Literature DB >> 20720303

Mutations in the bovine ABCG2 and the ovine MSTN gene added to the few quantitative trait nucleotides identified in farm animals: a mini-review.

M H Braunschweig1.   

Abstract

The progress in molecular genetics in animal breeding is moderately effective as compared to traditional animal breeding using quantitative genetic approaches. There is an extensive disparity between the number of reported quantitative trait loci (QTLs) and their linked genetic variations in cattle, pig, and chicken. The identification of causative mutations affecting quantitative traits is still very challenging and hampered by the cloudy relationship between genotype and phenotype. There are relatively few reports in which a successful identification of a causative mutation for an animal production trait was demonstrated. The examples that have attracted considerable attention from the animal breeding community are briefly summarized and presented in a table. In this mini-review, the recent progress in mapping quantitative trait nucleotides (QTNs) are reviewed, including the ABCG2 gene mutation that underlies a QTL for fat and protein content and the ovine MSTN gene mutation that causes muscular hypertrophy in Texel sheep. It is concluded that the progress in molecular genetics might facilitate the elucidation of the genetic architecture of QTLs, so that also the high-hanging fruits can be harvested in order to contribute to efficient and sustainable animal production.

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Year:  2010        PMID: 20720303     DOI: 10.1007/BF03208858

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   2.653


  56 in total

1.  Haplotype sharing refines the location of an imprinted quantitative trait locus with major effect on muscle mass to a 250-kb chromosome segment containing the porcine IGF2 gene.

Authors:  Carine Nezer; Catherine Collette; Laurence Moreau; Benoît Brouwers; Jong-Joo Kim; Elisabetta Giuffra; Nadine Buys; Leif Andersson; Michel Georges
Journal:  Genetics       Date:  2003-09       Impact factor: 4.562

Review 2.  Domestic-animal genomics: deciphering the genetics of complex traits.

Authors:  Leif Andersson; Michel Georges
Journal:  Nat Rev Genet       Date:  2004-03       Impact factor: 53.242

3.  Invited review: reliability of genomic predictions for North American Holstein bulls.

Authors:  P M VanRaden; C P Van Tassell; G R Wiggans; T S Sonstegard; R D Schnabel; J F Taylor; F S Schenkel
Journal:  J Dairy Sci       Date:  2009-01       Impact factor: 4.034

4.  A deletion in the bovine myostatin gene causes the double-muscled phenotype in cattle.

Authors:  L Grobet; L J Martin; D Poncelet; D Pirottin; B Brouwers; J Riquet; A Schoeberlein; S Dunner; F Ménissier; J Massabanda; R Fries; R Hanset; M Georges
Journal:  Nat Genet       Date:  1997-09       Impact factor: 38.330

5.  IGF2 antisense transcript expression in porcine postnatal muscle is affected by a quantitative trait nucleotide in intron 3.

Authors:  Martin H Braunschweig; Anne-Sophie Van Laere; Nadine Buys; Leif Andersson; Göran Andersson
Journal:  Genomics       Date:  2004-12       Impact factor: 5.736

Review 6.  Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems.

Authors:  Patrick C Phillips
Journal:  Nat Rev Genet       Date:  2008-11       Impact factor: 53.242

7.  A frameshift mutation in the coding region of the myostatin gene (MSTN) affects carcass conformation and fatness in Norwegian White Sheep (Ovis aries).

Authors:  I A Boman; G Klemetsdal; T Blichfeldt; O Nafstad; D I Våge
Journal:  Anim Genet       Date:  2009-03-23       Impact factor: 3.169

Review 8.  Revealing the architecture of gene regulation: the promise of eQTL studies.

Authors:  Yoav Gilad; Scott A Rifkin; Jonathan K Pritchard
Journal:  Trends Genet       Date:  2008-07-01       Impact factor: 11.639

9.  Polymorphisms in the ovine myostatin gene (MSTN) and their association with growth and carcass traits in New Zealand Romney sheep.

Authors:  J G H Hickford; R H Forrest; H Zhou; Q Fang; J Han; C M Frampton; A L Horrell
Journal:  Anim Genet       Date:  2009-10-01       Impact factor: 3.169

10.  Genome-wide identification of quantitative trait loci in a cross between Hampshire and Landrace II: meat quality traits.

Authors:  Ellen Markljung; Martin H Braunschweig; Peter Karlskov-Mortensen; Camilla S Bruun; Milena Sawera; In-Cheol Cho; Ingela Hedebro-Velander; Asa Josell; Kerstin Lundström; Gertrud von Seth; Claus B Jørgensen; Merete Fredholm; Leif Andersson
Journal:  BMC Genet       Date:  2008-02-28       Impact factor: 2.797

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  6 in total

1.  Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle.

Authors:  Irene van den Berg; Didier Boichard; Mogens S Lund
Journal:  Genet Sel Evol       Date:  2016-11-04       Impact factor: 4.297

2.  Genes contributing to genetic variation of muscling in sheep.

Authors:  Ross L Tellam; Noelle E Cockett; Tony Vuocolo; Christopher A Bidwell
Journal:  Front Genet       Date:  2012-08-29       Impact factor: 4.599

3.  QTL fine mapping with Bayes C(π): a simulation study.

Authors:  Irene van den Berg; Sébastien Fritz; Didier Boichard
Journal:  Genet Sel Evol       Date:  2013-06-19       Impact factor: 4.297

4.  Concordance analysis for QTL detection in dairy cattle: a case study of leg morphology.

Authors:  Irene van den Berg; Sébastien Fritz; Sabrina Rodriguez; Dominique Rocha; Mekki Boussaha; Mogens S Lund; Didier Boichard
Journal:  Genet Sel Evol       Date:  2014-05-19       Impact factor: 4.297

5.  A Meta-Assembly of Selection Signatures in Cattle.

Authors:  Imtiaz A S Randhawa; Mehar S Khatkar; Peter C Thomson; Herman W Raadsma
Journal:  PLoS One       Date:  2016-04-05       Impact factor: 3.240

6.  Using Sequence Variants in Linkage Disequilibrium with Causative Mutations to Improve Across-Breed Prediction in Dairy Cattle: A Simulation Study.

Authors:  Irene van den Berg; Didier Boichard; Bernt Guldbrandtsen; Mogens S Lund
Journal:  G3 (Bethesda)       Date:  2016-08-09       Impact factor: 3.154

  6 in total

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