Genotype by Environment Interaction for Production Traits While Accounting for Heteroscedasticity

Grazing (G) provides an alternative management system for dairy production. Heteroscedasticity (HV) of the data may bias estimates of genetic correlations of yield traits between environments, an indicator of genotype-by-environment interaction (G×E). The objective of this study was to investigate t...

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Veröffentlicht in:Journal of dairy science 2007-08, Vol.90 (8), p.3889-3899
Hauptverfasser: Fahey, A.G., Schutz, M.M., Lofgren, D.L., Schinckel, A.P., Stewart, T.S.
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container_end_page 3899
container_issue 8
container_start_page 3889
container_title Journal of dairy science
container_volume 90
creator Fahey, A.G.
Schutz, M.M.
Lofgren, D.L.
Schinckel, A.P.
Stewart, T.S.
description Grazing (G) provides an alternative management system for dairy production. Heteroscedasticity (HV) of the data may bias estimates of genetic correlations of yield traits between environments, an indicator of genotype-by-environment interaction (G×E). The objective of this study was to investigate the effect of HV on estimates of heritabilities and genetic correlations for mature-equivalent milk, protein, and fat yield, and lactation-average somatic cell scores of daughters, and to determine if HV affects the ability of sire's predicted transmitting ability (PTA) to predict daughter production in G and confinement (C) herds. Data consisted of 72,489 records from 35,674 cows in 366G herds from 11 states, and 117,629 records from 50,963 cows in 373C herds from the same 11 states plus 1 geographically contiguous state. Herds were divided into variance quartiles (QV1–QV4) based on milk yield. A transformation was used to reduce HV by standardizing the within-herd standard deviation to the average across-herd standard deviation of a base year for each parity, and was similar to the method used in current USDA-DHIA genetic evaluations. Regression of daughter yield on sire PTA showed that PTA overestimated production of all traits in QV1–QV3 and of milk in QV4 of G herds. For C herds, yields of milk in QV1 and QV2, and of protein and fat in QV1 were overestimated, and protein was underestimated in QV4. Reducing HV had little effect on G herds, but for C herds, regression did not differ from unity for milk and protein in QV1 and QV2. For milk, protein, and fat in G, heritabilities were approximately 0.17, 0.17, and 0.19, respectively. The heritabilities for milk, protein, and fat in C herds were approximately 0.16, 0.17, and 0.21, respectively. Genetic correlations between C and G did not suggest a G×E in 3 upper quartiles, but a possible G×E (correlation = 0.21, estimated standard error = 0.22) for the lowest quartile. Reducing HV did not affect estimates of heritabilities or genetic correlations. Results indicated that modest evidence for existence of G×E did not arise solely from HV.
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Heteroscedasticity (HV) of the data may bias estimates of genetic correlations of yield traits between environments, an indicator of genotype-by-environment interaction (G×E). The objective of this study was to investigate the effect of HV on estimates of heritabilities and genetic correlations for mature-equivalent milk, protein, and fat yield, and lactation-average somatic cell scores of daughters, and to determine if HV affects the ability of sire's predicted transmitting ability (PTA) to predict daughter production in G and confinement (C) herds. Data consisted of 72,489 records from 35,674 cows in 366G herds from 11 states, and 117,629 records from 50,963 cows in 373C herds from the same 11 states plus 1 geographically contiguous state. Herds were divided into variance quartiles (QV1–QV4) based on milk yield. 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Psychology ; genetic correlation ; Genetic Variation - genetics ; Genotype ; genotype-environment interaction ; grazing ; heritability ; heteroscedasticity ; Lactation - genetics ; Lactation - physiology ; Linear Models ; Male ; Milk - chemistry ; Milk - cytology ; Milk and cheese industries. 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Heteroscedasticity (HV) of the data may bias estimates of genetic correlations of yield traits between environments, an indicator of genotype-by-environment interaction (G×E). The objective of this study was to investigate the effect of HV on estimates of heritabilities and genetic correlations for mature-equivalent milk, protein, and fat yield, and lactation-average somatic cell scores of daughters, and to determine if HV affects the ability of sire's predicted transmitting ability (PTA) to predict daughter production in G and confinement (C) herds. Data consisted of 72,489 records from 35,674 cows in 366G herds from 11 states, and 117,629 records from 50,963 cows in 373C herds from the same 11 states plus 1 geographically contiguous state. Herds were divided into variance quartiles (QV1–QV4) based on milk yield. 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Heteroscedasticity (HV) of the data may bias estimates of genetic correlations of yield traits between environments, an indicator of genotype-by-environment interaction (G×E). The objective of this study was to investigate the effect of HV on estimates of heritabilities and genetic correlations for mature-equivalent milk, protein, and fat yield, and lactation-average somatic cell scores of daughters, and to determine if HV affects the ability of sire's predicted transmitting ability (PTA) to predict daughter production in G and confinement (C) herds. Data consisted of 72,489 records from 35,674 cows in 366G herds from 11 states, and 117,629 records from 50,963 cows in 373C herds from the same 11 states plus 1 geographically contiguous state. Herds were divided into variance quartiles (QV1–QV4) based on milk yield. A transformation was used to reduce HV by standardizing the within-herd standard deviation to the average across-herd standard deviation of a base year for each parity, and was similar to the method used in current USDA-DHIA genetic evaluations. Regression of daughter yield on sire PTA showed that PTA overestimated production of all traits in QV1–QV3 and of milk in QV4 of G herds. For C herds, yields of milk in QV1 and QV2, and of protein and fat in QV1 were overestimated, and protein was underestimated in QV4. Reducing HV had little effect on G herds, but for C herds, regression did not differ from unity for milk and protein in QV1 and QV2. For milk, protein, and fat in G, heritabilities were approximately 0.17, 0.17, and 0.19, respectively. The heritabilities for milk, protein, and fat in C herds were approximately 0.16, 0.17, and 0.21, respectively. Genetic correlations between C and G did not suggest a G×E in 3 upper quartiles, but a possible G×E (correlation = 0.21, estimated standard error = 0.22) for the lowest quartile. Reducing HV did not affect estimates of heritabilities or genetic correlations. Results indicated that modest evidence for existence of G×E did not arise solely from HV.</abstract><cop>Savoy, IL</cop><pub>Elsevier Inc</pub><pmid>17639000</pmid><doi>10.3168/jds.2006-699</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
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subjects Animal productions
Animals
Biological and medical sciences
breeding value
Cattle - genetics
Cattle - physiology
dairy cattle
Dairying - methods
daughters
Environment
Fats
Female
Food industries
Fundamental and applied biological sciences. Psychology
genetic correlation
Genetic Variation - genetics
Genotype
genotype-environment interaction
grazing
heritability
heteroscedasticity
Lactation - genetics
Lactation - physiology
Linear Models
Male
Milk - chemistry
Milk - cytology
Milk and cheese industries. Ice creams
milk composition
Milk Proteins
milk yield
Phenotype
phenotypic variation
Statistics as Topic
Terrestrial animal productions
traits
United States
variance
variance quartile
Vertebrates
title Genotype by Environment Interaction for Production Traits While Accounting for Heteroscedasticity
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