Polymorphisms of the porcine cathepsins, growth hormone-releasing hormone and leptin receptor genes and their association with meat quality traits in Ukrainian Large White breed

© 2016, The Author(s). Cathepsins, growth hormone-releasing hormone (GHRH) and leptin receptor (LEPR) genes have been receiving increasing attention as potential markers for meat quality and pig performance traits. This study investigated the allele variants in four cathepsin genes (CTSB, CTSK, CTSL, CTSS), GHRH and LEPR in pure-bred Ukrainian Large White pigs and evaluated effects of the allele variants on meat quality characteristics. The study was conducted on 72 pigs. Genotyping was performed using PCR–RFLP technique. Meat quality characteristics analysed were intramuscular fat content, tenderness, total water content, ultimate pH, crude protein and ashes. A medium level of heterozygosity values was established for GHRH and LEPR genes which corresponded to very high levels of informativeness indexes. Cathepsins CTSL, CTSB and CTSK had a low level of heterozygosity, and CTSS did not segregate in this breed. Association studies established that intramuscular fat content and tenderness were affected by the allele variance in GHRH and LEPR but not by CTSB and CTSL genes. The GHRH results could be particularly relevant for the production of lean prime cuts as the A allele is associated with both, a lower meat fat content and better tenderness values, which are two attributes highly regarded by consumers. Results of this study suggest that selective breeding towards GHRH/AA genotype would be particularly useful for improving meat quality characteristics in the production systems involving lean Large White lines, which typically have less than 2% intramuscular fat content

Differences in muscle transcriptome among pigs phenotypically extreme for fatty acid composition

Contains fulltext : 137788.pdf (publisher's version ) (Open Access)BACKGROUND: Besides 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 x Landrace backcross with extreme phenotypes according to FA profile. RESULTS: We 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. CONCLUSIONS: The 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

Identification of genes regulating growth and fatness traits in pig through hypothalamic transcriptome analysis

Previous studies on Iberian x Landrace (IBMAP) pig intercrosses have enabled the identification of several QTL regions related to growth and fatness traits; however the genetic variation underlying those QTLs are still unknown. These traits are not only relevant because of their impact on economically important production traits, but also because pig constitutes a widely studied animal model for human obesity and obesity related diseases. The hypothalamus is the main gland regulating growth, food intake and fat accumulation. Therefore, the aim of this work was to identify genes and/or gene transcripts involved in the determination of growth and fatness in pig by a comparison of the whole hypothalamic transcriptome (RNA-seq) in two groups of phenotypically divergent IBMAP pigs. Around 16,000 of the ~25.010 annotated genes were expressed in these hypothalamic samples, with most of them showing intermediate expression levels. Functional analyses supported the key role of the hypothalamus in the regulation of growth, fat accumulation and energy expenditure. Besides, 58,927 potentially new isoforms were detected. More than 250 differentially expressed genes and novel transcript isoforms were identified between the two groups of pigs. Twenty-one DE genes/transcripts that co-localized in previously identified QTL regions and/or whose biological functions are related to the traits of interest were explored in more detail. Additionally, the transcription factors potentially regulating these genes and the subjacent networks and pathways were also analyzed. This study allows us to propose strong candidate genes for growth and fatness based on expression patterns, genomic location and network interaction

Using RNASeq SNP data to reveal potential causal mutations related to pig production traits and RNA editing

This is the peer reviewed version of the following article: Martinez, A. M. , Fernández, A. , Perez-Montarelo, D. , Alves, E. , Benitez, R.M., Nuñez, Y. , Oviló, C. , Ibañez Escriche, Noelia, Folch, J.M., Fernandez, A.I.. (2016). Using RNASeq SNP data to reveal potential causal mutations related to pig production traits and RNA editing.Animal Genetics, 48, 2, 151-165. DOI: 10.1111/age.12507, which has been published in final form at http://doi.org/10.1111/age.12507. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] RNA-Seq technology is widely used in quantitative gene expression studies and identification of non-annotated transcripts. However this technology also can be used for polymorphism detection and RNA editing in transcribed regions in an efficient and costeffective way. This study used SNP data from an RNA-Seq assay to identify genes and mutations underlying production trait variations in an experimental pig population. The hypothalamic and hepatic transcriptomes of nine extreme animals for growth and fatness from an (Iberian x Landrace) x Landrace backcross were analyzed by RNA-Seq methodology, and SNP calling was conducted. More than 125 000 single nucleotide variants (SNVs) were identified in each tissue, and 78% were considered to be potential SNPs, those SNVs segregating in the context of this study. Potential informative SNPs were detected by considering those showing a homozygous or heterozygous genotype in one extreme group and the alternative genotype in the other group. In this way, 4396 and 1862 informative SNPs were detected in hypothalamus and liver respectively. Out of the 32 SNPs selected for validation, 25 (80%) were confirmed as actual SNPs. Association analyses for growth, fatness and premium cut yields with 19 selected SNPs were carried out, and four potential causal genes (RETSAT, COPA, RNMT and PALMD) were identified. Interestingly, new RNA editing modifications were detected and validated for the NR3C1: g. 102797 (ss1985401074) and ACSM2B: g. 13374 (ss1985401075) positions and for the COG3: g3.4525 (ss1985401087) modification previously identified across vertebrates, which could lead to phenotypic variation and should be further investigated.This work was funded by Ministerio de Ciencia e Innovacion (MICINN) project AGL2011-29821-C02. AngelMartinez-Montes was funded by a (FPI) PhD grant from the Spanish Ministerio de Ciencia e Innovacion. We wish to thank Fabian Garcia and Anna Castello for technical assistance, Luis Silio for manuscript corrections and Beatriz Villanueva for comments, suggestions and English style corrections.Martinez, AM.; Fernández, A.; Perez-Montarelo, D.; Alves, E.; Benitez, R.; Nuñez, Y.; Oviló, C.... (2016). Using RNASeq SNP data to reveal potential causal mutations related to pig production traits and RNA editing. Animal Genetics. 48(2):151-165. https://doi.org/10.1111/age.12507S15116548