Genotype by environment interaction for activity-based estrus traits in relation to production level for Danish Holstein

Abstract

The objective of this study was to investigate whether genotype by environment interaction exists for female fertility traits and production of energy-corrected milk at 70d in milk (ECM70). Fertility traits considered were the activity-based estrus traits interval from calving to first high activity (CFHA), duration of high activity episode (DHA), as an indicator for first estrus duration, and strength of high activity episode (SHA), as an indicator for first estrus strength. The physical activity traits were derived from electronic activity tags for 11,522 first-parity cows housed in 125 commercial dairy herds. Data were analyzed using a univariate random regression animal model (URRM), by regressing the phenotypic performance on the average herd ECM70 as an environmental gradient. Furthermore, the genetic correlations between CFHA and ECM70 as a function of production level were estimated using a bivariate random regression animal model (BRRM). For all traits, heterogeneity of additive genetic variances and heritability estimates was observed. The heritability estimate for CFHA decreased from 0.25 to 0.10 with increasing production level and the heritability estimate for ECM70 decreased from 0.35 to 0.15 with increasing production level using URRM. The genetic correlation of the same trait in low and high production levels was around 0.74 for CFHA and 0.80 for ECM70 using URRM, but when data were analyzed using the multiple-trait analysis (MT), genetic correlation estimates between low and high production levels were not significantly different from unity. Furthermore, the genetic correlation of SHA between low and high production level was 0.22 using URRM, but the corresponding correlation estimate had large standard error when data were analyzed using MT. The genetic correlation between CFHA and ECM70 as a function of production environment was weak but unfavorable and decreased slightly from 0.09 to 0.04 with increasing production level using BRRM. Moreover, the same trend was observed when the data were analyzed using MT where the genetic correlation between CFHA and ECM70 in the low production environment was 0.29 compared with -0.13 in the high production environment, but these estimates had large standard errors. In conclusion, regardless of the trait used, in relation to average herd ECM70 production, the results indicated no clear evidence of strong genotype by environment interaction that would cause significant re-ranking of sires between low and high production environments.

Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models

“…A recent study found the genetic variances of production traits varied at different THI levels, and a quadratic curve was observed in the heritabilities of protein yield [8]. In Danish Holstein populations, heterogeneities of heritabilities of several fertility traits were observed across different production levels or grass ratio in feed [6,33]. Although heritabilities vary across EGs in different analyses, patterns of heritabilities with changes in the environment are predictable.…”

Genotype-by-environment Interaction in Holstein Heifer Fertility Traits using Single-step Genomic Reaction Norm Models

“…A recent study found the genetic variances of production traits varied in different THI levels, and a quadratic curve was observed in the heritabilities of protein yield [8]. In Danish Holstein populations, heterogeneities of heritabilities of several fertility traits were observed across different production levels or grass ratio in feed [6,33] Based on the t-test for the variance of the slope, a statistically significant GE was observed for all traits in this study [5]. Moderate to strong negative correlations were detected between the intercept and slope for each trait.…”

“…G×E exists if the variance of the slope was significantly different from zero by using a one-tailed t-test with the significance level of 0.05 [6,33]. One possible consequence of G×E is the re-ranking of animals across different environments [5];…”

Genotype-environment interaction for age at first calving in Holstein cows in Brazil

“…According to Nesser, Van Wyk and Ducrocq (2014) , the bull selection is important because selected animals should be adapted to the environmental conditions according to the locations in which their progeny will be raised. Thus, several studies have been carried out worldwide to identify the presence of GEI in Holstein herds to improve milking period ( Ismael et al., 2016a ), milk production ( Tiezzi, Los Campos, Parker Gaddis & Maltecca, 2017 ; Tsuruta, Lourenco, Misztal & Lawlort, 2015 ), fat and protein percentages, and somatic cell counts ( Streit, Reinhardt, Thaller & Bennewitz, 2013 ; Tiezzi et al., 2017 ).…”