Different approaches to identify markers for meat quality and production traits in pigs: analysis of the transcriptome in post mortem skeletal muscle and investigation of candidate genes

Due to the growing attention of consumers towards their food, improvement of quality of animal products has become one of the main focus of research. To this aim, the application of modern molecular genetics approaches has been proved extremely useful and effective. This innovative drive includes all livestock species productions, including pork. The Italian pig breeding industry is unique because needs heavy pigs slaughtered at about 160 kg for the production of high quality processed products. For this reason, it requires precise meat quality and carcass characteristics. Two aspects have been considered in this thesis: the application of the transcriptome analysis in post mortem pig muscles as a possible method to evaluate meat quality parameters related to the pre mortem status of the animals, including health, nutrition, welfare, and with potential applications for product traceability (chapters 3 and 4); the study of candidate genes for obesity related traits in order to identify markers associated with fatness in pigs that could be applied to improve carcass quality (chapters 5, 6, and 7). Chapter three addresses the first issue from a methodological point of view. When we considered this issue, it was not obvious that post mortem skeletal muscle could be useful for transcriptomic analysis. Therefore we demonstrated that the quality of RNA extracted from skeletal muscle of pigs sampled at different post mortem intervals (20 minutes, 2 hours, 6 hours, and 24 hours) is good for downstream applications. Degradation occurred starting from 48 h post mortem even if at this time it is still possible to use some RNA products. In the fourth chapter, in order to demonstrate the potential use of RNA obtained up to 24 hours post mortem, we present the results of RNA analysis with the Affymetrix microarray platform that made it possible to assess the level of expression of more of 24000 mRNAs. We did not identify any significant differences between the different post mortem times suggesting that this technique could be applied to retrieve information coming from the transcriptome of skeletal muscle samples not collected just after slaughtering. This study represents the first contribution of this kind applied to pork. In the fifth chapter, we investigated as candidate for fat deposition the TBC1D1 [TBC1 (tre-2/USP6, BUB2, cdc16) gene. This gene is involved in mechanisms regulating energy homeostasis in skeletal muscle and is associated with predisposition to obesity in humans. By resequencing a fragment of the TBC1D1 gene we identified three synonymous mutations localized in exon 2 (g.40A>G, g.151C>T, and g.172T>C) and 2 polymorphisms localized in intron 2 (g.219G>A and g.252G>A). One of these polymorphisms (g.219G>A) was genotyped by high resolution melting (HRM) analysis and PCR-RFLP. Moreover, this gene sequence was mapped by radiation hybrid analysis on porcine chromosome 8. The association study was conducted in 756 performance tested pigs of Italian Large White and Italian Duroc breeds. Significant results were obtained for lean meat content, back fat thickness, visible intermuscular fat and ham weight. In chapter six, a second candidate gene (tribbles homolog 3, TRIB3) is analyzed in a study of association with carcass and meat quality traits. The TRIB3 gene is involved in energy metabolism of skeletal muscle and plays a role as suppressor of adipocyte differentiation. We identified two polymorphisms in the first coding exon of the porcine TRIB3 gene, one is a synonymous SNP (c.132T> C), a second is a missense mutation (c.146C> T, p.P49L). The two polymorphisms appear to be in complete linkage disequilibrium between and within breeds. The in silico analysis of the p.P49L substitution suggests that it might have a functional effect. The association study in about 650 pigs indicates that this marker is associated with back fat thickness in Italian Large White and Italian Duroc breeds in two different experimental designs. This polymorphisms is also associated with lactate content of muscle semimembranosus in Italian Large White pigs. Expression analysis indicated that this gene is transcribed in skeletal muscle and adipose tissue as well as in other tissues. In the seventh chapter, we reported the genotyping results for of 677 SNPs in extreme divergent groups of pigs chosen according to the extreme estimated breeding values for back fat thickness. SNPs were identified by resequencing, literature mining and in silico database mining. analysis, data reported in the literature of 60 candidates genes for obesity. Genotyping was carried out using the GoldenGate (Illumina) platform. Of the analyzed SNPs more that 300 were polymorphic in the genotyped population and had minor allele frequency (MAF) >0.05. Of these SNPs, 65 were associated (P<0.10) with back fat thickness. One of the most significant gene marker was the same TBC1D1 SNPs reported in chapter 5, confirming the role of this gene in fat deposition in pig. These results could be important to better define the pig as a model for human obesity other than for marker assisted selection to improve carcass characteristics.

Analisi critica di modelli previsionali per le frane in Emilia Romagna

Questa tesi di dottorato è inserita nell’ambito della convenzione tra ARPA_SIMC (che è l’Ente finanziatore), l’Agenzia Regionale di Protezione Civile ed il Dipartimento di Scienze della Terra e Geologico - Ambientali dell’Ateneo di Bologna. L’obiettivo principale è la determinazione di possibili soglie pluviometriche di innesco per i fenomeni franosi in Emilia Romagna che possano essere utilizzate come strumento di supporto previsionale in sala operativa di Protezione Civile. In un contesto geologico così complesso, un approccio empirico tradizionale non è sufficiente per discriminare in modo univoco tra eventi meteo innescanti e non, ed in generale la distribuzione dei dati appare troppo dispersa per poter tracciare una soglia statisticamente significativa. È stato quindi deciso di applicare il rigoroso approccio statistico Bayesiano, innovativo poiché calcola la probabilità di frana dato un certo evento di pioggia (P(A|B)) , considerando non solo le precipitazioni innescanti frane (quindi la probabilità condizionata di avere un certo evento di precipitazione data l’occorrenza di frana, P(B|A)), ma anche le precipitazioni non innescanti (quindi la probabilità a priori di un evento di pioggia, P(A)). L’approccio Bayesiano è stato applicato all’intervallo temporale compreso tra il 1939 ed il 2009. Le isolinee di probabilità ottenute minimizzano i falsi allarmi e sono facilmente implementabili in un sistema di allertamento regionale, ma possono presentare limiti previsionali per fenomeni non rappresentati nel dataset storico o che avvengono in condizioni anomale. Ne sono esempio le frane superficiali con evoluzione in debris flows, estremamente rare negli ultimi 70 anni, ma con frequenza recentemente in aumento. Si è cercato di affrontare questo problema testando la variabilità previsionale di alcuni modelli fisicamente basati appositamente sviluppati a questo scopo, tra cui X – SLIP (Montrasio et al., 1998), SHALSTAB (SHALlow STABility model, Montgomery & Dietrich, 1994), Iverson (2000), TRIGRS 1.0 (Baum et al., 2002), TRIGRS 2.0 (Baum et al., 2008).

Gait analysis using a single wearable inertial measurement unit

Procedures for quantitative walking analysis include the assessment of body segment movements within defined gait cycles. Recently, methods to track human body motion using inertial measurement units have been suggested. It is not known if these techniques can be readily transferred to clinical measurement situations. This work investigates the aspects necessary for one inertial measurement unit mounted on the lower back to track orientation, and determine spatio-temporal features of gait outside the confines of a conventional gait laboratory. Apparent limitations of different inertial sensors can be overcome by fusing data using methods such as a Kalman filter. The benefits of optimizing such a filter for the type of motion are unknown. 3D accelerations and 3D angular velocities were collected for 18 healthy subjects while treadmill walking. Optimization of Kalman filter parameters improved pitch and roll angle estimates when compared to angles derived using stereophotogrammetry. A Weighted Fourier Linear Combiner method for estimating 3D orientation angles by constructing an analytical representation of angular velocities and allowing drift free integration is also presented. When tested this method provided accurate estimates of 3D orientation when compared to stereophotogrammetry. Methods to determine spatio-temporal features from lower trunk accelerations generally require knowledge of sensor alignment. A method was developed to estimate the instants of initial and final ground contact from accelerations measured by a waist mounted inertial device without rigorous alignment. A continuous wavelet transform method was used to filter and differentiate the signal and derive estimates of initial and final contact times. The technique was tested with data recorded for both healthy and pathologic (hemiplegia and Parkinson’s disease) subjects and validated using an instrumented mat. The results show that a single inertial measurement unit can assist whole body gait assessment however further investigation is required to understand altered gait timing in some pathological subjects.

Peak-to-Peak Output Current Ripple Analysis in Multiphase and Multilevel Inverters

Analysis of the peak-to-peak output current ripple amplitude for multiphase and multilevel inverters is presented in this PhD thesis. The current ripple is calculated on the basis of the alternating voltage component, and peak-to-peak value is defined by the current slopes and application times of the voltage levels in a switching period. Detailed analytical expressions of peak-to-peak current ripple distribution over a fundamental period are given as function of the modulation index. For all the cases, reference is made to centered and symmetrical switching patterns, generated either by carrier-based or space vector PWM. Starting from the definition and the analysis of the output current ripple in three-phase two-level inverters, the theoretical developments have been extended to the case of multiphase inverters, with emphasis on the five- and seven-phase inverters. The instantaneous current ripple is introduced for a generic balanced multiphase loads consisting of series RL impedance and ac back emf (RLE). Simplified and effective expressions to account for the maximum of the output current ripple have been defined. The peak-to-peak current ripple diagrams are presented and discussed. The analysis of the output current ripple has been extended also to multilevel inverters, specifically three-phase three-level inverters. Also in this case, the current ripple analysis is carried out for a balanced three-phase system consisting of series RL impedance and ac back emf (RLE), representing both motor loads and grid-connected applications. The peak-to-peak current ripple diagrams are presented and discussed. In addition, simulation and experimental results are carried out to prove the validity of the analytical developments in all the cases. The cases with different phase numbers and with different number of levels are compared among them, and some useful conclusions have been pointed out. Furthermore, some application examples are given.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Statistical analysis of the error associated with the simplification of the stratigraphy in geotechnical models

The uncertainties in the determination of the stratigraphic profile of natural soils is one of the main problems in geotechnics, in particular for landslide characterization and modeling. The study deals with a new approach in geotechnical modeling which relays on a stochastic generation of different soil layers distributions, following a boolean logic – the method has been thus called BoSG (Boolean Stochastic Generation). In this way, it is possible to randomize the presence of a specific material interdigitated in a uniform matrix. In the building of a geotechnical model it is generally common to discard some stratigraphic data in order to simplify the model itself, assuming that the significance of the results of the modeling procedure would not be affected. With the proposed technique it is possible to quantify the error associated with this simplification. Moreover, it could be used to determine the most significant zones where eventual further investigations and surveys would be more effective to build the geotechnical model of the slope. The commercial software FLAC was used for the 2D and 3D geotechnical model. The distribution of the materials was randomized through a specifically coded MatLab program that automatically generates text files, each of them representing a specific soil configuration. Besides, a routine was designed to automate the computation of FLAC with the different data files in order to maximize the sample number. The methodology is applied with reference to a simplified slope in 2D, a simplified slope in 3D and an actual landslide, namely the Mortisa mudslide (Cortina d’Ampezzo, BL, Italy). However, it could be extended to numerous different cases, especially for hydrogeological analysis and landslide stability assessment, in different geological and geomorphological contexts.