Journal cover Journal topic
Archives Animal Breeding Archiv Tierzucht
Journal topic

Journal metrics

Journal metrics

  • IF value: 1.203 IF 1.203
  • IF 5-year value: 1.203 IF 5-year 1.203
  • CiteScore value: 0.98 CiteScore 0.98
  • SNIP value: 0.920 SNIP 0.920
  • SJR value: 0.390 SJR 0.390
  • IPP value: 0.89 IPP 0.89
  • h5-index value: 11 h5-index 11
  • Scimago H index value: 23 Scimago H index 23
Supported by
Logo Leibniz Institute for Farm Animal Biology Logo Leibniz Association
Volume 60, issue 3 | Copyright
Arch. Anim. Breed., 60, 335-346, 2017
https://doi.org/10.5194/aab-60-335-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Review 29 Sep 2017

Review | 29 Sep 2017

Invited review: Genome-wide association analysis for quantitative traits in livestock – a selective review of statistical models and experimental designs

Markus Schmid and Jörn Bennewitz Markus Schmid and Jörn Bennewitz
  • University Hohenheim, Institute of Animal Science, Garbenstrasse 17, 70599 Stuttgart, Germany

Abstract. Quantitative or complex traits are controlled by many genes and environmental factors. Most traits in livestock breeding are quantitative traits. Mapping genes and causative mutations generating the genetic variance of these traits is still a very active area of research in livestock genetics. Since genome-wide and dense SNP panels are available for most livestock species, genome-wide association studies (GWASs) have become the method of choice in mapping experiments. Different statistical models are used for GWASs. We will review the frequently used single-marker models and additionally describe Bayesian multi-marker models. The importance of nonadditive genetic and genotype-by-environment effects along with GWAS methods to detect them will be briefly discussed. Different mapping populations are used and will also be reviewed. Whenever possible, our own real-data examples are included to illustrate the reviewed methods and designs. Future research directions including post-GWAS strategies are outlined.

Download & links
Download
Citation
Share