Increasing habitat fragmentation leads to wild populations becoming small, isolated, and threatened by inbreeding depression. However, small populations may be able to purge recessive deleterious alleles as they become expressed in homozygotes, thus reducing inbreeding depression and increasing population viability. We used whole-genome sequences from 57 tigers to estimate individual inbreeding and mutation load in a small–isolated and two large–connected populations in India. As expected, the small–isolated population had substantially higher average genomic inbreeding (FROH = 0.57) than the large–connected (FROH = 0.35 and FROH = 0.46) populations. The small–isolated population had the lowest loss-of-function mutation load, likely due to purging of highly deleterious recessive mutations. The large populations had lower missense mutation loads than the small–isolated population, but were not identical, possibly due to different demographic histories. While the number of the loss-of-function alleles in the small–isolated population was lower, these alleles were at higher frequencies and homozygosity than in the large populations. Together, our data and analyses provide evidence of 1) high mutation load, 2) purging, and 3) the highest predicted inbreeding depression, despite purging, in the small–isolated population. Frequency distributions of damaging and neutral alleles uncover genomic evidence that purifying selection has removed part of the mutation load across Indian tiger populations. These results provide genomic evidence for purifying selection in both small and large populations, but also suggest that the remaining deleterious alleles may have inbreeding-associated fitness costs. We suggest that genetic rescue from sources selected based on genome-wide differentiation could offset any possible impacts of inbreeding depression.

Knowledge of relationships in wild populations is critical for better understanding mating systems and inbreeding scenarios to inform conservation strategies for endangered species. To delineate pedigrees in wild populations, study genetic connectivity, study genotype‐phenotype associations, trace individuals, or track wildlife trade, many identified individuals need to be genotyped at thousands of loci, mostly from noninvasive samples. This requires us to (a) identify the most common noninvasive sample available from identified individuals, (b) assess the ability to acquire genome‐wide data from such samples, and (c) evaluate the quality of such genome‐wide data, and its ability to reconstruct relationships between animals within a population. We followed identified individuals from a wild endangered tiger population and found that shed hair samples were the most common compared to scat samples, opportunistically found carcasses, and opportunistic invasive samples. We extracted DNA from these samples, prepared whole genome sequencing libraries, and sequenced genomes from these. Whole genome sequencing methods resulted in between 25%–98% of the genome sequenced for five such samples. Exploratory population genetic analyses revealed that these data were free of holistic biases and could recover expected population structure and relatedness. Mitochondrial genomes recovered matrilineages in accordance with long‐term monitoring data. Even with just five samples, we were able to uncover the matrilineage for three individuals with unknown ancestry. In summary, we demonstrated that noninvasive shed hair samples yield adequate quality and quantity of DNA in conjunction with sensitive library preparation methods, and provide reliable data from hundreds of thousands of SNPs across the genome. This makes shed hair an ideal noninvasive resource for studying individual‐based genetics of elusive endangered species in the wild.

Increasing habitat fragmentation leads to wild populations becoming small, isolated, and threatened by inbreeding depression. However, small populations may be able to purge recessive deleterious alleles as they become expressed in homozygotes, thus reducing inbreeding depression and increasing population viability. We used genome sequencing of 57 tigers to estimate individual inbreeding and mutation loads in a small-isolated, and two large-connected populations in India. As expected, the small-isolated population had substantially higher average genomic inbreeding (FROH=0.57) than the large-connected (FROH=0.35 and FROH=0.46) populations. The small-isolated population had the lowest loss-of-function mutation load, likely due to purging of highly deleterious recessive mutations. The large populations had lower missense mutation loads than the small-isolated population, but were not identical, possibly due to different demographic histories. While the number of the loss-of-function alleles in the small-isolated population was lower, these alleles were at high frequencies and homozygosity than in the large populations. Together, our data and analyses provide evidence of (a) high mutation load; (b) purging and (c) the highest predicted inbreeding depression, despite purging, in the small-isolated population. Frequency distributions of damaging and neutral alleles uncover genomic evidence that purifying selection has removed part of the mutation load across Indian tiger populations. These results provide genomic evidence for purifying selection in both small and large populations, but also suggest that the remaining deleterious alleles may have inbreeding associated fitness costs. We suggest that genetic rescue from sources selected based on genome-wide differentiation should offset any possible impacts of inbreeding depression.