DNA sequence polymorphisms in a panel of eight candidate bovine imprinted genes and their association with performance traits in Irish Holstein-Friesian cattle

peer-reviewedBackground: Studies in mice and humans have shown that imprinted genes, whereby expression from one of the two parentally inherited alleles is attenuated or completely silenced, have a major effect on mammalian growth, metabolism and physiology. More recently, investigations in livestock species indicate that genes subject to this type of epigenetic regulation contribute to, or are associated with, several performance traits, most notably muscle mass and fat deposition. In the present study, a candidate gene approach was adopted to assess 17 validated single nucleotide polymorphisms (SNPs) and their association with a range of performance traits in 848 progeny-tested Irish Holstein-Friesian artificial insemination sires. These SNPs are located proximal to, or within, the bovine orthologs of eight genes (CALCR, GRB10, PEG3, PHLDA2, RASGRF1, TSPAN32, ZIM2 and ZNF215) that have been shown to be imprinted in cattle or in at least one other mammalian species (i.e. human/mouse/pig/sheep). Results: Heterozygosities for all SNPs analysed ranged from 0.09 to 0.46 and significant deviations from Hardy-Weinberg proportions (P ≤ 0.01) were observed at four loci. Phenotypic associations (P ≤ 0.05) were observed between nine SNPs proximal to, or within, six of the eight analysed genes and a number of performance traits evaluated, including milk protein percentage, somatic cell count, culled cow and progeny carcass weight, angularity, body conditioning score, progeny carcass conformation, body depth, rump angle, rump width, animal stature, calving difficulty, gestation length and calf perinatal mortality. Notably, SNPs within the imprinted paternally expressed gene 3 (PEG3) gene cluster were associated (P ≤ 0.05) with calving, calf performance and fertility traits, while a single SNP in the zinc finger protein 215 gene (ZNF215) was associated with milk protein percentage (P ≤ 0.05), progeny carcass weight (P ≤ 0.05), culled cow carcass weight (P ≤ 0.01), angularity (P ≤ 0.01), body depth (P ≤ 0.01), rump width (P ≤ 0.01) and animal stature (P ≤ 0.01). Conclusions: Of the eight candidate bovine imprinted genes assessed, DNA sequence polymorphisms in six of these genes (CALCR, GRB10, PEG3, RASGRF1, ZIM2 and ZNF215) displayed associations with several of the phenotypes included for analyses. The genotype-phenotype associations detected here are further supported by the biological function of these six genes, each of which plays important roles in mammalian growth, development and physiology. The associations between SNPs within the imprinted PEG3 gene cluster and traits related to calving, calf performance and gestation length suggest that this domain on chromosome 18 may play a role regulating pre-natal growth and development and fertility. SNPs within the bovine ZNF215 gene were associated with bovine growth and body conformation traits and studies in humans have revealed that the human ZNF215 ortholog belongs to the imprinted gene cluster associated with Beckwith-Wiedemann syndrome--a genetic disorder characterised by growth abnormalities. Similarly, the data presented here suggest that the ZNF215 gene may have an important role in regulating bovine growth. Collectively, our results support previous work showing that (candidate) imprinted genes/loci contribute to heritable variation in bovine performance traits and suggest that DNA sequence polymorphisms within these genes/loci represents an important reservoir of genomic markers for future genetic improvement of dairy and beef cattle populations.Department of Agriculture, Fisheries and Food Ireland - Research Stimulus Fund (project numbers: RSF-06-406, RSF-06-0353 and RSF-06-0409); Science Foundation Ireland - Investigator Programme Grants(SFI/01/F.1/B028; SFI/08/IN.1/B1931, 07/SRC/B1156 (MPM)

A Parameter Estimation and Identifiability Analysis Methodology Applied to a Street Canyon Air Pollution Model

Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street Pollution Model (OSPMr). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to succesfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach applied for the uncertainty calculations underestimated the parameter uncertainties. The model parameter uncertainty was qualitatively assessed to be significant, and reduction strategies were identified

Ultrafast carrier relaxation in GaN, In_(0.05)Ga_(0.95)N and an In_(0.05)Ga_(0.95)/In_(0.15)Ga_(0.85)N Multiple Quantum Well

Room temperature, wavelength non-degenerate ultrafast pump/probe measurements were performed on GaN and InGaN epilayers and an InGaN multiple quantum well structure. Carrier relaxation dynamics were investigated as a function of excitation wavelength and intensity. Spectrally-resolved sub-picosecond relaxation due to carrier redistribution and QW capture was found to depend sensitively on the wavelength of pump excitation. Moreover, for pump intensities above a threshold of 100 microJ/cm2, all samples demonstrated an additional emission feature arising from stimulated emission (SE). SE is evidenced as accelerated relaxation (< 10 ps) in the pump-probe data, fundamentally altering the re-distribution of carriers. Once SE and carrier redistribution is completed, a slower relaxation of up to 1 ns for GaN and InGaN epilayers, and 660 ps for the MQW sample, indicates carrier recombination through spontaneous emission.Comment: submitted to Phys. Rev.

Analysis of the impact of inhomogeneous emissions in the Operational Street Pollution Model (OSPM)

Semi-parameterized street canyon models, as e.g. the Operational Street Pollution Model (OSPM^&reg;), have been frequently applied for the last two decades to analyse levels and consequences of air pollution in streets. These models are popular due to their speed and low input requirements. One often-used simplification is the assumption that emissions are homogeneously distributed in the entire length and width of the street canyon. It is thus the aim of the present study to analyse the impact of this assumption by implementing an inhomogeneous emission geometry scheme in OSPM. The homogeneous and the inhomogeneous emission geometry schemes are validated against two real-world cases: Hornsgatan, Stockholm, a sloping street canyon; and Jagtvej, Copenhagen; where the morning rush hour has more traffic on one lane compared to the other. The two cases are supplemented with a theoretical calculation of the impact of street aspect (height / width) ratio and emission inhomogeneity on the concentrations resulting from inhomogeneous emissions. The results show an improved performance for the inhomogeneous emission geometry over the homogeneous emission geometry. Moreover, it is shown that the impact of inhomogeneous emissions is largest for near-parallel wind directions and for high aspect ratio canyons. The results from the real-world cases are however confounded by challenges estimating the emissions accurately

The Treatment of Uncertainties in Reactive Pollution Dispersion Models at Urban Scales

The ability to predict NO2 concentrations ([NO¬2]) within urban street networks is important for the evaluation of strategies to reduce exposure to NO2. However, models aiming to make such predictions involve the coupling of several complex processes: traffic emissions under different levels of congestion; dispersion via turbulent mixing; chemical processes of relevance at the street-scale. Parameterisations of these processes are challenging to quantify with precision. Predictions are therefore subject to uncertainties which should be taken into account when using models within decision making. This paper presents an analysis of mean [NO¬2] predictions from such a complex modelling system applied to a street canyon within the city of York, UK including the treatment of model uncertainties and their causes. The model system consists of a micro-scale traffic simulation and emissions model, a Reynolds Averaged turbulent flow model coupled to a reactive Lagrangian particle dispersion model. The analysis focuses on the sensitivity of predicted in-street increments of [NO¬2] at different locations in the street to uncertainties in the model inputs. These include physical characteristics such as background wind direction, temperature and background ozone concentrations; traffic parameters such as overall demand and primary NO2 fraction; as well as model parameterisations such as roughness lengths, turbulent time- and length-scales and chemical reaction rate coefficients. Predicted [NO¬2] is shown to be relatively robust with respect to model parameterisations, although there are significant sensitivities to the activation energy for the reaction NO+O3 as well as the canyon wall roughness length. Under off-peak traffic conditions, demand is the key traffic parameter. Under peak conditions where the network saturates, road-side [NO¬2] is relatively insensitive to changes in demand and more sensitive to the primary NO2 fraction. The most important physical parameter was found to be the background wind direction. The study highlights the key parameters required for reliable [NO¬2] estimations suggesting that accurate reference measurements for wind direction should be a critical part of air quality assessments for in-street locations. It also highlights the importance of street scale chemical processes in forming road-side [NO¬2], particularly for regions of high NOx emissions such as close to traffic queues

Distance to high-voltage power lines and risk of childhood leukemia:An analysis of confounding by and interaction with other potential risk factors

We investigated whether there is an interaction between distance from residence at birth to nearest power line and domestic radon and traffic-related air pollution, respectively, in relation to childhood leukemia risk. Further, we investigated whether adjusting for potential confounders alters the association between distance to nearest power line and childhood leukemia. We included 1024 cases aged <15, diagnosed with leukemia during 1968-1991, from the Danish Cancer Registry and 2048 controls randomly selected from the Danish childhood population and individually matched by gender and year of birth. We used geographical information systems to determine the distance between residence at birth and the nearest 132-400 kV overhead power line. Concentrations of domestic radon and traffic-related air pollution (NOx at the front door) were estimated using validated models. We found a statistically significant interaction between distance to nearest power line and domestic radon regarding risk of childhood leukemia (p = 0.01) when using the median radon level as cut-off point but not when using the 75th percentile (p = 0.90). We found no evidence of an interaction between distance to nearest power line and traffic-related air pollution (p = 0.73). We found almost no change in the estimated association between distance to power line and risk of childhood leukemia when adjusting for socioeconomic status of the municipality, urbanization, maternal age, birth order, domestic radon and traffic-related air pollution. The statistically significant interaction between distance to nearest power line and domestic radon was based on few exposed cases and controls and sensitive to the choice of exposure categorization and might, therefore, be due to chance

THE MUST MODEL EVALUATION EXERCISE: STATISTICAL ANALYSIS OF MODELLING RESULTS

The first validation exercise of the COST action 732 lead to a substantial number of simulation results for comparison with the MUST wind tunnel experiments. Validation metrics for selected simulation results of the flow field and the concentrations are presented and compared to the state of the art. In addition mean metrics and corresponding scatter limits are computed from the individual results

THE MUST MODEL EVALUATION EXERCISE: PATTERNS IN MODEL PERFORMANCE

As part of the COST 732 action more than a dozen different research groups have modelled the MUST experiment, as simulated in a wind tunnel. The model evaluation guidance developed within COST 732 recommends \u27exploratory data analysis\u27 as one of the elements in model validation. Experience has shown that such exploratory analysis is crucial to reveal shortcomings of models that might otherwise pass unnoticed. Conditions are best for detecting common patterns and anomalies if you have a situation where several models are put into a common framework – like the case at hand. The available material provides a unique opportunity to identify and explore patterns within model performance