Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models
Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univaria...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sociedade Brasileira de Genética
2009-01-01
|
| Series: | Genetics and Molecular Biology |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572009000200013 |
| _version_ | 1819057709510557696 |
|---|---|
| author | Newton T. Pégolo Henrique N. Oliveira Lúcia G. Albuquerque Luiz Antonio F. Bezerra Raysildo B. Lôbo |
| author_facet | Newton T. Pégolo Henrique N. Oliveira Lúcia G. Albuquerque Luiz Antonio F. Bezerra Raysildo B. Lôbo |
| author_sort | Newton T. Pégolo |
| collection | DOAJ |
| description | Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001). |
| first_indexed | 2024-12-21T13:43:37Z |
| format | Article |
| id | doaj.art-9e0d0c2e065844d491b656167973f433 |
| institution | Directory Open Access Journal |
| issn | 1415-4757 1678-4685 |
| language | English |
| last_indexed | 2024-12-21T13:43:37Z |
| publishDate | 2009-01-01 |
| publisher | Sociedade Brasileira de Genética |
| record_format | Article |
| series | Genetics and Molecular Biology |
| spelling | doaj.art-9e0d0c2e065844d491b656167973f4332022-12-21T19:01:57ZengSociedade Brasileira de GenéticaGenetics and Molecular Biology1415-47571678-46852009-01-01322281287Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm modelsNewton T. PégoloHenrique N. OliveiraLúcia G. AlbuquerqueLuiz Antonio F. BezerraRaysildo B. LôboGenotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001).http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572009000200013growthgenotype by environment interactionplasticityrandom regressionrobustness |
| spellingShingle | Newton T. Pégolo Henrique N. Oliveira Lúcia G. Albuquerque Luiz Antonio F. Bezerra Raysildo B. Lôbo Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models Genetics and Molecular Biology growth genotype by environment interaction plasticity random regression robustness |
| title | Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models |
| title_full | Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models |
| title_fullStr | Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models |
| title_full_unstemmed | Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models |
| title_short | Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models |
| title_sort | genotype by environment interaction for 450 day weight of nelore cattle analyzed by reaction norm models |
| topic | growth genotype by environment interaction plasticity random regression robustness |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572009000200013 |
| work_keys_str_mv | AT newtontpegolo genotypebyenvironmentinteractionfor450dayweightofnelorecattleanalyzedbyreactionnormmodels AT henriquenoliveira genotypebyenvironmentinteractionfor450dayweightofnelorecattleanalyzedbyreactionnormmodels AT luciagalbuquerque genotypebyenvironmentinteractionfor450dayweightofnelorecattleanalyzedbyreactionnormmodels AT luizantoniofbezerra genotypebyenvironmentinteractionfor450dayweightofnelorecattleanalyzedbyreactionnormmodels AT raysildoblobo genotypebyenvironmentinteractionfor450dayweightofnelorecattleanalyzedbyreactionnormmodels |