Abstract

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.

Highlights

  • Understanding genetic diversity including genetic relatedness and inbreeding levels in wild panda populations is important for preserving panda genetic diversity through ex situ conservation and reintroduction programs

  • We estimated additional measures of genomic relatedness and similarity: probability of alleles identical by descent (IBD) to serve as a measure of genomic relatedness and a comparison with genomic conancestry coefficient, probability of alleles identical by state (IBS) as a measure of common alleles shared by two individuals, probability of single nucleotide polymorphism (SNP) loci identical by genotype (IBG) as a measure of common genotypes shared by two individuals, and probability of non-shared genotypes between two genotypes (NSG) as a measure of opposing genotypes without common alleles (e.g., AA and aa genotypes) to exclude parent-offspring relationship between two individuals

  • Additive and dominance relationships were estimated using two sets of SNP markers for forty-nine pandas including thirty-four wild pandas sampled from all six panda habitats, Minshan, Qionglai, Qinling, Liangshan, Daxiangling and Xiaoxiangling [1]

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Summary

Introduction

Understanding genetic diversity including genetic relatedness and inbreeding levels in wild panda populations is important for preserving panda genetic diversity through ex situ conservation and reintroduction programs. Genetic diversity analysis of pandas from various origins using microsatellite markers generated information about the genomic representation of the wild panda population by the captive population [2,3], inbreeding and relatedness in panda captive breeding population [3], historical changes of genetic diversity in the two largest panda habitats [4], and variations of the MHC polymorphism in different habitats [5]. A study using nineteen microsatellite markers detected the existence of substantial inbreeding and relatedness among wild-born and captive-born pandas managed at panda breeding centers [3]. Knowledge of such inbreeding and relatedness not documented in the panda pedigree should be helpful for minimizing hidden inbreeding due to related wild founders that were assumed unrelated in the calculation of inbreeding coefficients using pedigree data

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