Evolvability of Chaperonin Substrate Proteins

Molecular chaperones ensure that their substrate proteins reach the functional native state, and prevent their aggregation. Recently, an additional function was proposed for molecular chaperones: they serve as buffers (_capacitors_) for evolution by permitting their substrate proteins to mutate and at the same time still allowing them to fold productively.

Using pairwise alignments of _E. coli_ genes with genes from other gamma-proteobacteria, we showed that the described buffering effect cannot be observed among substrate proteins of GroEL, an essential chaperone in _E. coli_. Instead, we find that GroEL substrate proteins evolve less than other soluble _E. coli_ proteins. We analyzed several specific structural and biophysical properties of proteins to assess their influence on protein evolution and to find out why specifically GroEL substrates do not show the expected higher divergence from their orthologs.

Our results culminate in four main findings: *1.* We find little evidence that GroEL in _E. coli_ acts as a capacitor for evolution _in vivo_. *2.* GroEL substrates evolved less than other _E. coli_ proteins. *3.* Predominantly structural features appear to be a strong determinant of evolutionary rate. *4.* Besides size, hydrophobicity is a criterion for exclusion for a protein as a chaperonin substrate

Towards a fully automated computation of RG-functions for the 3-dd O(N) vector model: Parametrizing amplitudes

Within the framework of field-theoretical description of second-order phase transitions via the 3-dimensional O(N) vector model, accurate predictions for critical exponents can be obtained from (resummation of) the perturbative series of Renormalization-Group functions, which are in turn derived --following Parisi's approach-- from the expansions of appropriate field correlators evaluated at zero external momenta. Such a technique was fully exploited 30 years ago in two seminal works of Baker, Nickel, Green and Meiron, which lead to the knowledge of the $\beta$-function up to the 6-loop level; they succeeded in obtaining a precise numerical evaluation of all needed Feynman amplitudes in momentum space by lowering the dimensionalities of each integration with a cleverly arranged set of computational simplifications. In fact, extending this computation is not straightforward, due both to the factorial proliferation of relevant diagrams and the increasing dimensionality of their associated integrals; in any case, this task can be reasonably carried on only in the framework of an automated environment. On the road towards the creation of such an environment, we here show how a strategy closely inspired by that of Nickel and coworkers can be stated in algorithmic form, and successfully implemented on the computer. As an application, we plot the minimized distributions of residual integrations for the sets of diagrams needed to obtain RG-functions to the full 7-loop level; they represent a good evaluation of the computational effort which will be required to improve the currently available estimates of critical exponents.Comment: 54 pages, 17 figures and 4 table

Genetic correlations between measures of beef quality traits and their predictions by near-infrared spectroscopy in the Piemontese cattle breed.

The aims of this study were to predict beef quality traits (BQ: colour, shear force, drip and cooking losses) of Piemontese cattle using near-infrared spectroscopy (NIRS) and to estimate genetic parameters for measured BQ and their predictions by NIRS. Heritabilities and genetic correlations for measured BQ and their predictions based on NIRS were estimated through bivariate Bayesian analyses. Heritability estimates for measured BQ were of intermediate magnitude (from 0.10 to 0.63) and similar to those for NIRS predictions. The genetic correlations between BQ measures and their predictions by NIRS were very high for colour traits, high for drip loss, and nil for shear force and cooking loss. NIRS predictions can be proposed as indicator traits in breeding programs for enhancement of colour traits and drip loss

Effects of Stearoyl-CoA Desaturase 1 and Sterol Regulatory Element Binding Protein Gene Polymorphisms on Milk Production, Composition and Coagulation Properties of Individual Milk of Brown Swiss Cows

Associations between stearoyl-CoA desaturase (SCD) and sterol regulatory element binding protein (SREBP-1) gene polymorphisms and milk production, composition (fat, protein, and casein content), acidity (pH and titratable acidity) and coagulation properties (MCP), namely rennet coagulation time (RCT, min) and curd firmness (a30, mm) were investigated on individual Brown Swiss milk. A total of 294 cows from 16 herds and progeny of 15 sires were milk-sampled once. Th e additive effects of SCD and SREBP-1 genotypes on the aforementioned traits were analyzed through Bayesian linear models. The SCD gene was associated with protein content, casein content and a30. Lower protein, casein and a30 was observed for milk yielded by SCD V than A cows, whereas for other traits the effect was trivial. Animals carrying the L allele of SREBP-1 showed higher fat content than animals carrying the S allele. These results suggest a possible use of these loci in gene-assisted selection programs for the improvement of milk quality traits and MCP in Brown Swiss cattle, although large scale studies in different breeds are required

Investigation on variability of candidate genes for meat quality traits in Piemontese cattle

This study aimed to investigate the variability of 15 genes chosen according to their function as markers of meat quality traits in Piemontese cattle. Meat samples of Longissimus thoracis muscle and data on carcass weight (CW), shear force (SF), cooking loss (CL), and pH collected on 1,208 Piemontese young bulls progeny of 109 AI sires were available for this investigation. For each trait considered (CW, SF, CL, pH), 48 samples were chosen from each tail of normal distribution, and one or more single nucleotide polymorphisms (SNPs) were determined for the following loci: growth hormone (GH), growth hormone receptor (GHR), pro-opiomelanocortin (POMC), pituitary-specific positive transcription factor 1 (POU1F1), melanocortin-4 receptor (MC4R), corticotrophin-realising hormone (CRH), insulin-like growth factor binding protein- 3 (IGFBP3), diacylglycerol acyltransferase 1 (DGAT1), thyroglobulin (TG), carboxypeptidase E (CPE), calpain 1 (CAPN1), calpastatin (CAST), cathepsin B and D (CATB, CATD), and protein kinase adenosine monophosphate-activated γ3-subunit (PRKAG3). Eight SNPs were characterized by a high, 4 by an intermediate and 2 by a low variability; 6 may be almost fixed. Based on these results, variable loci will be investigated on the entire available data set in order to study their effects on meat quality traits

The Site Frequency/Dosage Spectrum of Autopolyploid Populations

The Site Frequency Spectrum (SFS) and the heterozygosity of allelic variants are among the most important summary statistics for population genetic analysis of diploid organisms. We discuss the generalization of these statistics to populations of autopolyploid organisms in terms of the joint Site Frequency/Dosage Spectrum and its expected value for autopolyploid populations that follow the standard neutral model. Based on these results, we present estimators of nucleotide variability from High-Throughput Sequencing (HTS) data of autopolyploids and discuss potential issues related to sequencing errors and variant calling. We use these estimators to generalize Tajima's D and other SFS-based neutrality tests to HTS data from autopolyploid organisms. Finally, we discuss how these approaches fail when the number of individuals is small. In fact, in autopolyploids there are many possible deviations from the Hardy–Weinberg equilibrium, each reflected in a different shape of the individual dosage distribution. The SFS from small samples is often dominated by the shape of these deviations of the dosage distribution from its Hardy–Weinberg expectations