A Review and Meta-Analysis of Genotype by Environment Interaction in Commercial Shrimp Breeding

Abstract

(1) Background: Genotype-by-environment interaction (G×E) can adversely impact genetic improvement programs. The presence of G×E is mainly measured as the genetic correlation between the same trait measured in different environments where departure from unity can be taken as presence of G×E. (2) Methods: To understand the extent of G×E in shrimp production, a review and meta-analysis was conducted using the results from 32 peer-reviewed studies. (3) Results: Of these, 22 G×E studies were conducted on Pacific white shrimp (Litopenaeus vannamei) with fewer studies reported in other shrimp species. The most frequently studied traits were growth and survival, with relatively few studies on traits of economic importance. The meta-analysis demonstrated a moderately high genetic correlation (r_g = 0.72 ± 0.05) for growth, indicating low to moderate levels of G×E with some re-ranking of breeding values across environments. However, substantial G×E was evident for survival where only a moderate genetic correlation (r_g = 0.58 ± 0.07) was observed for survival across different environments. A re-ranking of breeding values is likely for this trait and genetic improvement of shrimp for survival in one environment may not be effective in other environments. The results from ANOVA-based studies show that G×E accounted for 6.42 ± 1.05% and 7.13 ± 3.46% of the variation for growth and survival traits, respectively. (4) Conclusion: The significance of G×E necessitates tailored genetic improvement programs in commercial shrimp breeding. We discuss the scope and challenges of G×E for shrimp breeding programs, including opportunities of implementing G×E in genomic selection programs.

Keywords: aquaculture; genetic correlation; genetic improvement; growth; survival.

Figure 1

Illustration of genotype-by-environment interaction (G×E) using two hypothetical genotypes across two environments. (a) Absence of G×E: Both genotypes show higher expression in environment II, with genotype 1 (red) consistently outperforming genotype 2 (green). (b) Heterogeneity of genetic variance: The performance gap between genotypes widens in environment II compared with environment I, indicating a mild G×E. (c) Re-ranking of genotypes: A strong G×E is demonstrated, where genotype 1 performs better in environment I, while genotype 2 excels in environment II. This crossover interaction shows how each genotype is better adapted to a specific environment.

Figure 2

Distribution of r_g across studies of G×E in shrimp species shown as boxplots based on (a) three trait groups (growth, survival and other) and (b) across two different environmental classification (habitat type and stress). Boxplots show median (central line), interquartile range (box), and range (whiskers, extending to 1.5 times the interquartile range) of r_g values. Points beyond whiskers represent potential outliers. r_g values closer to 1 suggest weaker G×E effects, while values closer to 0 or less indicate stronger G×E effects.

Figure 3

Boxplots of percent of phenotypic variation explained by G×E in ANOVA-based studies for growth and survival traits. Boxplots show median (central line), interquartile range (box), and range (whiskers, extending to 1.5 times the interquartile range) of % variation explained. Points beyond whiskers represent potential outliers.