Eucalyptus grandis is a commercially important hardwood species and is known to be susceptible to a number of pests and pathogens. Determining mechanisms of defense is therefore a research priority. The published genome for E. grandis has aided the identification of one important class of resistance (R) genes that incorporate nucleotide binding sites and leucine-rich repeat domains (NBS-LRR). Using an iterative search process we identified NBS-LRR gene models within the E. grandis genome. We characterized the gene models and identified their genomic arrangement. The gene expression patterns were examined in E. grandis clones, challenged with a fungal pathogen (Chrysoporthe austroafricana) and insect pest (Leptocybe invasa). One thousand two hundred and fifteen putative NBS-LRR coding sequences were located which aligned into two large classes, Toll or interleukin-1 receptor (TIR) and coiled-coil (CC) based on NB-ARC domains. NBS-LRR gene-rich regions were identified with 76% organized in clusters of three or more genes. A further 272 putative incomplete resistance genes were also identified. We determined that E. grandis has a higher ratio of TIR to CC classed genes compared to other woody plant species as well as a smaller percentage of single NBS-LRR genes. Transcriptome profiles indicated expression hotspots, within physical clusters, including expression of many incomplete genes. The clustering of putative NBS-LRR genes correlates with differential expression responses in resistant and susceptible plants indicating functional relevance for the physical arrangement of this gene family. This analysis of the repertoire and expression of E. grandis putative NBS-LRR genes provides an important resource for the identification of novel and functional R-genes; a key objective for strategies to enhance resilience.
As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.systems genetics | lignocellulosic biomass | cell wall | bioenergy | network-based data integration
We used a systems genetics approach to elucidate the molecular mechanisms of the responses of maize to grey leaf spot (GLS) disease caused by Cercospora zeina, a threat to maize production globally. Expression analysis of earleaf samples in a subtropical maize recombinant inbred line population (CML444 × SC Malawi) subjected in the field to C. zeina infection allowed detection of 20 206 expression quantitative trait loci (eQTLs). Four trans-eQTL hotspots coincided with GLS disease QTLs mapped in the same field experiment. Co-expression network analysis identified three expression modules correlated with GLS disease scores. The module (GY-s) most highly correlated with susceptibility (r = 0.71; 179 genes) was enriched for the glyoxylate pathway, lipid metabolism, diterpenoid biosynthesis and responses to pathogen molecules such as chitin. The GY-s module was enriched for genes with trans-eQTLs in hotspots on chromosomes 9 and 10, which also coincided with phenotypic QTLs for susceptibility to GLS. This transcriptional network has significant overlap with the GLS susceptibility response of maize line B73, and may reflect pathogen manipulation for nutrient acquisition and/or unsuccessful defence responses, such as kauralexin production by the diterpenoid biosynthesis pathway. The co-expression module that correlated best with resistance (TQ-r; 1498 genes) was enriched for genes with trans-eQTLs in hotspots coinciding with GLS resistance QTLs on chromosome 9. Jasmonate responses were implicated in resistance to GLS through co-expression of COI1 and enrichment of genes with the Gene Ontology term 'cullin-RING ubiquitin ligase complex' in the TQ-r module. Consistent with this, JAZ repressor expression was highly correlated with the severity of GLS disease in the GY-s susceptibility network.
BackgroundThe Democratic Republic of the Congo (DRC) is characterized as a holoendemic malaria area with the main vectors being Anopheles funestus and members of the Anopheles gambiae complex. Due to political instability and socio-economic challenges in the region, knowledge of insecticide resistance status and resistance mechanisms in these vectors is limited. Mosquitoes were collected from a mining site in the north-eastern part of the country and, following identification, were subjected to extensive testing for the target-site and biochemical basis of resistance. Quantitative real-time PCR was used to assess a suite of 10 genes frequently involved in pyrethroid and dichlorodiphenyltrichloroethane (DDT) resistance in An. gambiae females and males. In An. funestus, gene expression microarray analysis was carried out on female mosquitoes.ResultsIn both species, deltamethrin resistance was recorded along with high resistance and suspected resistance to DDT in An. gambiae and An. funestus, respectively. A total of 85% of An. gambiae carried the kdr mutations as either homozygous resistant (RR) (L1014S, L1014F or both) or heterozygous (RS), however only 3% carried the rdl mutant allele (RS) and no ace-1 mutations were recorded. Synergist assays indicated a strong role for P450s in deltamethrin resistance in both species. In An. gambiae, analysis of transcription levels showed that the glutathione-S-transferase, GSTS1-2, produced the highest fold change in expression (7.6-fold in females and 31-fold in males) followed by GSTE2, thioredoxin peroxidase (TPX2), and cytochrome oxidases (CYP6M2 and CYP6P1). All other genes tested produced fold change values below 2. Microarray analysis revealed significant over-transcription of cuticular proteins as well as CYP6M7, CYP6P9a and CYP6P9b in insecticide resistant An. funestus.ConclusionsThese data show that high levels of deltamethrin resistance in the main malaria vector species, conferred by enzymatic detoxification, are present in the DRC.Electronic supplementary materialThe online version of this article (10.1186/s12936-017-2099-y) contains supplementary material, which is available to authorized users.
Leptocybe invasa is an insect pest causing gall formation on oviposited shoot tips and leaves of Eucalyptus trees leading to leaf deformation, stunting, and death in severe cases. We previously observed different constitutive and induced terpenes, plant specialized metabolites that may act as attractants or repellents to insects, in a resistant and susceptible clone of Eucalyptus challenged with L. invasa. We tested the hypothesis that specific terpenes are associated with pest resistance in a Eucalyptus grandis half-sib population. Insect damage was scored over 2 infestation cycles, and leaves were harvested for near-infrared reflectance (NIR) and terpene measurements. We used Bayesian model averaging for terpene selection and obtained partial least squares NIR models to predict terpene content and L. invasa infestation damage. In our optimal model, 29% of the phenotypic variation could be explained by 7 terpenes, and the monoterpene combination, limonene, α-terpineol, and 1,8-cineole, could be predicted with an NIR prediction ability of .67. Bayesian model averaging supported α-pinene, γ-terpinene, and iso-pinocarveol as important for predicting L. invasa infestation. Susceptibility was associated with increased γ-terpinene and α-pinene, which may act as a pest attractant, whereas reduced susceptibility was associated with iso-pinocarveol, which may act to recruit parasitoids or have direct toxic effects.
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