Genomic Studies of Reproductive Performance and Fur Quality Traits in American Mink
Abstract
This thesis aimed to enhance reproductive performance and pelt quality traits in American mink
(Neogale vison) using genomics approaches. Chapter 3 involved estimation of genetic and
phenotypic parameters for pelt quality traits. Low-to-moderate heritabilities (±SE), ranging from
0.12±0.04 to 0.44±0.047, were estimated for dried pelt, live grading, body weight and length traits
indicating these traits can be improved by genetic/genomic selection. The estimated genetic
correlations demonstrated body weight and length measured in November of the first year of life
was a good indicator for pelt size without negative influence on overall quality of dried pelt. The
moderate positive genetic correlations between body length in November and harvest with overall
quality of dried pelt suggested their utility as indicators to select for increased size and overall
quality of dried pelt. Chapter 4 analyzed whole-genome data from 100 mink to detect selection
signatures in the genome influencing pelt quality traits and coat color. Selection signatures were
detected through three methods of fixation index (Fst), cross population extended haplotype
homozygosity (XP-EHH), and nucleotide diversity (θπ). Overlapping top 1% of Fst and XP-EHH
contained 376 genes for pelt quality and coat color. Overlapping top 1% of Fst, XP-EHH and θπ
revealed 19 selection signature regions on chromosomes 3, 4, 5, 6, 7, 8, 9, and 10, including
APCDD1 gene with important roles on hair follicular process. In Chapter 5, genome-wide
association studies performed to identify markers associated with eight reproductive traits and five
pelt quality traits. The most significant associations were found on chromosomes 1, 2, and 4 for
gestation length and on chromosome 6 for dried pelt size. Several candidate genes with important
roles in reproduction were detected, along with novel genes related to pelt quality and size. In
Chapter 6, prediction performance of three genomic evaluation approaches of genomic best liner
unbiased prediction (GBLUP), BayesCπ, and single-step Bayesian multiple marker regression
(SSBR) were compared for reproductive and pelt quality traits. SSBR consistently yielded higher
predictive accuracy for all traits compared to both GBLUP and BayesCπ. The findings of these
studies suggest that genomic approaches hold promise for improving these economically important
traits.