Use of the Multivariate Discriminant Analysis for Genome-Wide Association Studies in Cattle.

Genome-wide association studies (GWAS) are traditionally carried out by using the single marker regression model that, if a small number of individuals is involved, often lead to very few associations. The Bayesian methods, such as BayesR, have obtained encouraging results when they are applied to the GWAS. However, these approaches, require that an a priori posterior inclusion probability threshold be fixed, thus arbitrarily affecting the obtained associations. To partially overcome these problems, a multivariate statistical algorithm was proposed. The basic idea was that animals with different phenotypic values of a specific trait share different allelic combinations for genes involved in its determinism. Three multivariate techniques were used to highlight the differences between the individuals assembled in high and low phenotype groups: the canonical discriminant analysis, the discriminant analysis and the stepwise discriminant analysis. The multivariate method was tested both on simulated and on real data. The results from the simulation study highlighted that the multivariate GWAS detected a greater number of true associated single nucleotide polymorphisms (SNPs) and Quantitative trait loci (QTLs) than the single marker model and the Bayesian approach. For example, with 3000 animals, the traditional GWAS highlighted only 29 significantly associated markers and 13 QTLs, whereas the multivariate method found 127 associated SNPs and 65 QTLs. The gap between the two approaches slowly decreased as the number of animals increased. The Bayesian method gave worse results than the other two. On average, with the real data, the multivariate GWAS found 108 associated markers for each trait under study and among them, around 63% SNPs were also found in the single marker approach. Among the top 118 associated markers, 76 SNPs harbored putative candidate genes.

Effect of dietary polyunsaturated fatty acid and antioxidant supplementation on the transcriptional level of genes involved in lipid and energy metabolism in swine.

Porcine fat traits depend mostly on the interaction between nutritional and genetic factors. However, the pathways and biological processes influenced by this interaction are still poorly known in pigs, although they can have a huge impact on meat quality traits. The present research provides new knowledge insight into the effect of four diets (D1 = standard diet; D2 = linseed supplementation; D3 = linseed, vitamin E and selenium supplementation; D4 = linseed and plant-derived polyphenols supplementation) on the expression of 24 candidate genes selected for their role in lipid and energy metabolism. The data indicated that 10 out of 24 genes were differentially expressed among diets, namely ACACA, ADIPOQ, ADIPOR1, CHREBP (MLXPL), ELOVL6, FASN, G6PD, PLIN2, RXRA and SCD. Results from the univariate analysis displayed an increased expression of ACACA, ADIPOQ, ADIPOR1, CHREBP, ELOVL6, FASN, PLIN2, RXRA and SCD in D4 compared to D2. Similarly, ACACA, ADIPOQ, ADIPOR1, ELOVL6 and SCD were highly expressed in D4 compared to D3, while no differences were observed in D2-D3 comparison. Moreover, an increased expression of G6PD and ELOVL6 genes in D4 compared to D1 was observed. Results from the multivariate analysis confirmed that D2 was not different from D3 and that ACACA, SCD and FASN expression made D4 different from D2 and D3. Comparing D4 and D1, the expression levels of ELOVL6 and ACACA were the most influenced. This research provides evidence that the addition of both n-3 PUFA and polyphenols, derived from linseed, grape-skin and oregano supplementation in the diets, stimulates the expression of genes involved in lipogenesis and in oxidative processes. Results evidenced a greater effect on gene expression of the diet added with both plant extracts and n-3 PUFA, resulting in an increased expression of genes coding for fatty acid synthesis, desaturation and elongation in pig Longissimus thoracis muscle.

Chemokines and pro-inflammatory cytokines in Down's syndrome: an early marker for Alzheimer-type dementia?

BACKGROUND: People with Down's syndrome (DS) show early Alzheimer-like dementia. It has been suggested that the pro-inflammatory cytokine class plays a role in Alzheimer's disease (AD). The study aims at verifying whether pro-inflammatory cytokines in DS are correlated with age, affective symptoms and intellectual decline to a different degree than in subjects with non-DS learning disabilities. CASES: 19 subjects with DS; controls: sex- and age-matched individuals with learning disabilities caused by perinatal ischaemic damage. The level of mental retardation was assessed according to DSM-IV; psychopathological symptoms were measured by the Assessment and Information Rating Profile. Serum levels of cytokines were determined with ELISA. RESULTS: DS patients showed higher levels of cytokines and chemokines, with the exception of RANTES; but the only significant difference detected was for MIP-1alpha. A correlation between the degree of mental retardation and IL-6, and between MIP-lalpha and age was found in patients with DS, but not in controls. CONCLUSIONS: The data obtained suggest a possible involvement of chemokines in the inflammatory and degenerative processes similar to AD in DS. Further longitudinal research is required to confirm these findings.