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

Mediterranean River Buffalo CSN1S1 gene: search for polymorphisms and association studies.

The aim of the present work was to study the variability at CSN1S1 locus of the Italian Mediterranean river buffalo and to investigate possible allele effects on milk yield and its composition. Effects of parity, calving season and month of production were also evaluated. Three SNPs were detected. The first mutation, located at position 89 of 17th exon (c.628C>T), is responsible for the amino acid change (p.Ser178Leu). The other two polymorphisms, detected at the positions 144 (c.882G>A) and 239 (c.977A>G) of 19th exon respectively, are silent (3’ UTR). Associations between the CSN1S1 genotypes and milk production traits were investigated using 4,122 test day records of 503 lactations from 175 buffalo cows. Milk yield, fat and protein percentages were analyzed using a mixed linear model. A significant association between the c.628C>T SNP and the protein percentage was found. In particular, the CC genotype showed an average value of about 0.04% higher than the CT and TT genotypes. The allele substitution effect of the cytosine into the thymine was -0.014, with a quite low (0.3%) protein percentage (PP) contribution on total phenotypic variance. A large dominance effect was detected. Furthermore, a characterization of the CSN1S1 transcripts and a method based on MboI-ACRS-PCR for a rapid genotyping of c.628C>T were provided

The ALICE Zero Degree Calorimeters

In the ALICE experiment at Cern LHC, a set of hadron calorimeters will be used to determine the centrality of the Pb-Pb collision. The spectator protons and neutrons, will be separated from the ion beams, using the separator magnet (D1) of the LHC beam optics and respectively detected by a proton (ZP) and a neutron (ZN) "Zero-degree Calorimeter" (ZDC). The detectors will be placed in front of the separator D2 magnet, 115 meters away from the beam intersection point. The ZDCs are quartz-fiber spaghetti calorimeters that exploit the Cherenkov light produced by the shower particles in silica optical fibers.This technique offers the advantages of high radiation hardness (up to several Grad), fast response and reduced lateral dimension of the detectable shower. In addition, quartz-fiber calorimeters are intrinsically insensitive to radio-activation background, which produces particles below the Cherenkov threshold.The ALICE ZDC should have an energy resolution comparable with the intrinsic energy fluctuations, which range from about 20 0.000000or central events to about 5 0.000000or peripheral ones, according to simulations that use HIJING as event generator. The fiber-to-absorber filling ratio must be chosen as a good compromise between the required energy resolution and the fiber cost.The design of the proposed calorimeter will be discussed, together with the expected performances. Whenever possible, the simulated results will be compared with the experimental ones, obtained with the built prototypes and with the NA50 ZDC, which can be considered as a working prototype for the ALICE neutron calorimeter