Animal Science, Department of

 

ORCID IDs

Stephen D. Kachman

Document Type

Article

Date of this Version

2017

Citation

J. Anim. Sci. 2017.95:4196–4205

doi:10.2527/jas2016.1334

Comments

© 2017 American Society of Animal Science.

Abstract

Genetic variants associated with traits such as age at puberty and litter size could provide insight into the underlying genetic sources of variation impacting sow reproductive longevity and productivity. Genomewide characterization and gene expression profiling were used using gilts from the University of Nebraska–Lincoln swine resource population (n = 1,644) to identify genetic variants associated with age at puberty and litter size traits. From all reproductive traits studied, the largest fraction of phenotypic variation explained by the Porcine SNP60 BeadArray was for age at puberty (27.3%). In an evaluation data set, the predictive ability of all SNP from highranked 1-Mb windows (1 to 50%), based on genetic variance explained in training, was greater (12.3 to 36.8%) compared with the most informative SNP from these windows (6.5 to 23.7%). In the integrated data set (n = 1,644), the top 1% of the 1-Mb windows explained 6.7% of the genetic variation of age at puberty. One of the high-ranked windows detected (SSC2, 12–12.9 Mb) showed pleiotropic features, affecting both age at puberty and litter size traits. The RNA sequencing of the hypothalami arcuate nucleus uncovered 17 differentially expressed genes (adjusted P < 0.05) between gilts that became pubertal early (180 d of age). Twelve of the differentially expressed genes are upregulated in the late pubertal gilts. One of these genes is involved in energy homeostasis (FFAR2), a function in which the arcuate nucleus plays an important contribution, linking nutrition with reproductive development. Energy restriction during the gilt development period delayed age at puberty by 7 d but increased the probability of a sow to produce up to 3 parities (P < 0.05). Identification of pleotropic functional polymorphisms may improve accuracy of genomic prediction while facilitating a reduction in sow replacement rates and addressing welfare concerns.

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