Year of Award


Document Type


Degree Type

Doctor of Philosophy (PhD)

Degree Name

Organismal Biology and Ecology

Department or School/College

Division of Biological Sciences

Committee Co-chair

Fred W. Allendorf, Gordon Luikart

Commitee Members

Jeffrey Good, Jon Graham, John McCutcheon


University of Montana


Understanding the fitness effects of inbreeding is a crucial and long standing goal in conservation and evolutionary biology. Many studies measure individual inbreeding (F, the proportion of genome that is identical by descent) and its fitness effects using either pedigrees or molecular markers. Knowing which genes most strongly affect fitness can help to explain why some individuals outperform others, and elucidate the mechanisms of inbreeding depression and adaptation. However, identifying adaptive genes is difficult in most species because of limited genomic resources.

I used simulations to evaluate the performance of marker- and pedigree-based measures of F and inbreeding depression. I found that FP was less precise than marker-based measures of F in a broad range of scenarios. For example, the true F was always more strongly correlated with heterozygosity measured with 5000 single nucleotide polymorphisms (SNPs) than with FP. F was also more strongly correlated with the proportion of the genome in long runs of homozygosity (FROH, estimated with 35K SNPs) than with FP. I also show that heterozygosity-based estimates of the strength of inbreeding depression are precise in populations with high variance in F (e.g., σ2(F) ≥ 0.002). A potential solution to the imprecision of FP is to use genetic markers to correct for the kinship of pedigree founders. However, I found that founder kinship-corrected values of FP were also imprecise. These results show that F and inbreeding depression can be most reliably measured with genetic markers in most scenarios – countering the prevailing historical view that F is most reliably measured with pedigrees.

I used whole genome sequences of pooled DNA aligned to the domestic sheep genome to detect candidate adaptive genes in bighorn sheep. I detected selection signatures in 53 genomic regions containing genes. However, simulations suggest that some of these selection signatures may be false positives. Putatively selected genomic regions contained genes involved with traits known to affect fitness in bighorn sheep (e.g., horn and body growth). These results provide candidate genes for traits known to strongly influence fitness in bighorn, and illustrate the great promise of WGS for detecting selection signatures in small populations.



© Copyright 2013 Martin Dennis Kardos