Quantitative Trait Locus-by-Environment Interaction for Milk Yield Traits on <i>Bos taurus</i> Autosome 6

Lillehammer, Marie; Goddard, Michael E.; Nilsen, Heidi; Sehested, E.; Olsen, Harald; Lien, Sigbjørn; Meuwissen, Theo H. E.

doi:10.1534/genetics.107.084483

Cited by 24 publications

(16 citation statements)

References 24 publications

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“…1). When GxE interaction occurs, genotypes react differently according to the environmental levels 3,7 . Indeed, different genomic variants showed a specific effect on AFC in different environmental conditions (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…2A). Some studies in dairy cattle 7,38 , pigs 8 and beef cattle 3,10 have shown that different environmental conditions can cause substantial changes in SNP effect estimates.…”

Section: Resultsmentioning

confidence: 99%

“…GxE interaction occurs when the genetic variance and/or the classification of animals change according to the environment 4,5 . The re-ranking of animals caused by GxE interaction is an indication that some genomic regions might have different effects according to the environments 6,7 .…”

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confidence: 99%

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Genome-wide scan highlights the role of candidate genes on phenotypic plasticity for age at first calving in Nellore heifers

Mota

Lopes²,

Júnior

et al. 2020

Sci Rep

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Age at first calving (AFC) plays an important role in the economic efficiency of beef cattle production. This trait can be affected by a combination of genetic and environmental factors, leading to physiological changes in response to heifers' adaptation to a wide range of environments. Genomewide association studies through the reaction norm model were carried out to identify genomic regions associated with AFC in Nellore heifers, raised under different environmental conditions (EC). The SNP effects for AFC were estimated in three EC levels (Low, Medium, and High, corresponding to average contemporary group effects on yearling body weight equal to 159.40, 228.6 and 297.6 kg, respectively), which unraveled shared and unique genomic regions for AFC in Low, Medium, and High EC levels, that varied according to the genetic correlation between AFC in different EC levels. The significant genomic regions harbored key genes that might play an important biological role in controlling hormone signaling and metabolism. Shared genomic regions among EC levels were identified on BTA 2 and 14, harboring candidate genes associated with energy metabolism (IGFBP2, IGFBP5, SHOX, SMARCAL1, LYN, RPS20, MOS, PLAG1, CHCD7, and SDR16C6). Gene set enrichment analyses identified important biological functions related to growth, hormone levels affecting female fertility, physiological processes involved in female pregnancy, gamete generation, ovulation cycle, and age at puberty. the genomic regions highlighted differences in the physiological processes linked to AFC in different EC levels and metabolic processes that support complex interactions between the gonadotropic axes and sexual precocity in nellore heifers. open Scientific RepoRtS | (2020) 10:6481 | https://doi.org/10.1038/s41598-020-63516-4 www.nature.com/scientificreports www.nature.com/scientificreports/ pathway and gene network analyses from these results can be performed to uncover mechanisms whereby the environment can potentially affect the sexual precocity in cattle. Such knowledge regarding genomic regions and biological pathways involved with GxE interactions in Nellore heifers' sexual precocity is important to identify molecular mechanisms underlying the phenotypic responses to different environments. Hence, this study was carried out to evaluate the changes in the SNP effect estimates, as well as the biological processes associated with age at first calving in three environmental conditions, combining RN models and GWAS. Materials and Methodsethics approval. The animal procedures in this study were approved by Animal Care of the São Paulo State University (UNESP), School of Agricultural and Veterinary Science Ethical Committee (protocol number 18.340/16). All the data sampling was performed in accordance with CEUA/ FCAV-UNESP guidelines and regulations.phenotypic and genotypic data. Age at first calving (AFC) records were obtained from 185,356Nellore heifers belonging to three commercial breeding programs (DeltaGen, Paint -CRV Lagoa and Cia de Melhoramento), which are p...

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Section: Resultsmentioning

confidence: 99%

“…2A). Some studies in dairy cattle 7,38 , pigs 8 and beef cattle 3,10 have shown that different environmental conditions can cause substantial changes in SNP effect estimates.…”

Section: Resultsmentioning

confidence: 99%

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Genome-wide scan highlights the role of candidate genes on phenotypic plasticity for age at first calving in Nellore heifers

Mota

Lopes²,

Júnior

et al. 2020

Sci Rep

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“…Differential animal responses across environmental conditions have been assessed through reaction norm models (RNM), describing animal sensitivity to environmental changes (Calus & Veerkamp 2003;Kolmodin et al 2003). Genomic information has been used to assess G9E interactions, representing a promising alternative to evaluating traits strongly influenced by environmental factors (Lillehammer et al 2008(Lillehammer et al , 2009Silva et al 2014;Mota et al 2016;Zhang et al 2019). According to Hayes et al (2016), the inclusion of genomic information in RNM has the potential to overcome the low quantity of phenotypic information from sires with offspring in a wide range of environments, given that the genotyped animals are well distributed across different environments.…”

Section: Introductionmentioning

confidence: 99%

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

et al. 2020

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Summary Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment‐specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re‐ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment‐specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.

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“…In the Norwegian Red, milk production QTL for ES on BTA2, BTA6, BTA7, and BTA16 were reported by Lillehammer et al (2007, 2008). A detailed analysis of BTA6 with a high marker density revealed two QTL for milk yield with an effect on ES, but no QTL with an ES effect for fat and protein yield.…”

Section: Discussionmentioning

confidence: 98%

Using Genome-Wide Association Analysis to Characterize Environmental Sensitivity of Milk Traits in Dairy Cattle

Streit

Wellmann

Reinhardt³

et al. 2013

G3 Genes|Genomes|Genetics

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Genotype-by-environment interaction (GxE) has been widely reported in dairy cattle. One way to analyze GxE is to apply reaction norm models. The first derivative of a reaction norm is the environmental sensitivity (ES). In the present study we conducted a large-scale, genome-wide association analysis to identify single-nucleotide polymorphisms (SNPs) that affect general production (GP) and ES of milk traits in the German Holstein population. Sire estimates for GP and for ES were calculated from approximately 13 million daughter records by the use of linear reaction norm models. The daughters were offspring from 2297 sires. Sires were genotyped for 54k SNPs. The environment was defined as the average milk energy yield performance of the herds at the time during which the daughter observations were recorded. The sire estimates were used as observations in a genome-wide association analysis, using 1797 sires. Significant SNPs were confirmed in an independent validation set (500 sires of the same population). To separate GxE scaling and other GxE effects, the observations were log-transformed in some analyses. Results from the reaction norm model revealed GxE effects. Numerous significant SNPs were validated for both GP and ES. Many SNPs that affect GP also affect ES. We showed that ES of milk traits is a typical quantitative trait, genetically controlled by many genes with small effects and few genes with larger effect. A log-transformation of the observation resulted in a reduced number of validated SNPs for ES, pointing to genes that not only caused scaling GxE effects. The results will have implications for breeding for robustness in dairy cattle.

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Quantitative Trait Locus-by-Environment Interaction for Milk Yield Traits on Bos taurus Autosome 6

Cited by 24 publications

References 24 publications

Genome-wide scan highlights the role of candidate genes on phenotypic plasticity for age at first calving in Nellore heifers

Genome-wide scan highlights the role of candidate genes on phenotypic plasticity for age at first calving in Nellore heifers

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Using Genome-Wide Association Analysis to Characterize Environmental Sensitivity of Milk Traits in Dairy Cattle

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