Literature DB >> 19841231

Overlapping chromosomal regions for fertility traits and production traits in the Danish Holstein population.

J K Höglund1, A J Buitenhuis, B Guldbrandtsen, G Su, B Thomsen, M S Lund.   

Abstract

Before implementing selection based on quantitative trait loci (QTL) for fertility, it is important to determine the existence of correlated effects between the fertility QTL and QTL with effects on production traits. When a QTL is detected for a trait that is a composite of subtraits, it is of interest to validate which of the subtraits are affected by the QTL. Phenotypic and marker data were collected from 34 grandsire families from the Danish Holstein population. First, the trait data for "fertility treatments" were separated into their underlying subtraits: uterine infections, antibiotics placed in the placenta, and abortions. In addition, retained placenta was selected for analysis because it is related to uterine infections. A genome scan was performed using 416 microsatellite markers for the fertility treatment subtraits and retained placenta, and an additional genome scan for milk production traits conditional on the QTL regions for the subtraits and retained placenta was conducted. Second, we selected 24 genomic regions harboring QTL for fertility traits from a previous study. A QTL scan for milk production traits conditional on the selected regions was conducted. We found that 16 selected genomic regions containing a QTL for fertility (including the fertility treatment subtraits and retained placenta) also harbored QTL for milk yield or milk composition traits. Furthermore, 12 QTL regions corresponding to 9 different fertility traits (including the fertility treatment subtraits) did not harbor a QTL for milk production or milk composition traits; that is, the region was specific for the fertility trait. The genome scan for the fertility treatment subtraits did not correspond to the QTL found for fertility treatments. No QTL were detected for the subtrait abortion, however genome scans for retained placenta revealed 4 different QTL.

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Year:  2009        PMID: 19841231     DOI: 10.3168/jds.2008-1964

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  7 in total

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Authors:  Jinghang Zhou; Liyuan Liu; Chunpeng James Chen; Menghua Zhang; Xin Lu; Zhiwu Zhang; Xixia Huang; Yuangang Shi
Journal:  BMC Genomics       Date:  2019-11-08       Impact factor: 3.969

2.  Effect of the myostatin locus on muscle mass and intramuscular fat content in a cross between mouse lines selected for hypermuscularity.

Authors:  Stefan Kärst; Eva M Strucken; Armin O Schmitt; Alexandra Weyrich; Fernando P M de Villena; Hyuna Yang; Gudrun A Brockmann
Journal:  BMC Genomics       Date:  2013-01-16       Impact factor: 3.969

3.  Genome wide analysis of fertility and production traits in Italian Holstein cattle.

Authors:  Giulietta Minozzi; Ezequiel L Nicolazzi; Alessandra Stella; Stefano Biffani; Riccardo Negrini; Barbara Lazzari; Paolo Ajmone-Marsan; John L Williams
Journal:  PLoS One       Date:  2013-11-12       Impact factor: 3.240

4.  High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs, and novel candidate genes influencing cow milk traits.

Authors:  Eveline M Ibeagha-Awemu; Sunday O Peters; Kingsley A Akwanji; Ikhide G Imumorin; Xin Zhao
Journal:  Sci Rep       Date:  2016-08-10       Impact factor: 4.379

5.  Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle.

Authors:  Shadi Nayeri; Mehdi Sargolzaei; Mohammed K Abo-Ismail; Natalie May; Stephen P Miller; Flavio Schenkel; Stephen S Moore; Paul Stothard
Journal:  BMC Genet       Date:  2016-06-10       Impact factor: 2.797

6.  Genetic Markers Associated with Field PRRSV-Induced Abortion Rates.

Authors:  Ramona N Pena; Carlos Fernández; María Blasco-Felip; Lorenzo J Fraile; Joan Estany
Journal:  Viruses       Date:  2019-08-01       Impact factor: 5.048

7.  Genome-wide association study of beef bull semen attributes.

Authors:  M L Butler; A R Hartman; J M Bormann; R L Weaber; D M Grieger; M M Rolf
Journal:  BMC Genomics       Date:  2022-01-23       Impact factor: 3.969

  7 in total

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