RNA-Seq reveals a xenobiotic stress response in the soybean aphid, Aphis glycines, when fed aphid-resistant soybean

Partial funding for Open Access provided by The Ohio State University Open Access Fund.Background: While much recent research has expanded our understanding of the molecular interactions between aphids and their host plants, it is lacking for the soybean aphid, Aphis glycines. Since its North American invasion, A. glycines has become one of the most damaging insect pests on this important crop. Five soybean genes for host plant resistance to A. glycines have been identified, but populations of A. glycines have already adapted to overcome these resistance genes. Understanding the molecular interactions between resistant soybean and A. glycines can provide clues to its adaptation mechanisms. Here, we used RNA-Sequencing to compare and contrast A. glycines gene expression when fed resistant (Rag1) and susceptible soybean. Results: Combining results from a previous A. glycines transcriptome, we generated 64,860 high quality transcripts, totaling 41,151,086 bases. Statistical analysis revealed 914 genes with significant differential expression. Most genes with higher expression in A. glycines on resistant plants (N = 352) were related to stress and detoxification such as cytochrome P450s, glutathione-S-transferases, carboxyesterases, and ABC transporters. A total of 562 genes showed lower transcript abundance in A. glycines on resistant plants. From our extensive transcriptome data, we also identified genes encoding for putative salivary effector proteins (N = 73). Among these, 6 effector genes have lower transcript abundance in A. glycines feeding on resistant soybean. Conclusions: Overall, A. glycines exhibited a pattern typical of xenobiotic challenge, thereby validating antibiosis in Rag1, presumably mediated through toxic secondary metabolites. Additionally, this study identified many A. glycines genes and gene families at the forefront of its molecular interaction with soybean. Further investigation of these genes in other biotypes may reveal adaptation mechanisms to resistant plants

Combining Next-Generation Sequencing Strategies for Rapid Molecular Resource Development from an Invasive Aphid Species, Aphis glycines

Aphids are one of the most important insect taxa in terms of ecology, evolutionary biology, genetics and genomics, and interactions with endosymbionts. Additionally, many aphids are serious pest species of agricultural and horticultural plants. Recent genetic and genomic research has expanded molecular resources for many aphid species, including the whole genome sequencing of the pea aphid, Acrythosiphon pisum. However, the invasive soybean aphid, Aphis glycines, lacks in any significant molecular resources.Two next-generation sequencing technologies (Roche-454 and Illumina GA-II) were used in a combined approach to develop both transcriptomic and genomic resources, including expressed genes and molecular markers. Over 278 million bp were sequenced among the two methods, resulting in 19,293 transcripts and 56,688 genomic sequences. From this data set, 635 SNPs and 1,382 microsatellite markers were identified. For each sequencing method, different soybean aphid biotypes were used which revealed potential biotype specific markers. In addition, we uncovered 39,822 bp of sequence that were related to the obligatory endosymbiont, Buchnera aphidicola, as well as sequences that suggest the presence of Hamiltonella defensa, a facultative endosymbiont.Molecular resources for an invasive, non-model aphid species were generated. Additionally, the power of next-generation sequencing to uncover endosymbionts was demonstrated. The resources presented here will complement ongoing molecular studies within the Aphididae, including the pea aphid whole genome, lead to better understanding of aphid adaptation and evolution, and help provide novel targets for soybean aphid control

Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachishypogaea L.)

Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 × ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2–3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48–33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3–15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54–44.72% PVE) and 63 (7.11–21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7–8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2–9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut

Optimum biorefinery pathways selection using the integer cuts constraint method applied to a MILP problem.

Biorefineries are multi-product facilities that convert biomass into a broad variety of products (energy, biofuels, chemicals, feed, and food). In this paper, a new systematic approach to select and rank different biorefinery conversion pathways is proposed using the Integer-Cut Constraint (ICC) method applied to a MILP problem. In particular, two different statements of the constraints are analyzed. The first step is building a superstructure collecting several biomass conversion models. The ICC method allows different conversion pathways to be evaluated inside the superstructure and ordered according to the objective function values. The key value of a rank of pathways including suboptimal routes allows a fair comparison between alternative biorefinery options and may widen the choice to suboptimal ones. The method is applied to a case study in which various biomass-to-fuel technologies are analyzed to set up a rank of the most promising conversion processes in the current Swiss market