Investigating genotype by environment interaction for beef cattle fertility traits in commercial herds in northern Australia with multi-trait analysis

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Genetics Selection Evolution Pub Date : 2024-10-31 DOI:10.1186/s12711-024-00936-0
James P. Copley, Benjamin J. Hayes, Elizabeth M. Ross, Shannon Speight, Geoffry Fordyce, Benjamin J. Wood, Bailey N. Engle
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Abstract

Genotype by environment interactions (GxE) affect a range of production traits in beef cattle. Quantifying the effect of GxE in commercial and multi-breed herds is challenging due to unknown genetic linkage between animals across environment levels. The primary aim of this study was to use multi-trait models to investigate GxE for three heifer fertility traits, corpus luteum (CL) presence, first pregnancy and second pregnancy, in a large tropical beef multibreed dataset (n = 21,037). Environmental levels were defined by two different descriptors, burden of heat load (temperature humidity index, THI) and nutritional availability (based on mean average daily gain for the herd, ADWG). To separate the effects of genetic linkage and real GxE across the environments, 1000 replicates of a simulated phenotype were generated by simulating QTL effects with no GxE onto real marker genotypes from the population, to determine the genetic correlations that could be expected across environments due to the existing genetic linkage only. Correlations from the real phenotypes were then compared to the empirical distribution under the null hypothesis from the simulated data. By adopting this approach, this study attempted to establish if low genetic correlations between environmental levels were due to GxE or insufficient genetic linkage between animals in each environmental level. The correlations (being less than <0.8) for the real phenotypes were indicative of GxE for CL presence between ADWG environmental levels and in pregnancy traits. However, none of the correlations for CL presence or first pregnancy between ADWG levels were below the 5th percentile value for the empirical distribution under the null hypothesis from the simulated data. Only one statistically significant (P < 0.05) indication of GxE for first pregnancy was found between THI environmental levels, where rg = 0.28 and 5th percentile value = 0.29, and this result was marginal. Only one case of statistically significant GxE for fertility traits was detected for first pregnancy between THI environmental levels 2 and 3. Other initial indications of GxE that were observed from the real phenotypes did not prove significant when compared to an empirical null distribution from simulated phenotypes. The lack of compelling evidence of GxE indicates that direct selection for fertility traits can be made accurately, using a single evaluation, regardless of environment.
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通过多性状分析调查澳大利亚北部商业牛群中肉牛繁殖力性状的基因型与环境的交互作用
基因型与环境的相互作用(GxE)会影响肉牛的一系列生产性状。由于不同环境水平下动物之间的遗传联系未知,因此量化 GxE 对商业牛群和多品种牛群的影响具有挑战性。本研究的主要目的是在一个大型热带肉牛多品种数据集(n = 21,037)中,使用多性状模型研究 GxE 对黄体(CL)存在、首次妊娠和第二次妊娠这三个母牛繁殖性状的影响。环境水平由两个不同的描述因子定义,即热负荷(温度湿度指数,THI)和营养供应(基于牛群平均日增重,ADWG)。为了区分遗传连锁和真实 GxE 在不同环境中的影响,通过将无 GxE 的 QTL 效应模拟到种群的真实标记基因型上,生成了 1000 个重复的模拟表型,以确定仅由于现有的遗传连锁而可能在不同环境中产生的遗传相关性。然后将真实表型的相关性与模拟数据零假设下的经验分布进行比较。通过采用这种方法,本研究试图确定环境水平之间的低遗传相关性是由于 GxE 还是由于各环境水平中动物之间的遗传联系不足。实际表型的相关性(小于<0.8)表明,ADWG 环境水平与妊娠性状之间的 CL 存在 GxE。然而,在模拟数据的零假设下,ADWG 水平与 CL 存在或首次怀孕之间的相关性均不低于经验分布的第 5 百分位值。在 THI 环境水平之间只发现了一个具有统计学意义(P < 0.05)的 GxE 显示,即 rg = 0.28 和第 5 百分位值 = 0.29,而且这个结果是边缘性的。在 THI 环境水平 2 和 3 之间,仅发现一例具有统计学意义的初孕生殖力性状 GxE。从实际表型中观察到的其他 GxE 初步迹象与模拟表型的经验零分布相比并不显著。缺乏令人信服的 GxE 证据表明,无论环境如何,都可以通过单一评价对育种性状进行准确的直接选择。
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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