MN-16-043 of the Agricultural Experiment Station at the University of Minnesota, and by Grant no. 2011- 67015-30333 from the USDA National Institute of Food and Agriculture. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Supercomputer computing time was provided by the Minnesota Supercomputer Institute. The authors thank Dr. Fuwen Wei's laboratory for making the panda sequence data available to the public.
© 2016 Garbe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.