Effect of including genetic progress in milk yield on evaluating the use of sexed semen and other reproduction strategies in a dairy herd

The objective of this study was to explore the importance of including genetic progress in milk yield when evaluating different reproductive strategies in a dairy herd by simulation modeling. The model used in this study was SimHerd V, a dynamic and mechanistic Monte Carlo simulation model of a dairy herd including young stock. A daily increasing trend describing genetic milk yield potential of the sire population was included in the model. The inaccuracy of assuming that replacement heifers have the same (milk yield) potential as the cows present in the herd was hereby dealt with. Improving estrus detection rate from 0.45 to 0.80 increased gross margin (GM) per cow-year by €20 when genetic progress was not included in the model. When genetic progress was included in the model, then the same improvement in estrus detection decreased the GM per cow-year by €7.4. This reduced effect was explained by a lower replacement rate in consequence of the improved estrus detection and thereby a slower genetic progress in the herd. There was a reduced effect of including genetic progress on GM when surplus heifers were sold selectively based on breeding values. Repeated insemination with sexed semen on the superior half of all heifers reduced GM by €8 per cow-year when genetic progress was not included and increased the GM by €16 per cow-year when genetic progress was included in the model. Including genetic progress reduced the losses caused by lower conception and estrus detection rates and had a minimal effect with regard to postponing first insemination. This study has proven that it is important to include genetic progress in decisions on reproduction strategies in a dairy herd.     

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

Background

Network inference methods reconstruct mathematical models of molecular or genetic networks directly from experimental data sets. We have previously reported a mathematical method which is exclusively data-driven, does not involve any heuristic decisions within the reconstruction process, and deliveres all possible alternative minimal networks in terms of simple place/transition Petri nets that are consistent with a given discrete time series data set.

Results

We fundamentally extended the previously published algorithm to consider catalysis and inhibition of the reactions that occur in the underlying network. The results of the reconstruction algorithm are encoded in the form of an extended Petri net involving control arcs. This allows the consideration of processes involving mass flow and/or regulatory interactions. As a non-trivial test case, the phosphate regulatory network of enterobacteria was reconstructed using in silico-generated time-series data sets on wild-type and in silico mutants.

Conclusions

The new exact algorithm reconstructs extended Petri nets from time series data sets by finding all alternative minimal networks that are consistent with the data. It suggested alternative molecular mechanisms for certain reactions in the network. The algorithm is useful to combine data from wild-type and mutant cells and may potentially integrate physiological, biochemical, pharmacological, and genetic data in the form of a single model.     

Generic genetic differences between farmed and wild Atlantic salmon identified from a 7K SNP-chip

Genetic interactions between farmed and wild conspecifics are of special concern in fisheries where large numbers of domesticated individuals are released into the wild. In the Atlantic salmon (Salmo salar), selective breeding since the 1970's has resulted in rapid genetic changes in commercially important traits, such as a doubling of the growth rate. Each year, farmed salmon escape from net pens, enter rivers, and interbreed with wild salmon. Field experiments demonstrate that genetic introgression may weaken the viability of recipient populations. However, due to the lack of diagnostic genetic markers, little is known about actual rates of gene flow from farmed to wild populations. Here we present a panel of 60 single nucleotide polymorphisms (SNPs) that collectively are diagnostic in identifying individual salmon as being farmed or wild, regardless of their populations of origin. These were sourced from a pool of 7000 SNPs comparing historical wild and farmed salmon populations, and were distributed on all but two of the 29 chromosomes. We suggest that the generic differences between farmed and wild salmon at these SNPs have arisen due to domestication. The identified panel of SNPs will permit quantification of gene flow from farmed to wild salmon populations, elucidating one of the most controversial potential impacts of aquaculture. With increasing global interest in aquaculture and increasing pressure on wild populations, results from our study have implications for a wide range of species.     

Untangling the intracellular signalling network in cancer--a strategy for data integration in acute myeloid leukaemia

Protein and gene networks centred on the regulatory tumour suppressor proteins may be of crucial importance both in carcinogenesis and in the response to chemotherapy. Tumour suppressor protein p53 integrates intracellular data in stress responses, receiving signals and translating these into differential gene expression. Interpretation of the data integrated on p53 may therefore reveal the response to therapy in cancer. Proteomics offers more specific data - closer to "the real action" - than the hitherto more frequently used gene expression profiling. Integrated data analysis may reveal pathways disrupted at several regulatory levels. Ultimately, integrated data analysis may also contribute to finding key underlying cancer genes. We here proposes a Partial Least Squares Regression (PLSR)-based data integration strategy, which allows simultaneous analysis of proteomic data, gene expression data and classical clinical parameters. PLSR collapses multidimensional data into fewer relevant dimensions for data interpretation. PLSR can also aid identification of functionally important modules by also performing comparison to databases on known biological interactions. Further, PLSR allows meaningful visualization of complex datasets, aiding interpretation of the underlying biology. Extracting the true biological causal mechanisms from heterogeneous patient populations is the key to discovery of new therapeutic options in cancer.     

Protein carbonylation and metal-catalyzed protein oxidation in a cellular perspective

Proteins can become oxidatively modified in many different ways, either by direct oxidation of amino acid side chains and protein backbone or indirectly by conjugation with oxidation products of polyunsaturated fatty acids and carbohydrates. While reversible oxidative modifications are thought to be relevant in physiological processes, irreversible oxidative modifications are known to contribute to cellular damage and disease. The most well-studied irreversible protein oxidation is carbonylation. In this work we first examine how protein carbonylation occurs via metal-catalyzed oxidation (MCO) in vivo and in vitro with an emphasis on cellular metal ion homeostasis and metal binding. We then review proteomic methods currently used for identifying carbonylated proteins and their sites of modification. Finally, we discuss the identified carbonylated proteins and the pattern of carbonylation sites in relation to cellular metabolism using the mitochondrion as a case story.     

Attitudes to publicly funded obesity treatment and prevention

The aim of this study was to investigate the Danish public's support for publicly funded obesity treatment and prevention. It was also examined whether levels of support could be explained by dislike of obese people and/or the belief that those who are obese are personally responsible for their condition. A representative survey of members of the Danish public (N = 1,141) was conducted using a web-based questionnaire. The survey was designed to assess attitudes to public funding for obesity-related health care, and to investigate the impact, on those attitudes, of dislike of obese people, the perceived controllability of obesity, self-reported BMI, and additional attitudinal and socio-demographic characteristics. Public funding of some obesity treatments, such as weight-loss surgery, attracted only limited public support. A majority of the Danish public did support "softer" treatment interventions and preventive initiatives. Attitudes to the treatment of obesity were clearly best predicted by the belief that individuals are personally responsible for their own obesity. Dislike of obese persons had no direct effect on the preference for collective treatment initiatives and only a small effect on support for publicly funded obesity prevention. The high level of disapproval for publicly funded obesity treatment should be cause for concern for decision makers aiming to ensure equal access to health care. Since it is the belief that obese people are personally responsible which explains this disapproval, strategies for challenging public opinion on this issue are discussed.     

Trend in obesity prevalence in European adult cohort populations during follow-up since 1996 and their predictions to 2015

Objective

To investigate trends in obesity prevalence in recent years and to predict the obesity prevalence in 2015 in European populations.

Methods

Data of 97 942 participants from seven cohorts involved in the European Prospective Investigation into Cancer and Nutrition (EPIC) study participating in the Diogenes project (named as “Diogenes cohort” in the following) with weight measurements at baseline and follow-up were used to predict future obesity prevalence with logistic linear and non-linear (leveling off) regression models. In addition, linear and leveling off models were fitted to the EPIC-Potsdam dataset with five weight measures during the observation period to find out which of these two models might provide the more realistic prediction.

Results

During a mean follow-up period of 6 years, the obesity prevalence in the Diogenes cohort increased from 13% to 17%. The linear prediction model predicted an overall obesity prevalence of about 30% in 2015, whereas the leveling off model predicted a prevalence of about 20%. In the EPIC-Potsdam cohort, the shape of obesity trend favors a leveling off model among men (R² = 0.98), and a linear model among women (R² = 0.99).

Conclusion

Our data show an increase in obesity prevalence since the 1990ies, and predictions by 2015 suggests a sizeable further increase in European populations. However, the estimates from the leveling off model were considerably lower.     

MicroRNA alterations and associated aberrant DNA methylation patterns across multiple sample types in oral squamous cell carcinoma

Background

MicroRNA (miRNA) expression is broadly altered in cancer, but few studies have investigated miRNA deregulation in oral squamous cell carcinoma (OSCC). Epigenetic mechanisms are involved in the regulation of >30 miRNA genes in a range of tissues, and we aimed to investigate this further in OSCC.

Methods

TaqMan® qRT-PCR arrays and individual assays were used to profile miRNA expression in a panel of 25 tumors with matched adjacent tissues from patients with OSCC, and 8 control paired oral stroma and epithelium from healthy volunteers. Associated DNA methylation changes of candidate epigenetically deregulated miRNA genes were measured in the same samples using the MassArray® mass spectrometry platform. MiRNA expression and DNA methylation changes were also investigated in FACS sorted CD44^high oral cancer stem cells from primary tumor samples (CSCs), and in oral rinse and saliva from 15 OSCC patients and 7 healthy volunteers.

Results

MiRNA expression patterns were consistent in healthy oral epithelium and stroma, but broadly altered in both tumor and adjacent tissue from OSCC patients. MiR-375 is repressed and miR-127 activated in OSCC, and we confirm previous reports of miR-137 hypermethylation in oral cancer. The miR-200 s/miR-205 were epigenetically activated in tumors vs normal tissues, but repressed in the absence of DNA hypermethylation specifically in CD44^high oral CSCs. Aberrant miR-375 and miR-200a expression and miR-200c-141 methylation could be detected in and distinguish OSCC patient oral rinse and saliva from healthy volunteers, suggesting a potential clinical application for OSCC specific miRNA signatures in oral fluids.

Conclusions

MiRNA expression and DNA methylation changes are a common event in OSCC, and we suggest miR-375, miR-127, miR-137, the miR-200 family and miR-205 as promising candidates for future investigations. Although overall activated in OSCC, miR-200/miR-205 suppression in oral CSCs indicate that cell specific silencing of these miRNAs may drive tumor expansion and progression.