62 research outputs found
Building phenotype networks to improve QTL detection: a comparative analysis of fatty acid and fat traits in pigs.
15 pagesInternational audienceModels in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits
Bridge toughening in fiber-reinforced composites: A three-dimensional, discrete fiber model
Effect of sodium-based slag treatment on the distribution of impurities in metallurgical grade silicon
Conference Name:4th International Conference on Manufacturing Science and Engineering, ICMSE 2013. Conference Address: Dalian, China. Time:March 30, 2013 - March 31, 2013.Northeastern University, China; Harbin Institute of Technology; Jilin UniversityThe distribution of impurities in metallurgical grade silicon before and after slag treatment was investigated for the purpose of upgrading metallurgical grade to solar grade silicon. It was found that metal impurities co-deposited with silicon and formed different intermetallics in the precipitated phase, and these intermetallics such as Si-Fe, Si-Ni, Si-Ti-V and Si-Ca-Al-Fe were substituted by Si-Fe-Ti-V after treatment of Na2CO3-SiO2 slag. Non-metallic impurities B and P were nearly homogeneous distribution in metallurgical grade silicon before and after slag treatment. Moreover, a particular analysis of the microstructure of slag has been carried out, it was determined that metal impurities Al and Ca could easily migrate from silicon to slag phase in the refining process. ? (2013) Trans Tech Publications, Switzerland
Research status on soil and water pollution remediation and environmental impact of nanomaterials
Design and Implementation of Crop Potential Model System Based on GIS and Componentware Technology
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