Genome-enabled prediction of quantitative traits in chickens using genomic annotation

Gota Morota, Rostam Abdollahi-Arpanahi, Andreas Kranis, Daniel Gianola

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Background: Genome-wide association studies have been deemed successful for identifying statistically associated genetic variants of large effects on complex traits. Past studies have found enrichment of trait-associated SNPs in functionally annotated regions, while depletion was reported for intergenic regions (IGR). However, no systematic examination of connections between genomic regions and predictive ability of complex phenotypes has been carried out.Results: In this study, we partitioned SNPs based on their annotation to characterize genomic regions that deliver low and high predictive power for three broiler traits in chickens using a whole-genome approach. Additive genomic relationship kernels were constructed for each of the genic regions considered, and a kernel-based Bayesian ridge regression was employed as prediction machine. We found that the predictive performance for ultrasound area of breast meat from using genic regions marked by SNPs was consistently better than that from SNPs in IGR, while IGR tagged by SNPs were better than the genic regions for body weight and hen house egg production. We also noted that predictive ability delivered by the whole battery of markers was close to the best prediction achieved by one of the genomic regions.Conclusions: Whole-genome regression methods use all available quality filtered SNPs into a model, contrary to accommodating only validated SNPs from exonic or coding regions. Our results suggest that, while differences among genomic regions in terms of predictive ability were observed, the whole-genome approach remains as a promising tool if interest is on prediction of complex traits.

Original languageEnglish (US)
Article number109
JournalBMC genomics
Volume15
Issue number1
DOIs
StatePublished - Feb 7 2014

Fingerprint

Single Nucleotide Polymorphism
Chickens
Genome
Intergenic DNA
Genome-Wide Association Study
Meat
Ovum
Breast
Body Weight
Phenotype

Keywords

  • Annotation
  • Chicken
  • SNP
  • Whole-genome prediction

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

Cite this

Genome-enabled prediction of quantitative traits in chickens using genomic annotation. / Morota, Gota; Abdollahi-Arpanahi, Rostam; Kranis, Andreas; Gianola, Daniel.

In: BMC genomics, Vol. 15, No. 1, 109, 07.02.2014.

Research output: Contribution to journalArticle

Morota, Gota ; Abdollahi-Arpanahi, Rostam ; Kranis, Andreas ; Gianola, Daniel. / Genome-enabled prediction of quantitative traits in chickens using genomic annotation. In: BMC genomics. 2014 ; Vol. 15, No. 1.
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