Mapping, fine mapping, and molecular dissection of quantitative trait loci in domestic animals

Georges, Michel

doi:10.1146/annurev.genom.8.080706.092408

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Mapping, fine mapping, and molecular dissection of quantitative trait loci in domestic animals

Georges, Michel

2007 • In Annual Review of Genomics and Human Genetics, 8, p. 131-162

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10.1146/annurev.genom.8.080706.092408

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17477823

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Keywords :

positional cloning; genetical genomics; genomic selection

Abstract :

[en] Artificial selection has created myriad breeds of domestic animals, each characterized by unique phenotypes pertaining to behavior, morphology, physiology, and disease. Most domestic animal populations share features with isolated founder populations, making them well suited for positional cloning. Genome sequences are now available for most domestic species, and with them a panoply of tools including high-density single-nucleotide polymorphism panels. As a result, domestic animal populations are becoming invaluable resources for studying the molecular architecture of complex traits and of adaptation. Here we review recent progress and issues in the positional identification of genes underlying complex traits in domestic animals. As many phenotypes studied in animals are quantitative, we focus on mapping, fine mapping, and cloning of quantitative trait loci.

Research Center/Unit :

Giga-Genetics - ULiège

Disciplines :

Veterinary medicine & animal health

Author, co-author :

Georges, Michel ; Université de Liège - ULiège > Département de productions animales > Génomique animale

Language :

English

Title :

Mapping, fine mapping, and molecular dissection of quantitative trait loci in domestic animals

Publication date :

2007

Journal title :

Annual Review of Genomics and Human Genetics

ISSN :

1527-8204

eISSN :

1545-293X

Publisher :

Annual Reviews, Palo Alto, United States - Florida

Volume :

Pages :

131-162

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 08 December 2009

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107

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without self-citations

102

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133

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