BackgroundReproductive traits play a key role in pig production in order to reduce costs and increase economic returns. Among others, gene expression analyses represent a useful approach to study genetic mechanisms underlying reproductive traits in pigs. The application of reverse-transcription quantitative PCR requires the selection of appropriate reference genes, whose expression levels should not be affected by the experimental conditions, especially when comparing gene expression across different physiological stages.ResultsThe gene expression stability of ten potential reference genes was studied by three different methods (geNorm, NormFinder and BestKeeper) in ovary and uterus collected at five different physiological time points (heat, and 15, 30, 45 and 60 days of pregnancy). Although final ranking differed, the three algorithms gave very similar results. Thus, the most stable genes across time were TBP and UBC in uterus and TBP and HPRT1 in ovary, while HMBS and ACTB showed the less stable expression in uterus and ovary, respectively. When studied as a systematic effect, the reproductive stage did not significantly affect the expression of the candidate reference genes except at 30d and 60d of pregnancy, when a general drop in expression was observed in ovary.ConclusionsBased in our results, we propose the use of TBP, UBC and SDHA in uterus and TBP, GNB2L1 and HPRT1 in ovary for normalization of longitudinal expression studies using quantitative PCR in sows.

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Teat number is an important trait in sows that should accompany the increase in litter size that has been achieved in the last decades through selection. We have previously identified a genome-wide significant QTL for teat number in porcine chromosome SSC5 by means of an experimental Meishan by Iberian F(2) intercross population. In the present report, we have studied the porcine parathyroid hormone-like hormone (PTHLH) gene, which maps to SSC5, as a candidate gene for this trait, as PTHLH is involved in nipple formation during embryogenesis and nipple development during pregnancy and lactation. We have found that porcine PTHLH gene is transcribed into three mRNA species differing in the 5'UTR region. Two of these variants are reported in pigs here for the first time: one was similar to variant 1 described in humans while the other, which was generated by the retention of two small introns, has not been identified before in any other species. In addition, mRNA expression profile for two of the mRNA variants was assessed in 19 pig tissues. Porcine PTHLH showed a widespread expression as it was present in all tested tissues and relative expression of each variant was tissue dependent. Finally, we have performed an association study between a non-synonymous mutation in the coding region of this gene and sow teat number. The PTHLH polymorphism was segregating in our Meishan by Iberian F(2) population at intermediate allelic frequencies. We compared here six different statistical models to choose the one with a better fit and a lower degree of complexity. However, despite the potential negative effect of the PTHLH mutation in the signal peptide of this protein, we did not detect any association between the PTHLH genotype and the sow teat number phenotype, concluding that the causal mutation of the observed QTL is very likely not related to this gene.

The aim of this study was to investigate chromosomal regions affecting gestation length in sows. An experimental F 2 cross between Iberian and Meishan pig breeds was used for this purpose and we genotyped 119 markers covering the 18 porcine autosomal chromosomes. Within this context, we have developed a new empirical Bayes factor (BF) approach to compare between nested models, with and without the quantitative trait loci (QTL) effect, and after including the location of the QTL as an unknown parameter in the model. This empirical BF can be easily calculated from the output of a Markov chain Monte Carlo sampling by averaging conditional densities at the null QTL effects. Linkage analyses were performed in each chromosome using an animal model to account for infinitesimal genetic effects. Initially, three QTL were detected at chromosomes 6, 8 and 11 although, after correcting for multiple testing, only the additive QTL located in cM 110 of chromosome 8 remained. For this QTL, the allelic effect of substitution of the Iberian allele increased gestation length in 0.521 days, with a highest posterior density region at 95% ranged between 0.121 and 0.972 days. Although future studies are necessary to confirm if detected QTL is relevant and segregating in commercial pig populations, a hot-spot on the genetic regulation of gestation length in pigs seems to be located in chromosome 8.

Differential gene expression analyses typically focus on departures across mathematical expectations (i.e. mean) from two or more groups of microarrays, without considering alternative patterns of departure. Nevertheless, recent studies in humans and great apes have suggested that differential gene expression could also be characterized in terms of heterogeneous dispersion patterns. This must be viewed as a very interesting genetic phenomenon clearly linked to the regulation mechanisms of gene transcription. Unfortunately, we completely lack information about the incidence and relevance of dispersion-specific differential gene expression in livestock species, although a specific Bayes factor (BF) for testing this kind of differential gene expression (i.e. within-probe heteroskedasticity) has been recently developed. Within this context, our main objective was to characterize the incidence of dispersion-specific differential gene expression in pigs and, if possible, providing the first evidence of this phenomenon in a livestock species. We evaluated dispersion-specific differential gene expression on ovary, uterus and hypophysis samples from 22 F2 Iberian × Meishan sows, where a total of 15 252 probes were interrogated. For each tissue, heteroskedasticity of probe-specific residual variances was evaluated by three pairwise comparisons involving three physiological stages, that is, heat, 15 days of pregnancy and 45 days of pregnancy. Between 2.9% and 37.4% of the analyzed probes provided statistical evidence of within-tissue across-physiological stages dispersion-specific differential gene expression (BF >1), and between 0.1% and 3.0% of them reported decisive evidence (BF >100). It is important to highlight that <8% of the heteroskedastic probes were also linked to differential gene expression in terms of departures among the probe-specific mathematical expectation of each physiological stage. This discarded the disturbance of scale effects in a high percentage of probes and suggested that probe-specific heteroskedasticity must be viewed as an independent phenomenon within the context of differential gene expression. As a whole, our results report a remarkable incidence of dispersion-specific differential gene expression across the whole genome of the pig, establishing a very interesting starting point for further studies focused on deciphering the genetic mechanisms underlying heteroskedasticity.