Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels

Abstract

Background One of the most important goals for the rainbow trout aquaculture industry is to improve fillet yield and fillet quality. Previously, we showed that a 50 K transcribed-SNP chip can be used to detect quantitative trait loci (QTL) associated with fillet yield and fillet firmness. In this study, data from 1568 fish genotyped for the 50 K transcribed-SNP chip and ~ 774 fish phenotyped for fillet yield and fillet firmness were used in a single-step genomic BLUP (ssGBLUP) model to compute the genomic estimated breeding values (GEBV). In addition, pedigree-based best linear unbiased prediction (PBLUP) was used to calculate traditional, family-based estimated breeding values (EBV). Results The genomic predictions outperformed the traditional EBV by 35% for fillet yield and 42% for fillet firmness. The predictive ability for fillet yield and fillet firmness was 0.19–0.20 with PBLUP, and 0.27 with ssGBLUP. Additionally, reducing SNP panel densities indicated that using 500–800 SNPs in genomic predictions still provides predictive abilities higher than PBLUP. Conclusion These results suggest that genomic evaluation is a feasible strategy to identify and select fish with superior genetic merit within rainbow trout families, even with low-density SNP panels.

Genotyping Strategies Using ddRAD Sequencing in Farmed Arctic Charr (Salvelinus alpinus)

“…Our association study for length and log 2 transformed condition factor (K) confirmed that the density of the marker set is crucial when conducting genome-wide regression studies in aquatic animal populations [49][50][51]. All SNPs of the high coverage set failed to reach the genome-wide adjusted significance threshold for both studied traits.…”

Optimizing self-pollinated crop breeding employing genomic selection: from schemes to updating training sets

“…This study used a SNP chip containing 1,000 markers to simulate the SNP-panel optimized for the IRRI irrigated breeding program (Arbelaez et al 2019). Low-density SNP panels are attractive for GS due to the lower price per sample and have been explored by several groups (Vallejo et al, 2018;Arbelaez et al, 2019;Al-Tobasei et al, 2021).…”

“…This study used a SNP chip containing 1,000 markers to simulate the SNP-panel optimized for the IRRI irrigated breeding program (Arbelaez et al 2019). Low-density SNP panels are attractive for GS due to the lower price per sample and have been explored by several groups (Vallejo et al, 2018;Arbelaez et al, 2019;Al-Tobasei et al, 2021). In this context, our results showed that updating the TS with an affordable size reduced the accuracy decline over breeding cycles, presenting a lower decay than other studies (Neyhart et al 2017;Muleta et al 2019), even using a low-density marker set.…”

Overview of Gulf of Mottama Wetland (GoMW) & Size Distribution and Economic Status of Sea Bass in Myanmar

“…This study focused on morphological study of sea bass fish and economic value change in local area of Myanmar. By length and body weight of sea bass can generally obtain highest prices and the demands of sea bass in local area are higher more and more and the residents favor the taste of sea bass [6,8,10,70,115]. The more abundance populations of sea bass can be found in Kokko and Kyuntone villages than other villages along The Gulf of Mottama Wetland (GoMW).…”

“…Figure(6) shows the job status of Kokko Tan village according to number of male under 18 years old. In the total amount of 517 people of Kokko Tan village, 428 people are working fishery, 80 people have their own farm land and paddy fields, 278 people are farmhands, 50 people are transporting workers, 96 people are government staffs, 12 people are grocery owners, 103 are merchants, 23 are students and in the total amount of 517 people of Kyuntone village, 67 people are working fishery, 18 people have their own farm land and paddy fields, 121 people are farmhands, 23 people are transporting workers, 52 people are government staffs, 7 people are grocery owners, 7 are merchants and 23 are students.…”