Related Experiment Video
Updated: May 7, 2026

Effectiveness of the Air Stripping in Two Salmonid Fish, Rainbow Trout Oncorhynchus Mykiss and Brown Trout Salmo Trutta Morpha fario
Published on: September 16, 2018
Molecular markers for variation in spawning date in a hatchery population of rainbow trout (Oncorhynchus mykiss)
M S Allen1, M M Ferguson, R G Danzmann
1Department of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
Abstract:
We examined the distribution of alleles at 63 microsatellite loci distributed across 29 linkage groups in broodstock females from a commercial population of rainbow trout spawning on different dates throughout the season (August to January). A total of 368 females, 184 and 117 females from each of the tail-ends of the spawning distribution and a subsample of 67 females spawning in the middle, were used to detect marker-trait associations. Twenty-one loci in a subset of genomic regions (RT-5, 7, 8, 10, 12, 14, 15, 22, 23, 24, 25, 29, 30, and 31) were significantly associated with variation in spawning date. Many of these markers localize to regions with known spawning date quantitative trait loci based on previous studies. An individual assignment analysis was used to test how well the molecular data could be used to assign individuals to their correct spawning group, and markers were given a ranking reflecting their contribution to the accuracy of assignment. The top 15 ranked markers were successful at assigning the majority of females to the correct spawning group based on genotype with an average accuracy of 76 %. The most likely genes that could contribute to these differences in spawning date are discussed. Together, these data indicate that the loci could be incorporated into a selection index with phenotype data to increase the accuracy of selection for spawning date.
Related Concept Videos
Derivatives: Problem Solving
Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...

