Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices

Genomic prediction models are often calibrated using multi-generation data. Over time, as data accumulates, training data sets become increasingly heterogeneous. Differences in allele frequency and linkage disequilibrium patterns between the training and prediction genotypes may limit prediction accuracy. This leads to the question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Previous research on training set optimization has focused on identifying a subset of the available data that is optimal for a given prediction set. However, this approach does not contemplate the possibility that different training sets may be optimal for different prediction genotypes. To address this problem, we recently introduced a sparse selection index (SSI) that identifies an optimal training set for each individual in a prediction set. Using additive genomic relationships, the SSI can provide increased accuracy relative to genomic-BLUP (GBLUP). Non-parametric genomic models using Gaussian kernels (KBLUP) have, in some cases, yielded higher prediction accuracies than standard additive models. Therefore, here we studied whether combining SSIs and kernel methods could further improve prediction accuracy when training genomic models using multi-generation data. Using four years of doubled haploid maize data from the International Maize and Wheat Improvement Center (CIMMYT), we found that when predicting grain yield the KBLUP outperformed the GBLUP, and that using SSI with additive relationships (GSSI) lead to 5–17% increases in accuracy, relative to the GBLUP. However, differences in prediction accuracy between the KBLUP and the kernel-based SSI were smaller and not always significant.Subject terms: Quantitative trait, Genetic models     

Decreases in Fire Spread Probability with Forest Age Promotes Alternative Community States, Reduced Resilience to Climate Variability and Large Fire Regime Shifts

The generalization that plant communities increase in flammability as they age and invariably lead to resilient self-organized landscape mosaics is being increasingly challenged. Plant communities often exhibit rapidly saturating or even hump-shaped age-flammability trajectories and landscapes often display strong non-linear behaviors, abrupt shifts, and self-reinforcing alternative community states. This plethora of fire-landscape interactions calls for a more general model that considers alternative age-flammability rules. We simulated landscape dynamics assuming communities that (1) increase in flammability with age and (2) gain flammability up to a certain age followed by a slight and moderate loss to a constant value. Simulations were run under combinations of ignition frequency and interannual climatic variability. Age-increasing fire probability promoted high resilience to changes in ignition frequency and climatic variability whereas humpbacked-shaped age-flammability led to strong non-linear behaviors. Moderate (20%) reductions in mature compared to peak flammability produced the least resilient behaviors. The relatively non-flammable mature forest matrix intersected by young flammable patches is prone to break up and disintegrate with slight increases in ignition/climate variability causing large-scale shifts in the fire regime because large fires were able to sweep through the more continuous young/flammable landscape. Contrary to the dominant perception, fire suppression in landscapes with positive feedbacks may effectively reduce fire occurrence by allowing less flammable later stage communities composed of longer lived, obligate seeders to replace earlier stages of light demanding, often more flammable resprouters. Conversely, increases in anthropogenic ignitions, a common global trend of many forested regions may, in synergism with increased climate variability, induce abrupt shifts, and large-scale forest degradation.     

Variation in the incidence of H2-oxidizing chemolithotrophic bacteria in rice grown under different cultivation conditions

Summary The incidence of H₂-oxidizing chemolithotrophic bacteria associated with rice grown under continuous wetland, upland, and rainfed wetland conditions was studied by¹⁴C-autoradiographic technique in a neutral soil at IRRI (Maahas) and an acid rainfed wetland soil (Luisiana).In Maahas soil, H₂-oxidizing chemolithotrophic bacteria were not detected in the endorhizosphere, rhizosphere, and nonrhizosphere soil of rice grown under dryland conditions. Under continuously flooded conditions a very large population of these bacteria were found in the endorhizosphere but not in the oxidized and reduced soil.A very low population of these bacteria were found in the endorhizosphere and basal culm of rice grown under rainfed wetland conditions at Luisiana. Bacteria isolated from Maahas wetland rice and inoculated to rice seedling planted in Luisiana soil failed to establish.Both Maahas and Luisiana soils consumed externally supplied H₂ and produced H₂ and CH₄ almost at the same rate when they were amended with rice straw or sucrose. This paper discusses possible causes of variation in the number of these bacteria and their distribution in rice grown under different cultural and soil conditions.     

Genetic analysis of agronomic characters in chickpea

Summary Twenty-eight diallel trials over 8 years and two locations were analysed to estimate genetic variances for agronomic characters of chickpea (Cicer arietinum L.). The data were analysed according to Method 4 and Model I of Griffing (1956). Days to flowering, plant height, and seed size were found to be predominantly under additive inheritance and were highly predictable. Both additive and non-additive genetic components were important for seed yield, number of branches, pods per plant, and seeds per pod. Although both general combining ability (gca) and specific combining ability (sca) varied significantly with generation, components of gca mean squares were invariably much larger than gca x generation interaction components, indicating that either the F₁ or the F₂ generation can be used to estimate the gca components effectively. Combined diallel analysis of F₂s over locations revealed the importance of combining ability x location interactions and emphasized the need for testing over more than one location for the precise estimation of combining ability. The implications of these findings and those reported earlier in the literature on the breeding strategies/methods for the genetic improvement of agronomic characters in chickpea are discussed.ICRISAT journal article no. 1199     

Analysis of the amino acid sequences of plant Bowman-Birk inhibitors

Plant seeds contain a large number of protease inhibitors of animal, fungal, and bacterial origin. One of the well-studied families of these inhibitors is the Bowman-Birk family(BBI). The BBIs from dicotyledonous seeds are 8K, double-headed proteins. In contrast, the 8K inhibitors from monocotyledonous seeds are single headed. Monocots also have a 16K, double-headed inhibitor. We have determined the primary structure of a Bowman-Birk inhibitor from a dicot, horsegram, by sequential edman analysis of the intact protein and peptides derived from enzymatic and chemical cleavage. The 76-residue-long inhibitor is very similar to that ofMacrotyloma axillare. An analysis of this inhibitor along with 26 other Bowman-Birk inhibitor domains (MW 8K) available in the SWISSPROT databank revealed that the proteins from monocots and dicots belong to related but distinct families. Inhibitors from monocots show larger variation in sequence. Sequence comparison shows that a crucial disulphide which connects the amino and carboxy termini of the active site loop is lost in monocots. The loss of a reactive site in monocots seems to be correlated to this. However, it appears that this disulphide is not absolutely essential for retention of inhibitory function. Our analysis suggests that gene duplication leading to a 16K inhibitor in monocots has occurred, probably after the divergence of monocots and dicots, and also after the loss of second reactive site in monocots. S. Selvaraj is on leave from Department of Physics, Bharathidasan University, Tiruchirapalli 620 024, Tamilnadu, India Correspondence to: M.R.N. Murthy     

Highly efficient preparation of sphingoid bases from glucosylceramides by chemoenzymatic method

Sphingoid base derivatives have attracted increasing attention as promising chemotherapeutic candidates against lifestyle diseases such as diabetes and cancer. Natural sphingoid bases can be a potential resource instead of those derived by time-consuming total organic synthesis. In particular, glucosylceramides (GlcCers) in food plants are enriched sources of sphingoid bases, differing from those of animals. Several chemical methodologies to transform GlcCers to sphingoid bases have already investigated; however, these conventional methods using acid or alkaline hydrolysis are not efficient due to poor reaction yield, producing complex by-products and resulting in separation problems. In this study, an extremely efficient and practical chemoenzymatic transformation method has been developed using microwave-enhanced butanolysis of GlcCers and a large amount of readily available almond β-glucosidase for its deglycosylation reaction of lysoGlcCers. The method is superior to conventional acid/base hydrolysis methods in its rapidity and its reaction cleanness (no isomerization, no rearrangement) with excellent overall yield.     

Taste Masking of Griseofulvin and Caffeine Anhydrous Using Kleptose Linecaps DE17 by Hot Melt Extrusion

The objective of this project was to investigate the potential of Kleptose Linecaps DE17 (KLD) in masking the unpleasant/bitter taste of therapeutic agents by hot melt extrusion (HME). Griseofulvin (GRI) and caffeine anhydrous (CA) were used as a bitter active pharmaceutical ingredient (API) model drugs. Thermogravimetric studies confirmed the stability of GRI, CA, and KLD at the employed extrusion temperatures. The differential scanning calorimetry (DSC) studies revealed a characteristic melting endotherm of GRI at 218–220°C and CA at 230–232°C in the physical mixtures as well as in all extrudates over the period of study, indicating the crystalline nature of drug. HME of KLD was achieved only in the presence of plasticizer. Among the several plasticizers investigated, xylitol showed improved processability of KLD at 15% w/w concentration. Dissolution studies of HME extrudates using simulated salivary medium exhibited ～threefold less release compared to physical mixture at the end of 5 min (the lesser drug release, better the taste masking efficiency). Furthermore, the results from the sensory evaluation of products in human panel demonstrated strong bitter taste in the case of physical mixture compared to the HME formulation, suggesting the potential of Kleptose Linecaps DE17 as taste masking polymer in melt extruded form.