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Investigations in the character of QTL affecting negatively correlated milk traits.

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Titel: Investigations in the character of QTL affecting negatively correlated milk traits.
Autoren: Freyer, G.1 freyer@fbn-dummerstorf.de, Sørensen, P.2, Kühn, C.1, Weikard, R.1
Quelle: Journal of Animal Breeding & Genetics. Feb2004, Vol. 121 Issue 1, p40-51. 12p.
Publikationsart: Article
Schlagworte: Milk yield, Holstein-Friesian cattle, Milk, Fat, Proteins, Genetics
Abstract (English): The primary aim of this study was to investigate the quantitative trait loci (QTL) on BTA6 that affect negatively correlated milk traits, using bivariate covariance component analysis of milk yield and fat (or protein) content, protein yield and fat content, and fat yield and protein content. A set of five different genetic models was adapted to differentiate trait-specific QTL in close linkage from pleiotropy. Using a grand-daughter design consisting of five half-sib families from the German Holstein population and 298 sons genotyped for 16 microsatellite markers on BTA6, we found significant trait-specific QTL for fat content and protein yield, 24 cM apart. Markers BM1329 and FBN12 bracketed the QTL for fat content, and the region between TGLA37 and FBN13 most likely harbours a QTL for protein yield. The analysis based on the close linkage model fully confirmed this result. Despite the pure QTL findings confirming results from the literature, distinguishing pleiotropic and closely linked QTL for competitive traits is a new aspect. Our multivariate analysis results did not suggest a pleiotropic QTL for the investigated negatively correlated traits. The QTL-based trait correlations were discussed as an important aspect of modelling that needs to be considered in the future. [ABSTRACT FROM AUTHOR]
Abstract (German): Das Ziel des Beitrages ist es, QTL auf BTA6 bezüglich ihrer Wirkung auf negativ korrelierte Milchleistungsmerkmale näher zu untersuchen. Die Kombinationen Milchmenge und Fett- (oder Protein-)gehalt, Proteinmenge und Fettgehalt sowie Fettmenge und Eiweißgehalt wurden jeweils einer bivariaten Covarianzanalyse unterzogen. Fünf verschiedene genetische Modelle wurden eingesetzt, um festzustellen, ob es sich um zwei eng gekoppelte QTL oder um einen pleiotrop-wirkenden QTL handelt. Das Enkellinnen-Design bestand aus fünf Halbgeschwisterfamilien aus der deutschen Holstein- Population und 298 Söhnen, genotypisiert an 16 Mikrosatellitenmarkern. Merkmalsspezifische (signifikante) QTL im Abstand von 24 cM wurden für den Fettgehalt und für die Proteinmenge gefunden. Der QTL für Fettgehalt befindet sich wahrscheinlich zwischen den Markern BM1329 und FBN12. Die Region zwischen TGLA37 und FBN13 enthält sehr wahrscheinlich einen QTL für Proteinmenge. Die auf dem ’Modell enge Kopplung’ basierende Analyse bestätigte das Ergebnis. Es gab keinen Hinweis auf einen pleiotropen QTL für die untersuchten Kombinationen negativ- korrelierter Merkmale. Obwohl die gefundenen QTL- Positionen bereits publizierte QTL bestätigen stellt die Unterscheidung zwischen pleiotropen und eng gekoppelten QTL für konkurrierende Merkmale’ einen neuen Aspekt dar. Ferner wurden die QTL-basierten Merkmalskorrelationen im Zusammenhang mit künftigen Modellerweiterungen erörtert. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Animal Breeding & Genetics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Author Affiliations: 1Research Institute for the Biology of Farm Animals, Dummerstorf, Germany.
2Danish Institute of Agricultural Sciences Research Center, Department of Animal Breeding and Genetics, Tjele, Denmark.
ISSN: 0931-2668
DOI: 10.1046/j.0931-2668.2003.00407.x
Dokumentencode: 12074651
Datenbank: Veterinary Source
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  Data: Investigations in the character of QTL affecting negatively correlated milk traits.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Animal+Breeding+%26+Genetics%22">Journal of Animal Breeding & Genetics</searchLink>. Feb2004, Vol. 121 Issue 1, p40-51. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Milk+yield%22">Milk yield</searchLink><br /><searchLink fieldCode="DE" term="%22Holstein-Friesian+cattle%22">Holstein-Friesian cattle</searchLink><br /><searchLink fieldCode="DE" term="%22Milk%22">Milk</searchLink><br /><searchLink fieldCode="DE" term="%22Fat%22">Fat</searchLink><br /><searchLink fieldCode="DE" term="%22Proteins%22">Proteins</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink>
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  Data: The primary aim of this study was to investigate the quantitative trait loci (QTL) on BTA6 that affect negatively correlated milk traits, using bivariate covariance component analysis of milk yield and fat (or protein) content, protein yield and fat content, and fat yield and protein content. A set of five different genetic models was adapted to differentiate trait-specific QTL in close linkage from pleiotropy. Using a grand-daughter design consisting of five half-sib families from the German Holstein population and 298 sons genotyped for 16 microsatellite markers on BTA6, we found significant trait-specific QTL for fat content and protein yield, 24 cM apart. Markers BM1329 and FBN12 bracketed the QTL for fat content, and the region between TGLA37 and FBN13 most likely harbours a QTL for protein yield. The analysis based on the close linkage model fully confirmed this result. Despite the pure QTL findings confirming results from the literature, distinguishing pleiotropic and closely linked QTL for competitive traits is a new aspect. Our multivariate analysis results did not suggest a pleiotropic QTL for the investigated negatively correlated traits. The QTL-based trait correlations were discussed as an important aspect of modelling that needs to be considered in the future. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (German)
  Group: Ab
  Data: Das Ziel des Beitrages ist es, QTL auf BTA6 bezüglich ihrer Wirkung auf negativ korrelierte Milchleistungsmerkmale näher zu untersuchen. Die Kombinationen Milchmenge und Fett- (oder Protein-)gehalt, Proteinmenge und Fettgehalt sowie Fettmenge und Eiweißgehalt wurden jeweils einer bivariaten Covarianzanalyse unterzogen. Fünf verschiedene genetische Modelle wurden eingesetzt, um festzustellen, ob es sich um zwei eng gekoppelte QTL oder um einen pleiotrop-wirkenden QTL handelt. Das Enkellinnen-Design bestand aus fünf Halbgeschwisterfamilien aus der deutschen Holstein- Population und 298 Söhnen, genotypisiert an 16 Mikrosatellitenmarkern. Merkmalsspezifische (signifikante) QTL im Abstand von 24 cM wurden für den Fettgehalt und für die Proteinmenge gefunden. Der QTL für Fettgehalt befindet sich wahrscheinlich zwischen den Markern BM1329 und FBN12. Die Region zwischen TGLA37 und FBN13 enthält sehr wahrscheinlich einen QTL für Proteinmenge. Die auf dem ’Modell enge Kopplung’ basierende Analyse bestätigte das Ergebnis. Es gab keinen Hinweis auf einen pleiotropen QTL für die untersuchten Kombinationen negativ- korrelierter Merkmale. Obwohl die gefundenen QTL- Positionen bereits publizierte QTL bestätigen stellt die Unterscheidung zwischen pleiotropen und eng gekoppelten QTL für konkurrierende Merkmale’ einen neuen Aspekt dar. Ferner wurden die QTL-basierten Merkmalskorrelationen im Zusammenhang mit künftigen Modellerweiterungen erörtert. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Animal Breeding & Genetics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
– Name: AffiliationAuthor
  Label: Author Affiliations
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  Data: <relatesTo>1</relatesTo>Research Institute for the Biology of Farm Animals, Dummerstorf, Germany.<br /><relatesTo>2</relatesTo>Danish Institute of Agricultural Sciences Research Center, Department of Animal Breeding and Genetics, Tjele, Denmark.
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