BackgroundBesides having an impact on human health, the porcine muscle fatty acid profile determines meat quality and taste. The RNA-Seq technologies allowed us to explore the pig muscle transcriptome with an unprecedented detail. The aim of this study was to identify differentially-expressed genes between two groups of 6 sows belonging to an Iberian × Landrace backcross with extreme phenotypes according to FA profile.ResultsWe sequenced the muscle transcriptome acquiring 787.5 M of 75 bp paired-end reads. About 85.1% of reads were mapped to the reference genome. Of the total reads, 79.1% were located in exons, 6.0% in introns and 14.9% in intergenic regions, indicating expressed regions not annotated in the reference genome. We identified a 34.5% of the intergenic regions as interspersed repetitive regions. We predicted a total of 2,372 putative proteins. Pathway analysis with 131 differentially-expressed genes revealed that the most statistically-significant metabolic pathways were related with lipid metabolism. Moreover, 18 of the differentially-expressed genes were located in genomic regions associated with IMF composition in an independent GWAS study in the same genetic background. Thus, our results indicate that the lipid metabolism of FAs is differently modulated when the FA composition in muscle differs. For instance, a high content of PUFA may reduce FA and glucose uptake resulting in an inhibition of the lipogenesis. These results are consistent with previous studies of our group analysing the liver and the adipose tissue transcriptomes providing a view of each of the main organs involved in lipid metabolism.ConclusionsThe results obtained in the muscle transcriptome analysis increase the knowledge of the gene regulation of IMF deposition, FA profile and meat quality, in terms of taste and nutritional value. Besides, our results may be important in terms of human health.

Current statistical approaches to investigate the nature and magnitude of transmission ratio distortion (TRD) are scarce and restricted to the most common experimental designs such as F 2 populations and backcrosses. In this article, we describe a new Bayesian approach to check TRD within a given biallelic genetic marker in a diploid species, providing a highly flexible framework that can accommodate any kind of population structure. This model relies on the genotype of each offspring and thus integrates all available information from either the parents' genotypes or population-specific allele frequencies and yields TRD estimates that can be corroborated by the calculation of a Bayes factor (BF). This approach has been evaluated on simulated data sets with appealing statistical performance. As a proof of concept, we have also tested TRD in a porcine population with five half-sib families and 352 offspring. All boars and piglets were genotyped with the Porcine SNP60 BeadChip, whereas genotypes from the sows were not available. The SNP-by-SNP screening of the pig genome revealed 84 SNPs with decisive evidences of TRD (BF . 100) after accounting for multiple testing. Many of these regions contained genes related to biological processes (e.g., nucleosome assembly and co-organization, DNA conformation and packaging, and DNA complex assembly) that are critically associated with embryonic viability. The implementation of this method, which overcomes many of the limitations of previous approaches, should contribute to fostering research on TRD in both model and nonmodel organisms.

The aim of this study was to investigate 96 single-nucleotide polymorphisms (SNPs) from 54 candidate genes, and test the associations of the polymorphic SNPs with milk yield, composition, milk urea nitrogen (MUN) content and somatic cell score (SCS) in individual milk samples from Italian Brown Swiss cows. Milk and blood samples were collected from 1271 cows sampled once from 85 herds. Milk production, quality traits (i.e. protein, casein, fat and lactose percentages), MUN and SCS were measured for each milk sample. Genotyping was performed using a custom Illumina VeraCode GoldenGate approach. A Bayesian linear animal model that considered the effects of herd, days in milk, parity, SNP genotype and additive polygenic effect was used for the association analysis. Our results showed that 14 of the 51 polymorphic SNPs had relevant additive effects on at least one of the aforementioned traits. Polymorphisms in the glucocorticoid receptor DNA-binding factor 1 ( GRLF1), prolactin receptor ( PRLR) and chemokine ligand 2 ( CCL2) were associated with milk yield; an SNP in the stearoyl-CoA desaturase ( SCD-1) was related to fat content; SNPs in the caspase recruitment domain 15 protein ( CARD15) and lipin 1 ( LPIN1) affected the protein and casein contents; SNPs in growth hormone 1 ( GH1), lactotransferrin ( LTF) and SCD-1 were relevant for casein number; variants in beta casein ( CSN2), GH1, GRLF1 and LTF affected lactose content; SNPs in beta-2 adrenergic receptor (ADRB2), serpin peptidase inhibitor (PI) and SCD-1 were associated with MUN; and SNPs in acetyl-CoA carboxylase alpha (ACACA) and signal transducer and activator of transcription 5A ( STAT5A) were relevant in explaining the variation of SCS. Although further research is needed to validate these SNPs in other populations and breeds, the association between these markers and milk yield, composition, MUN and SCS could be exploited in gene-assisted selection programs for genetic improvement purposes.

Inbred mice were essential animal models for scientific research during the 20th century and will contribute decisive results in the current and next centuries. Far from becoming an obsolete research tool, the generation of new inbred strains is continuing and such strains are being used in many research fields. However, their genetic properties have been overlooked for decades, although recent research has revealed new insights into their genetic fragility and relative instability. Contrary to what we usually assume, inbred mice are far from being completely isogenic and both single-gene major mutations and polygenic mutational variability are continuously uploading into inbred populations as new sources of genetic polymorphisms. Note that several inbred strains from new major mutations are released every year, whereas small mutations can accumulate up to accounting for a significant percentage of the phenotypic variance (e.g. 4.5% in a recent study on C57BL/6J mice). Moreover, this genetic heterogeneity can be maintained for several generations by heterozygote selection and, if fixed instead of dropping off, genetic drift must be anticipated. The contribution of accidental genetic contamination in inbred strains must also be considered, although its incidence in current breeding stocks should be minimal, or even negligible. This review revisits several relevant topics for current inbred strains, discussing the latest cutting-edge results within the context of the genetic homogeneity and stability of laboratory mice. Inbred mice can no longer be considered as completely isogenic, but provide a remarkably homogeneous animal model with an inevitable moderate-to-low degree of genetic variability. Despite a certain degree of genetic heterogeneity becoming inescapable, inbred mice still provide very useful animal models with evident advantages when compared with outbred, that is, highly variable, populations.Keywords: heterozygote selection, inbred strain, isogenicity, mouse, mutation Implications Inbred mice are basic tools for multiple research fields. Despite their relevance, their genetic architecture was overlooked for decades and recent research evidenced their genetic fragility, and even instability. Within this context, this review revisits several hot topics for current inbred strains, discussing the latest cutting-edge results on mutation and genetic drift, and characterizing other sources of genetic heterogeneity such as heterozygote selection or contamination. Far from invalidating the usefulness of inbred mice in research, this review was an attempt to describe the different sources of allogenicity and warns about potential consequences on the genetic stability of mice.