Within- and across-breed genomic prediction using whole-genome sequence and single nucleotide polymorphism panels

International audienceBackground Currently, genomic prediction in cattle is largely based on panels of about 54k single nucleotide polymorphisms (SNPs). However with the decreasing costs of and current advances in next-generation sequencing technologies, whole-genome sequence (WGS) data on large numbers of individuals is within reach. Availability of such data provides new opportunities for genomic selection, which need to be explored.MethodsThis simulation study investigated how much predictive ability is gained by using WGS data under scenarios with QTL (quantitative trait loci) densities ranging from 45 to 132 QTL/Morgan and heritabilities ranging from 0.07 to 0.30, compared to different SNP densities, with emphasis on divergent dairy cattle breeds with small populations. The relative performances of best linear unbiased prediction (SNP-BLUP) and of a variable selection method with a mixture of two normal distributions (MixP) were also evaluated. Genomic predictions were based on within-population, across-population, and multi-breed reference populations.ResultsThe use of WGS data for within-population predictions resulted in small to large increases in accuracy for low to moderately heritable traits. Depending on heritability of the trait, and on SNP and QTL densities, accuracy increased by up to 31 %. The advantage of WGS data was more pronounced (7 to 92 % increase in accuracy depending on trait heritability, SNP and QTL densities, and time of divergence between populations) with a combined reference population and when using MixP. While MixP outperformed SNP-BLUP at 45 QTL/Morgan, SNP-BLUP was as good as MixP when QTL density increased to 132 QTL/Morgan.ConclusionsOur results show that, genomic predictions in numerically small cattle populations would benefit from a combination of WGS data, a multi-breed reference population, and a variable selection method

Endocrine disruptors and spontaneous premature labor: a case control study

<p>Abstract</p> <p>Background</p> <p>Premature labor is a poorly understood condition. Estrogen is thought to play a key role and therefore the labor process may be affected by endocrine disruptors. We sought to determine whether or not an environmental toxicant, DDE, or dietary derived endocrine disruptors, daidzein and genistein, are associated with spontaneous preterm labor.</p> <p>Methods</p> <p>Cases were defined as primiparous patients having a preterm delivery at or before 35 weeks following the spontaneous onset of labor. Controls were defined as primiparous women who delivered on the same day as the cases but at term gestation.</p> <p>Over approximately 1 year, 26 cases and 52 controls were recruited. Subjects agreed to have blood tests on day one postpartum for DDE and for the phytoestrogens genistein and daidzein.</p> <p>Results</p> <p>The mean concentration of DDE was similar in the case and control groups: 4.29 vs 4.32 ng/g lipid p = .85. In the case group, 13/26 had detectable levels of daidzein (range 0.20 – 1.56 ng/ml) compared to 25/52 controls (range 0.21 – 3.26 ng/ml). The mean concentration of daidzein was similar in cases compared to controls: 0.30 vs .34 ng/ml p = 0.91. Of the case group,14/26 had detectable levels of genistein (range 0.20 – 2.19 ng/ml) compared to 32/52 controls (range 0.21 – 2.55 ng/ml). The mean concentration of genistein was similar in cases compared to controls: 0.39 vs 0.31 ng/ml, p = 0.61.</p> <p>Conclusion</p> <p>The serum levels of DDE in this population were found to be low.</p> <p>There appears to be no relationship between serum concentrations of DDE, daidzein, and genistein and spontaneous preterm labor in our population. The inability to identify an effect may be related to the comparatively low concentrations of DDE in our population and the rapid and variable reduction of phytoestrogens from women in labor.</p

Therapeutic opportunities within the DNA damage response

The DNA damage response (DDR) is essential for maintaining the genomic integrity of the cell, and its disruption is one of the hallmarks of cancer. Classically, defects in the DDR have been exploited therapeutically in the treatment of cancer with radiation therapies or genotoxic chemotherapies. More recently, protein components of the DDR systems have been identified as promising avenues for targeted cancer therapeutics. Here, we present an in-depth analysis of the function, role in cancer and therapeutic potential of 450 expert-curated human DDR genes. We discuss the DDR drugs that have been approved by the US Food and Drug Administration (FDA) or that are under clinical investigation. We examine large-scale genomic and expression data for 15 cancers to identify deregulated components of the DDR, and we apply systematic computational analysis to identify DDR proteins that are amenable to modulation by small molecules, highlighting potential novel therapeutic targets

DCD USANS and SESANS: a comparison of two neutron scattering techniques applicable for the study of large-scale structures

This paper provides a comparison of the capabilities of two techniques for extending the range of conventional small-angle neutron scattering (SANS) towards the micrometre length scale, namely the double-crystal diffraction ultra-small-angle neutron scattering (DCD USANS) technique, which uses perfect silicon crystals in Bragg reflection, and spin-echo SANS (SESANS), a method that uses the spin precessions of a polarized neutron beam. Both methods encode the scattering angle to very high precision. Based on round-robin test measurements, the strengths and weaknesses of the two techniques are discussed with respect to the measurement of the particle size of monodisperse scatterers, and potential performance gains for state-of-the-art DCD USANS and SESANS instruments are investigated. © 2013, Wiley-Blackwell

Light scattering measurements on microemulsions: estimation of droplet sizes

Different scattering methods were used as tools to assess the size of droplets in highly diluted microemulsions. These were obtained after dilution of a self-emulsifying system made up of an oil, a surfactant and ethanol. Typical methods, often used in size and shape determination of particles, such as SAXS and USAXS suffer in the present case from a lack of electrondensity contrast. It becomes clear from our extensive use of dynamic light scattering that one should be careful in interpreting the latter data as well. Sample preparation and the subsequent handling of the samples during the experiments strongly affect reproducibility of the results. There is a need for well-defined protocols at the level of sample preparation and data handling. In the present research one uses extensively dynamic light scattering (DLS) in the back scattering mode and strengths and pitfalls, inherent to the backscattering technique, are discussed. It is crucial to be aware of droplet size distributions (monomodal/bimodal/multimodal) while reporting mean radii (Rh) as this radius is only relevant in the case of well-defined monomodal distributions. Moreover, one should asses the shape of the droplets prior to data interpretation, as usual in scattering methods, by an independent method. Anyway the shape of the time correlation functions of the scattered intensity should be reported or at least inspected as they provide information on the reproducibility of the experiments hence safegarding the value of the physical meaning of the final value of droplet size (Rh). Preferentially static light scattering (SLS) measurements should always support DLS experiments as the angular dependence is very sensitive to the presence of large particles.status: publishe