Location: Cool and Cold Water Aquaculture ResearchTitle: GWAS for detecting QTL associated with Columnaris Disease in two rainbow trout breeding populations
|SILVA, RAFAEL - Orise Fellow|
|MARTIN, KYLE - Troutlodge, Inc|
|MISZTAL, IGNACY - University Of Georgia|
|Leeds, Timothy - Tim|
|LORENCO, DANIELA - University Of Georgia|
Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 11/1/2017
Publication Date: 1/13/2018
Citation: Silva, R., Evenhuis, J., Vallejo, R.L., Gao, G., Martin, K., Misztal, I., Leeds, T.D., Lorenco, D., Palti, Y. 2018. GWAS for detecting QTL associated with Columnaris Disease in two rainbow trout breeding populations. Plant and Animal Genome Conference. International Plant and Animal Genome XXVI. Paper No. 101.
Technical Abstract: The purpose of this study was to prospect genomic regions that explain large portion of the additive genetic variance for resistance against Columnaris disease (CD) in rainbow trout. Two important aquaculture populations were investigated. The National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line, which was previously selected for bacterial cold water disease resistance; and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. The number of fish in the pedigree was 54,350 and 36,265, respectively; in which 8,453 and 3,986 fish had phenotypes recorded for CD resistance, respectively. Fish that survived to 21 days post immersion challenge were recorded as resistant. Genotypes for 57k SNPs (Affymetrix Axiom®) were available for 1,185 and 1,137 fish from NCCCWA and TLUM, respectively. The SNP effects and variances were estimated using the weighted single-step genomic BLUP approach for genome-wide association (WssGBLUP), which uses pedigree, genotypes, and phenotypes from genotyped and ungenotyped animals. The weighting strategy accounted for 1Mb moving SNP-windows along each of the 29 chromosomes in the reference genome. Genomic regions that explained more than 1% of the additive genetic variance were considered associated with CD resistance. A total of 13 windows located on six chromosomes were found to be associated with CD resistance in the NCCCWA population. Two windows, located at 59-60 Mb and 61-62 Mb on chromosome Omy17, explained 12% and 11.33% of the genetic variance for CD resistance, respectively. In the TLUM population, a total of 16 windows located on nine chromosomes were detected. Only three similar windows (located on two chromosomes) were detected in both populations. The results suggest that CD resistance has an oligogenic architecture, and the SNP windows found to be associated with CD are not informative enough for selection decisions across populations. In the next steps, we will assess strategies for genomic selection by predicting and comparing the accuracy of genomic evaluations generated using lower-density SNP panels and a panel composed solely from QTL-associated SNPs.