Genetic analysis of twinning rate in Israeli Holstein cattle

International audienc

Deuteron Compton Scattering in Effective Field Theory: Spin-Dependent Cross Sections and Asymmetries

Polarized Compton scattering on the deuteron is studied in nuclear effective field theory. A set of tensor structures is introduced to define 12 independent Compton amplitudes. The scalar and vector amplitudes are calculated up to ${\cal O}((Q/\Lambda)^2)$ in low-energy power counting. Significant contribution to the vector amplitudes is found to come from the spin-orbit type of relativistic corrections. A double-helicity dependent cross section $\Delta_1 \sigma = (\sigma_{+1-1}-\sigma_{+1+1})/2$ is calculated to the same order, and the effect of the nucleon isoscalar spin-dependent polarizabilities is found to be smaller than the effect of isoscalar spin-independent ones. Contributions of spin-independent polarizabilities are investigated in various asymmetries, one of which has as large as 12 (26) percent effect at the center-of-mass photon energy 30 (50) MeV.Comment: 22 pages, 8 figures included, replaced with the version submitted to PR

Sum Rules and Spin-Dependent Polarizabilities of the Deuteron in Effective Field Theory

We construct sum rules for the forward vector and tensor polarizabilities for any spin-$S$ target and apply them to the spin-1 deuteron. We calculate these polarizabilities of the deuteron to the next-to-leading order in the pionless effective field theory.Comment: 10 pages, figures include

Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media

Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks. Our approach detects a broad range of cyber-attacks (e.g., distributed denial of service (DDOS) attacks, data breaches, and account hijacking) in an unsupervised manner using just a limited fixed set of seed event triggers. A new query expansion strategy based on convolutional kernels and dependency parses helps model reporting structure and aids in identifying key event characteristics. Through a large-scale analysis over Twitter, we demonstrate that our approach consistently identifies and encodes events, outperforming existing methods.Comment: 13 single column pages, 5 figures, submitted to KDD 201

Characterization of potential health promoting lipids in the co-products of de-flossed milkweed

The floss and oil of the common milkweed (Asclepias syriaca L.) seeds are currently used to produce comforters/pillows and skin care products, respectively. As an outcome of these products, copious quantities co-products (pressed seed meal and pod biomass) are disposed of each year despite the presence of potential health benefiting lipids. The objective of this project was to determine the feasibility of developing the lipid fraction from of these co-products for the fast growing dietary human health market. Although certain types of lipids were affected by the extraction solvent used (hexane and diethyl ether) as were overall amounts, analysis of the each extract showed novel lipid profiles with several potential health benefiting agents present at levels comparable to or exceeding those present in other typically consumed dietary oils or food systems (vitamin E, carotenoids, sterols and unsaturated free fatty acids, particularly the both omega 7-fatty acids)

Estimating genomic breeding values and detecting QTL using univariate and bivariate models

Background Genomic selection is particularly beneficial for difficult or expensive to measure traits. Since multi-trait selection is an important tool to deal with such cases, an important question is what the added value is of multi-trait genomic selection. Methods The simulated dataset, including a quantitative and binary trait, was analyzed with four univariate and bivariate linear models to predict breeding values for juvenile animals. Two models estimated variance components with REML using a numerator (A), or SNP based relationship matrix (G). Two SNP based Bayesian models included one (BayesA) or two distributions (BayesC) for estimated SNP effects. The bivariate BayesC model sampled QTL probabilities for each SNP conditional on both traits. Genotypes were permuted 2,000 times against phenotypes and pedigree, to obtain significance thresholds for posterior QTL probabilities. Genotypes were permuted rather than phenotypes, to retain relationships between pedigree and phenotypes, such that polygenic effects could still be estimated. Results Correlations between estimated breeding values (EBV) of different SNP based models, for juvenile animals, were greater than 0.93 (0.87) for the quantitative (binary) trait. Estimated genetic correlation was 0.71 (0.66) for model G (A). Accuracies of breeding values of SNP based models were for both traits highest for BayesC and lowest for G. Accuracies of breeding values of bivariate models were up to 0.08 higher than for univariate models. The bivariate BayesC model detected 14 out of 32 QTL for the quantitative trait, and 8 out of 22 for the binary trait. Conclusions Accuracy of EBV clearly improved for both traits using bivariate compared to univariate models. BayesC achieved highest accuracies of EBV and was also one of the methods that found most QTL. Permuting genotypes against phenotypes and pedigree in BayesC provided an effective way to derive significance thresholds for posterior QTL probabilitie

Dominance and parent-of-origin effects of coding and non-coding alleles at the acylCoA-diacylglycerol-acyltransferase (DGAT1) gene on milk production traits in German Holstein cows

<p>Abstract</p> <p>Background</p> <p>Substantial gene substitution effects on milk production traits have formerly been reported for alleles at the K232A and the promoter VNTR loci in the bovine acylCoA-diacylglycerol-acyltransferase 1 (<it>DGAT1</it>) gene by using data sets including sires with accumulated phenotypic observations of daughters (breeding values, daughter yield deviations). However, these data sets prevented analyses with respect to dominance or parent-of-origin effects, although an increasing number of reports in the literature outlined the relevance of non-additive gene effects on quantitative traits.</p> <p>Results</p> <p>Based on a data set comprising German Holstein cows with direct trait measurements, we first confirmed the previously reported association of <it>DGAT1 </it>promoter VNTR alleles with milk production traits. We detected a dominant mode of effects for the <it>DGAT1 </it>K232A and promoter VNTR alleles. Namely, the contrasts between the effects of heterozygous individuals at the <it>DGAT1 </it>loci differed significantly from the midpoint between the effects for the two homozygous genotypes for several milk production traits, thus indicating the presence of dominance. Furthermore, we identified differences in the magnitude of effects between paternally and maternally inherited <it>DGAT1 </it>promoter VNTR – K232A haplotypes indicating parent-of-origin effects on milk production traits.</p> <p>Conclusion</p> <p>Non-additive effects like those identified at the bovine <it>DGAT1 </it>locus have to be accounted for in more specific QTL detection models as well as in marker assisted selection schemes. The <it>DGAT1 </it>alleles in cattle will be a useful model for further investigations on the biological background of non-additive effects in mammals due to the magnitude and consistency of their effects on milk production traits.</p

Identification of Mendelian inconsistencies between SNP and pedigree information of sibs

Background Using SNP genotypes to apply genomic selection in breeding programs is becoming common practice. Tools to edit and check the quality of genotype data are required. Checking for Mendelian inconsistencies makes it possible to identify animals for which pedigree information and genotype information are not in agreement. Methods Straightforward tests to detect Mendelian inconsistencies exist that count the number of opposing homozygous marker (e.g. SNP) genotypes between parent and offspring (PAR-OFF). Here, we develop two tests to identify Mendelian inconsistencies between sibs. The first test counts SNP with opposing homozygous genotypes between sib pairs (SIBCOUNT). The second test compares pedigree and SNP-based relationships (SIBREL). All tests iteratively remove animals based on decreasing numbers of inconsistent parents and offspring or sibs. The PAR-OFF test, followed by either SIB test, was applied to a dataset comprising 2,078 genotyped cows and 211 genotyped sires. Theoretical expectations for distributions of test statistics of all three tests were calculated and compared to empirically derived values. Type I and II error rates were calculated after applying the tests to the edited data, while Mendelian inconsistencies were introduced by permuting pedigree against genotype data for various proportions of animals. Results Both SIB tests identified animal pairs for which pedigree and genomic relationships could be considered as inconsistent by visual inspection of a scatter plot of pairwise pedigree and SNP-based relationships. After removal of 235 animals with the PAR-OFF test, SIBCOUNT (SIBREL) identified 18 (22) additional inconsistent animals. Seventeen animals were identified by both methods. The numbers of incorrectly deleted animals (Type I error), were equally low for both methods, while the numbers of incorrectly non-deleted animals (Type II error), were considerably higher for SIBREL compared to SIBCOUNT. Conclusions Tests to remove Mendelian inconsistencies between sibs should be preceded by a test for parent-offspring inconsistencies. This parent-offspring test should not only consider parent-offspring pairs based on pedigree data, but also those based on SNP information. Both SIB tests could identify pairs of sibs with Mendelian inconsistencies. Based on type I and II error rates, counting opposing homozygotes between sibs (SIBCOUNT) appears slightly more precise than comparing genomic and pedigree relationships (SIBREL) to detect Mendelian inconsistencies between sib

Macrophage-derived human resistin is induced in multiple helminth infections and promotes inflammatory monocytes and increased parasite burden.

Parasitic helminth infections can be associated with lifelong morbidity such as immune-mediated organ failure. A better understanding of the host immune response to helminths could provide new avenues to promote parasite clearance and/or alleviate infection-associated morbidity. Murine resistin-like molecules (RELM) exhibit pleiotropic functions following helminth infection including modulating the host immune response; however, the relevance of human RELM proteins in helminth infection is unknown. To examine the function of human resistin (hResistin), we utilized transgenic mice expressing the human resistin gene (hRetnTg+). Following infection with the helminth Nippostrongylus brasiliensis (Nb), hResistin expression was significantly upregulated in infected tissue. Compared to control hRetnTg- mice, hRetnTg+ mice suffered from exacerbated Nb-induced inflammation characterized by weight loss and increased infiltration of inflammatory monocytes in the lung, along with elevated Nb egg burdens and delayed parasite expulsion. Genome-wide transcriptional profiling of the infected tissue revealed that hResistin promoted expression of proinflammatory cytokines and genes downstream of toll-like receptor signaling. Moreover, hResistin preferentially bound lung monocytes, and exogenous treatment of mice with recombinant hResistin promoted monocyte recruitment and proinflammatory cytokine expression. In human studies, increased serum resistin was associated with higher parasite load in individuals infected with soil-transmitted helminths or filarial nematode Wuchereria bancrofti, and was positively correlated with proinflammatory cytokines. Together, these studies identify human resistin as a detrimental factor induced by multiple helminth infections, where it promotes proinflammatory cytokines and impedes parasite clearance. Targeting the resistin/proinflammatory cytokine immune axis may provide new diagnostic or treatment strategies for helminth infection and associated immune-mediated pathology