Introduction
When rainbow trout and the other salmonids become sexually mature, they experience reduced growth , poor carcass quality ( external sex characters, reduced body fat and filet color) , and high mortality if reared in seawater . Thus, early sexual maturity before the desired market size is a serious economic drawback for the producers . Limited number of estimates are available for genetic variation of this trait in rainbow trout, but evidence suggests the presence of significant genetic variation
1-4
.
T he aim of this study was to obtain reliable estimates of genetic variation for early sexual maturity at two years of age in rainbow trout, and to search for possible quantitative trait loci (QTL) for the trait that can be used for genomic ( GS) and/or marker assisted selection (MAS).
Material and Methods
The population used in the current study originated from the breeding nucleus (year-class 2020) of Osland Genetics AS, comprising a total of 2054 fish, i.e., the offspring of 92 sires and 144 dams, with a median full- sib family size of 12 (ranging from 3-43). The fish were slaughtered at a mean body weight of 4.9 kg at about two years of age . The s exual maturity status (1 =maturing; 0 =immature) and the gender of each fish were recorded through the visual observation and palpation of gonads after the fish were killed and gutted . All the recorded individuals were genotyped using Illumina Infinium SNPs genotyping array carrying around ~22K SNPs.
Analyses: Estimates of genetic parameters were obtained using a linear mixed model(s) implemented in “ASREML, v4.2” with genomic and pedigree information. T he GWAS analysis was performed with “GCTA, v1.94” program using the “--mlma-loco” function
.
The fixed and the random effects in the applied statistical model are as follows:
w here is the vector of the observed binary sexual maturity trait (0 immature and 1 maturing ); is the overall mean; and are design matrices to relate the animal records to appropriate level of the fixed and the random genetic effects, respectively; is a vector of the fixed effect of gender , is the random animal genetic effect with , where is the genetic variance, is the genetic relationship matrix obtained using pedigree information, is a genomic relationship matrix computed using VanRaden’s method 1 ; and is the vector of random residuals with . Additionally, estimates of genetic variation for early sexual maturity trait were also obtained on the underlying liability scales using a threshold model(s).
Results and Discussion
The incidence of early sexual maturing fish at two years of age was very low (2% ); with males showing significantly higher incidence (2.3%) than females (1.7%).
The estimated genetic parameters revealed low but significant genetic variation for early sexual maturity with estimates of heritability ranging from ~0.06 to ~0.16 (Table 1) which varied across model (LM vs. TM) and source of information (pedigree vs. genomic).
The g enome-wide association analysis revealed a strong signal of a quantitative trait loci (QTL) at chromosome 28 with 27 SNPs surpassing chromosome and/or genome-wide Bonferroni corrected significant threshold (Figure 1). In spite of the low frequency of early sexually maturing fish in the current data, the highly significant SNP at chrom osome 28 explained ~31% of the total genetic variance computed using (Falconer and Mackay, 1996
). The display of a single clear QTL at chromosome 28 together with some minor indications from the SNPs located at other chromosomes (18 and 30) directs that the trait may be affected by a few gene(s) with large effect and multiple other genes with smaller effect size. The results show that the selection through GS and/or MAS can be used to further reduce incidences of undesired early sexual maturity in this population of rainbow trout.
Similar parameter estimates will also be obtained based on data from a more recent year-class (2021). In addition, we will present estimates of accuracy of prediction using cross validation scheme(s) with different models (PBLUP, GBLUP, Bayesian, and MAS) to assess and compare the potential of genomic and/or marker assisted selection over classical pedigree information.
Acknowledgement
The results of the current study are a part of the R& D agreement between NOFIMA AS and OSLAND GENETICS AS .
References
1. Crandell, P.A. & Gall, G.A.E. The genetics of age and weight at sexual maturity based on individually tagged rainbow trout (Oncorhynchus mykiss). Aquaculture 117, 95-105 (1993).
2. Quinton, C.D., et al., Genetic parameters of body weight, female spawning date, and age at sexual maturation in rainbow trout. in 7th WCGALP (Montpellier, France, 2002).
3. Gjerde, B. & Gjedrem, T. Estimates of phenotypic and genetic parameters for carcass traits in Atlantic salmon and rainbow trout. Aquaculture 36, 97-110 (1984).
4. Gjerde, B. Growth and Reproduction in Fish and Shellfish. Aquaculture 51, 37-55 (1986).
5. Yang, J., et. al., GCTA: A tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76-82 (2011).
6. Falconer, D.S. & Mackay, T.F.C. Introduction to Quantitative Genetics, (Longman Green, Harlow, Essex, UK, 1996).