Potential functional variants in AHR signaling pathways are associated with age at puberty in swine

Clustering of multi-tissue transcriptomes in gilts with normal cyclicity or delayed puberty reveals genes related to pubertal development†

In gilts, puberty is marked by standing estrus in the presence of a boar. Delayed puberty (DP; failure to display pubertal estrus) is a major reason for gilt removal. To investigate the physiological determinants underlying DP in gilts, transcriptomic data from tissues relevant to estrus and puberty, such as mediobasal hypothalamus, anterior pituitary gland, ovarian cortex, olfactory bulb, amygdala, and hippocampus, were obtained from age-matched DP (n = 8) and cyclic control gilts at follicular phase (n = 8) and luteal phase (n = 8) of the estrous cycle. A gene expression module analysis via three-way gene × individual × tissue clustering using tensor decomposition identified pituitary and ovary gene modules contributing to regulation of pubertal development. Analysis of gene expression in the hypothalamic-pituitary-ovary axis identified reduced expression of hypothalamic genes critical for stimulating gonadotropin secretion (KISS1 and TAC3) and reduced expression of LHB in the anterior pituitary of DP gilts compared with their cyclic counterparts. Consequently, luteinizing hormone-induced genes in the ovary important for folliculogenesis (OXTR, RUNX2, and PTX3) were less expressed in DP gilts. Other intrafollicular genes (AHR, PTGS2, PTGFR, and IGFBP7) and genes in the steroidogenesis pathways (STAR and CYP11A1) necessary to complete the ovulatory cascade were also less expressed in DP gilts. This is the first clustering of multi-tissue expression data from DP and cyclic gilts to identify genes differentially expressed in gilts of similar ages but at different levels of sexual development. A critical lack of gonadotropin support and reduced ovarian responsiveness underlie DP in gilts.

Functional genomics of reproduction in pigs: Are we there yet?

Reproductive failure is the main reason for culling females in swine herds and is both a financial and sustainability issue. Because reproductive traits are complex and lowly to moderately heritable, genomic selection within populations can achieve substantial genetic gain in reproductive efficiency. A better understanding of the physiological components affecting the expression of these traits will facilitate greater understanding of the genes affecting reproductive traits and is necessary to improve and optimize management strategies to maximize reproductive success of gilts and sows. Large-scale genotyping with single-nucleotide polymorphism (SNP) arrays are used for genome-wide association studies (GWAS) and have facilitated identification of positional candidate genes. Transcriptomic data can be used to weight SNP for GWAS and could lead to previously unidentified candidate genes. Resequencing and fine mapping of candidate genes are necessary to identify putative functional variants and some of these have been incorporated into new genotyping arrays. Sequence imputation and genotype by sequence are newer strategies that could reveal novel functional mutations. In this study, these approaches are discussed. Advantages and limitations are highlighted where additional research is needed.

Relationships of genomic estimated breeding values for age at puberty, birth weight, and growth during development in normal cyclic and acyclic gilts

Managing replacement gilts to reach optimal body weight and growth rate for boar stimulation and first breeding is a key component for sow reproductive longevity and producer profitability. Failure to display pubertal estrus remains a major reason that gilts are culled from the herd. Puberty is metabolically gated so evaluating phenotypic and genetic relationships between birth weight and growth traits with age at puberty and acyclicity can provide valuable insight for efficient gilt development. Data on a litter of origin of the gilt, average daily gain at different stages of development, and age at puberty were available for age-matched cyclic (n = 4,861) and acyclic gilts (prepubertal anestrus, n = 578; behavioral anestrus, n = 428). Genomic estimated breeding values were predicted for each trait using genomic best linear unbiased prediction. Primiparous sows produced more acyclic gilts than multiparous sows (P < 0.05). Accounting for effects of parity and litter size, prepubertal anestrus gilts were heavier at birth and behaviorally anestrus gilts grew faster during the finisher period compared to cyclic gilts (P < 0.05), reflecting possible prenatal programming that negatively affects optimal pubertal development and antagonistic effects between adolescent growth and expression of estrus of gilts from first parity sows. Regression of phenotypic age at puberty with lifetime growth rate (birth to selection) showed a negative linear relationship whereas genomic estimated breeding values showed a negative quadratic relationship indicating that gilts with the least and greatest growth are less optimal as replacements. The slopes of these relationships are small with low negative phenotypic (r = -0.06) and genetic correlations (r = -0.13). The addition of data from acyclic gilts did not substantially change the estimates for genetic relationships between growth and pubertal onset. Although this study identified differences in birth weight and growth rate between cyclic and acyclic gilts the genetic relationships are weak, suggesting that genetic selection for these traits can be achieved separately. Avoiding the smallest and largest gilts in a cohort born to first parity sows could result in gilts with optimal development and reduce the proportion of replacement gilts that are acyclic.

Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs

Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.