66 research outputs found
Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds
Background
The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used.
Methods
Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content.
Results
In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip.
Conclusions
Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available
RE: pedagogy â after neutrality
Within the UK and in many parts of the world, official accounts of what it is to make sense of religion are framed within a rhetorics of neutrality in which such study is premised upon the possibility of dispassionate engagement and analysis. This paper, which is largely theoretical in scope, explores both the affordances and the costs of such an approach which has become âblack boxedâ on account of the work that it achieves. A series of new orientations within the academy that are broadly associated with post-structuralist philosophies, feminist and post-colonial studies, together with insights from Science and Technology Studies, question the plausibility of these claims for neutrality whilst in turn raising a series of new questions and priorities. It therefore becomes necessary to re-think and re-frame what it is to make sense of religious and cultural difference after neutrality. The gathering and co-ordination of new planes of sense-making that are responsive to an emergent series of epistemological, ontological, and ethical orientations are considered. Some of the distinctive pedagogical implications of such an approach that engages material practice, difference and uncertainty are then entertained
Wages in high-tech start-ups - do academic spin-offs pay a wage premium?
Due to their origin from universities, academic spinâoffs operate at the forefront of the
technological development. Therefore, spinâoffs exhibit a skillâbiased labour demand, i.e. spinâoffs
have a high demand for employees with cutting edge knowledge and technical skills. In order to accommodate
this demand, spinâoffs may have to pay a relative wage premium compared to other
highâtech startâups. However, neither a comprehensive theoretical assessment nor the empirical
literature on wages in startâups unambiguously predicts the existence and the direction of wage differentials
between spinâoffs and nonâspinâoffs. This paper addresses this research gap and examines
empirically whether or not spinâoffs pay their employees a wage premium. Using a unique linked
employerâemployee data set of German highâtech startâups, we estimate Mincerâtype wage regressions
applying the HausmanâTaylor panel estimator. Our results show that spinâoffs do not pay a
wage premium in general. However, a notable exception from this general result is that spinâoffs that
commercialise new scientific results or methods provide higher wages to employees with linkages to
the university sector â either as university graduates or as student workers
A genome scan for milk production traits in dairy goats reveals two new mutations in <i>Dgat1</i> reducing milk fat content
The quantity of milk and milk fat and proteins are particularly important traits in dairy livestock.
However, little is known about the regions of the genome that influence these traits in goats. We
conducted a genome wide association study in French goats and identified 109 regions associated
with dairy traits. For a major region on chromosome 14 closely associated with fat content, the
Diacylglycerol O-Acyltransferase 1 (DGAT1) gene turned out to be a functional and positional candidate
gene. The caprine reference sequence of this gene was completed and 29 polymorphisms were found in
the gene sequence, including two novel exonic mutations: R251L and R396W, leading to substitutions
in the protein sequence. The R251L mutation was found in the Saanen breed at a frequency of 3.5% and
the R396W mutation both in the Saanen and Alpine breeds at a frequencies of 13% and 7% respectively.
The R396W mutation explained 46% of the genetic variance of the trait, and the R251L mutation 6%.
Both mutations were associated with a notable decrease in milk fat content. Their causality was then
demonstrated by a functional test. These results provide new knowledge on the genetic basis of milk
synthesis and will help improve the management of the French dairy goat breeding program
Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants
The CÄ«varavastu of the MĆ«lasarvÄstivÄda Vinaya and Its Counterparts in Other Indian Buddhist Monastic Law Codes: A Comparative Survey
Lifetime feed efficiency and deep phenotypes from scarce feed intake records using the mechanistic LiGAPS-Dairy model
Ideally, selection for feed efficiency requires deep phenotyping of net efficiency, or lifetime recording of intake and all energy sinks across environments. However, recording of feed intake is scarce. Therefore, net efficiency is often defined as a simplistic linear equation, e.g. RFI. We tested the use of the mechanistic LiGAPS-Dairy model to derive nine deep phenotypes with a dataset for 1,228 dairy cows, combining feed intake, yield and liveweight data, with ration, weather, cow and farm data. Mismatch between data recording and model assumptions made this process time consuming, but allowing for missing parities and further automation should improve this quickly. We managed for 206 cows to estimate the deep phenotypes. Heritability and phenotypic correlations between the nine traits were estimated. When the pipeline is finished, the mechanistic LiGAPS-Dairy model will enable us to derive a more comprehensive breeding goal, more closely resembling net efficiency, whilst utilising scarce records
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