Light-induced changes in fatty acid profiles of specific lipid classes in several freshwater phytoplankton species

We tested the influence of two light intensities [40 and 300 µmol PAR / (m² s)] on the fatty acid composition of three distinct lipid classes in four freshwater phytoplankton species. We chose species of different taxonomic classes in order to detect potentially similar reaction characteristics that might also be present in natural phytoplankton communities. From samples of the bacillariophyte Asterionella formosa, the chrysophyte Chromulina sp., the cryptophyte Cryptomonas ovata and the zygnematophyte Cosmarium botrytis we first separated glycolipids (monogalactosyldiacylglycerol, digalactosyldiacylglycerol, and sulfoquinovosyldiacylglycerol), phospholipids (phosphatidylcholine, phosphatidylethanol-amine, phosphatidylglycerol, phosphatidylinositol, and phosphatidylserine) as well as non-polar lipids (triacylglycerols), before analyzing the fatty acid composition of each lipid class. High variation in the fatty acid composition existed among different species. Individual fatty acid compositions differed in their reaction to changing light intensities in the four species. Although no generalizations could be made for species across taxonomic classes, individual species showed clear but small responses in their ecologically-relevant omega-3 and omega-6 polyunsaturated fatty acids in terms of proportions and of per carbon quotas. Knowledge on how lipids like fatty acids change with environmental or culture conditions is of great interest in ecological food web studies, aquaculture and biotechnology, since algal lipids are the most important sources of omega-3 long-chain polyunsaturated fatty acids for aquatic and terrestrial consumers, including human

A comparison of random forests, boosting and support vector machines for genomic selection

Genomic selection (GS) involves estimating breeding values using molecular markers spanning the entire genome. Accurate prediction of genomic breeding values (GEBVs) presents a central challenge to contemporary plant and animal breeders. The existence of a wide array of marker-based approaches for predicting breeding values makes it essential to evaluate and compare their relative predictive performances to identify approaches able to accurately predict breeding values. We evaluated the predictive accuracy of random forests (RF), stochastic gradient boosting (boosting) and support vector machines (SVMs) for predicting genomic breeding values using dense SNP markers and explored the utility of RF for ranking the predictive importance of markers for pre-screening markers or discovering chromosomal locations of QTLs

Getting the Most Out of Sorghum Low-Input Field Trials in West Africa Using Spatial Adjustment

Breeding sorghum for low-input conditions is hindered by soil heterogeneity. Spatial adjustment using mixed models can help account for this variation and increase precision of low-input field trials. Large small-scale spatial variation (CV 39.4 %) for plant available phosphorus was mapped in an intensely sampled low-input field. Spatial adjustments were shown to account for residual yield differences because of this and other growth factors. To investigate the potential of such models to increase the efficiency of low- and high-input field trials, 17 experiments with 70 sorghum genotypes conducted in Mali, West Africa, were analysed for grain yield using different mixed models including models with autoregressive spatial correlation terms. Spatial models (AR1, AR2) improved broad sense heritability estimates for grain yield, averaging gains of 10 and 6 % points relative to randomized complete block (RCB) and lattice models, respectively. The heritability estimate gains were even higher under low phosphorus conditions and in two-replicate analyses. No specific model was best for all environments. A single spatial model, AR1 × AR1, captured most of the gains for heritability and relative efficiency provided by the best model identified for each environment using Akaike's Information Criterion. Spatial modelling resulted in important changes in genotype ranking for grain yield. Thus, the use of spatial models was shown to have potentially important consequences for aiding effective sorghum selection in West Africa, particularly under low-input conditions and for trials with fewer replications. Thus, using spatial models can improve the resource allocation of a breeding program. Furthermore, our results show that good experimental design with optimal placement and orientation of blocks is essential for efficient statistical analysis with or without spatial adjustment

Farmer Participatory Early-Generation Yield Testing of Sorghum in West Africa: Possibilities to Optimize Genetic Gains for Yield in Farmers’ Fields

The effectiveness of on-farm and/or on-station early generation yield testing was examined to maximize the genetic gains for sorghum yield under smallholder famer production conditions in West Africa. On-farm first-stage yield trials (augmented design, 150 genotypes with subsets of 50 genotypes tested per farmer) and second-stage yield trials (replicated α-lattice design, 21 test genotypes) were conducted, as well as on-station α-lattice first- and second-stage trials under contrasting phosphorous conditions. On-farm testing was effective, with yield showing significant genetic variance and acceptable heritabilities (0.56 in first- and 0.61 to 0.83 in second-stage trials). Predicted genetic gains from on-station yield trials were always less than from direct testing on-farm, although on-station trials under low-phosphorus and combined over multiple environments improved selection efficiencies. Modeling alternative designs for on-farm yield testing (augmented, farmer-as-incomplete-block, multiple lattice, and augmented p-rep) indicated that acceptable heritabilities (0.57 to 0.65) could be obtained with all designs for testing 150 progenies in 20 trials and 75 plots per farmer. Ease of implementation and risk of errors would thus be key criteria for choice of design. Integrating results from on-station and on-farm yield testing appeared beneficial as progenies selected both by on-farm and on-station first-stage trials showed higher on-farm yields in second-stage testing

Quantum formulation for nanoscale optical and material chirality: symmetry issues, space and time parity, and observables

To properly represent the interplay and coupling of optical and material chirality at the photon-molecule or photon-nanoparticle level invites a recognition of quantum facets in the fundamental aspects and mechanisms of light-matter interaction. It is therefore appropriate to cast theory in a general quantum form, one that is applicable to both linear and nonlinear optics as well as various forms of chiroptical interaction including chiral optomechanics. Such a framework, fully accounting for both radiation and matter in quantum terms, facilitates the scrutiny and identification of key issues concerning spatial and temporal parity, scale, dissipation and measurement. Furthermore it fully provides for describing the interactions of light beams with a vortex character, and it leads to the complete identification of symmetry conditions for materials to provide for chiral discrimination. Quantum considerations also lend a distinctive perspective to the very different senses in which other aspects of chirality are recognized in metamaterials. Duly attending to the symmetry principles governing allowed or disallowed forms of chiral discrimination supports an objective appraisal of the experimental possibilities and developing applications

Selection Strategy for Sorghum Targeting Phosphorus-limited Environments in West Africa: Analysis of Multi-environment Experiments

Although sorghum [Sorghum bicolor (L.) Moench] in West Africa (WA) is generally cultivated with limited or no fertilization on soils of low phosphorus availability, no assessments of the genetic variation among WA sorghum varieties for adaptation to low soil P are known. We assessed grain yields of 70 diverse sorghum genotypes under −P (no P fertilization) and +P conditions at two locations in Mali over 5 yr. Genetic variation for grain yield under −P conditions and the feasibility and necessity of sorghum varietal testing for grain yield under −P conditions were evaluated. Delayed heading dates (0–9.8 d) and reductions of grain yield (2–59%) and plant height (13–107 cm) were observed in −P relative to the +P trials. High estimates of genetic variance and broad-sense heritabilities were found for grain yield across both −P (h2 = 0.93) and +P (h2 = 0.92) environments. The genetic correlation for grain yield performance between −P and +P conditions was high (rG = 0.89), suggesting that WA sorghum varieties generally possess good adaptation to low-P conditions. However, genotype × phosphorus crossover interaction was observed between some of the highest yielding genotypes from the −P and +P selected sets, with the variety IS 15401 showing specific adaptation to −P. Direct selection for grain yield in −P conditions was predicted to be 12% more efficient than indirect selection in +P conditions. Thus, selection under −P conditions should be useful for sorghum improvement in WA

Characterisation and correction of signal fluctuations in successive acquisitions of microarray images

<p>Abstract</p> <p>Background</p> <p>There are many sources of variation in dual labelled microarray experiments, including data acquisition and image processing. The final interpretation of experiments strongly relies on the accuracy of the measurement of the signal intensity. For low intensity spots in particular, accurately estimating gene expression variations remains a challenge as signal measurement is, in this case, highly subject to fluctuations.</p> <p>Results</p> <p>To evaluate the fluctuations in the fluorescence intensities of spots, we used series of successive scans, at the same settings, of whole genome arrays. We measured the decrease in fluorescence and we evaluated the influence of different parameters (PMT gain, resolution and chemistry of the slide) on the signal variability, at the level of the array as a whole and by intensity interval. Moreover, we assessed the effect of averaging scans on the fluctuations. We found that the extent of photo-bleaching was low and we established that 1) the fluorescence fluctuation is linked to the resolution e.g. it depends on the number of pixels in the spot 2) the fluorescence fluctuation increases as the scanner voltage increases and, moreover, is higher for the red as opposed to the green fluorescence which can introduce bias in the analysis 3) the signal variability is linked to the intensity level, it is higher for low intensities 4) the heterogeneity of the spots and the variability of the signal and the intensity ratios decrease when two or three scans are averaged.</p> <p>Conclusion</p> <p>Protocols consisting of two scans, one at low and one at high PMT gains, or multiple scans (ten scans) can introduce bias or be difficult to implement. We found that averaging two, or at most three, acquisitions of microarrays scanned at moderate photomultiplier settings (PMT gain) is sufficient to significantly improve the accuracy (quality) of the data and particularly those for spots having low intensities and we propose this as a general approach. For averaging and precise image alignment at sub-pixel levels we have made a program freely available on our web-site <url>http://bioinfome.cgm.cnrs-gif.fr</url> to facilitate implementation of this approach.</p