Literature DB >> 12729552

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle.

Jörn Bennewitz1, Norbert Reinsch, Cécile Grohs, Hubert Levéziel, Alain Malafosse, Hauke Thomsen, Ningying Xu, Christian Looft, Christa Kühn, Gudrun A Brockmann, Manfred Schwerin, Christina Weimann, Stefan Hiendleder, Georg Erhardt, Ivica Medjugorac, Ingolf Russ, Martin Förster, Bertram Brenig, Fritz Reinhardt, Reinhard Reents, Gottfried Averdunk, Jürgen Blümel, Didier Boichard, Ernst Kalm.   

Abstract

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.

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Year:  2003        PMID: 12729552      PMCID: PMC2732702          DOI: 10.1186/1297-9686-35-3-319

Source DB:  PubMed          Journal:  Genet Sel Evol        ISSN: 0999-193X            Impact factor:   4.297


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  21 in total

1.  Multiple quantitative trait loci mapping with cofactors and application of alternative variants of the false discovery rate in an enlarged granddaughter design.

Authors:  Jörn Bennewitz; Norbert Reinsch; Volker Guiard; Sebastien Fritz; Hauke Thomsen; Christian Looft; Christa Kühn; Manfred Schwerin; Christina Weimann; Georg Erhardt; Fritz Reinhardt; Reinhard Reents; Didier Boichard; Ernst Kalm
Journal:  Genetics       Date:  2004-10       Impact factor: 4.562

2.  The number of loci that affect milk production traits in dairy cattle.

Authors:  Amanda Jane Chamberlain; Helen Clare McPartlan; Michael Edward Goddard
Journal:  Genetics       Date:  2007-08-24       Impact factor: 4.562

3.  Mapping of a milk production quantitative trait locus to a 1.056 Mb region on bovine chromosome 5 in the Fleckvieh dual purpose cattle breed.

Authors:  Ashraf Awad; Ingolf Russ; Martin Förster; Ivica Medugorac
Journal:  Genet Sel Evol       Date:  2011-02-24       Impact factor: 4.297

4.  Fine mapping and physical characterization of two linked quantitative trait loci affecting milk fat yield in dairy cattle on BTA26.

Authors:  Mathieu Gautier; Rosa Roy Barcelona; Sébastien Fritz; Cécile Grohs; Tom Druet; Didier Boichard; André Eggen; Theo H E Meuwissen
Journal:  Genetics       Date:  2005-09-19       Impact factor: 4.562

5.  Study on the STAT5A/AvaI polymorphism in Jersey cows and association with milk production traits.

Authors:  Cataldo Dario; Maria Selvaggi
Journal:  Mol Biol Rep       Date:  2011-03-09       Impact factor: 2.316

6.  BRCA1: a new candidate gene for bovine mastitis and its association analysis between single nucleotide polymorphisms and milk somatic cell score.

Authors:  Zhengrong Yuan; Guiyan Chu; Yang Dan; Jiao Li; Lupei Zhang; Xue Gao; Huijiang Gao; Junya Li; Shangzhong Xu; Zhihua Liu
Journal:  Mol Biol Rep       Date:  2012-02-12       Impact factor: 2.316

7.  Targeted generation of 16 sequence-tagged sites for bovine chromosome region 5q21-q25 by microdissection.

Authors:  Tom Goldammer; Karin Rottengatter; Rosemarie Weikard; Rolf Horstmann; Annette Gehlhaus; Ronald M Brunner; Olivier Hanotte; Manfred Schwerin
Journal:  Chromosome Res       Date:  2004       Impact factor: 5.239

8.  Genome wide association studies for milk production traits in Chinese Holstein population.

Authors:  Li Jiang; Jianfeng Liu; Dongxiao Sun; Peipei Ma; Xiangdong Ding; Ying Yu; Qin Zhang
Journal:  PLoS One       Date:  2010-10-27       Impact factor: 3.240

9.  Combining two Meishan F2 crosses improves the detection of QTL on pig chromosomes 2, 4 and 6.

Authors:  Flavie Tortereau; Hélène Gilbert; Henri C M Heuven; Jean-Pierre Bidanel; Martien A M Groenen; Juliette Riquet
Journal:  Genet Sel Evol       Date:  2010-11-25       Impact factor: 4.297

10.  Joint QTL analysis of three connected F2-crosses in pigs.

Authors:  Christine Rückert; Jörn Bennewitz
Journal:  Genet Sel Evol       Date:  2010-11-01       Impact factor: 4.297

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