Breeding for robustness: investigating the genotype‐by‐environment interaction and micro‐environmental sensitivity of Genetically Improved Farmed Tilapia (Oreochromis niloticus). (30th July 2018)

• Record Type: Journal Article
• Authors: Agha, S.; Mekkawy, W.; Ibanez‐Escriche, N.; Lind, C. E.; Kumar, J.; Mandal, A.; Benzie, J. A. H.; Doeschl‐Wilson, A.
• Is Part Of: Animal genetics. Volume 49:Number 5(2018)
• Page Start: 421
• Page End: 427
• Publication Date: 2018-07-30
• Subjects: aquaculture breeding -- genetic heterogeneity of environmental variance -- Nile tilapia -- resilience; Animal genetics -- Periodicals; 572.8
• DOI: 10.1111/age.12680
• Languages: English
• ISSNs: 0268-9146

Abstract

Summary: Robustness has become a highly desirable breeding goal in the globalized agricultural market. Both genotype‐by‐environment interaction (G × E) and micro‐environmental sensitivity are important robustness components of aquaculture production, in which breeding stock is often disseminated to different environments. The objectives of this study were (i) to quantify the degree of G × E by assessing the growth performance of Genetically Improved Farmed Tilapia (GIFT) across three countries (Malaysia, India and China) and (ii) to quantify the genetic heterogeneity of environmental variance for body weight at harvest (BW) in GIFT as a measure of micro‐environmental sensitivity. Selection for BW was carried out for 13 generations in Malaysia. Subsets of 60 full‐sib families from Malaysia were sent to China and India after five and nine generations respectively. First, a multi‐trait animal model was used to analyse the BW in different countries as different traits. The results indicate a strong G × E. Second, a genetically structured environmental variance model, implemented using Bayesian inference, was used to analyse micro‐environmental sensitivity of BW in each country. The analysis revealed the presence of genetic heterogeneity of both BW and its environmental variance in all environments. The presence of genetic variation in residual variance of BW implies that the residual variance can be modified by selection. Incorporating both G × E and micro‐environmental sensitivity information may help in selecting robust genotypes with high performance across environments and resilience to environmental fluctuations.