Plants have evolved systems analogous to animal innate immunity that recognise pathogen-associated molecular patterns (PAMPs). PAMP detection is an important component of non-host resistance in plants and serves as an early warning system for the presence of potential pathogens. Binding of a PAMP to the appropriate pattern recognition receptor leads to downstream signalling events and, ultimately, to the induction of basal defence systems. To overcome non-host resistance, pathogens have evolved effectors that target specific regulatory components of the basal defence system. In turn, this has led to the evolution in plants of cultivar-specific resistance mediated by R proteins, which guard the targets of effectors against pathogen manipulation; the arms race continues.

A Rac–PAK1–Ajuba feedback loop stabilizes cadherin complexes via coordination of spatiotemporal signaling with actin remodeling at cell–cell contacts.

BackgroundGray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C. zeina limits production of this staple food crop.ResultsA maize RIL population (F7:S6) from a cross between CML444 and SC Malawi was field-tested under GLS disease pressure at five field sites over three seasons in KwaZulu-Natal, South Africa. Thirty QTL identified from eleven field trials (environments) were consolidated to seven QTL for GLS resistance based on their expression in at least two environments and location in the same core maize bins. Four GLS resistance alleles were derived from the more resistant parent CML444 (bin 1.10, 4.08, 9.04/9.05, 10.06/10.07), whereas the remainder were from SC Malawi (bin 6.06/6.07, 7.02/7.03, 9.06). QTLs in bin 4.08 and bin 6.06/6.07 were also detected as joint QTLs, each explained more than 11% of the phenotypic variation, and were identified in four and seven environments, respectively. Common markers were used to allocate GLS QTL from eleven previous studies to bins on the IBM2005 map, and GLS QTL “hotspots” were noted. Bin 4.08 and 7.02/7.03 GLS QTL from this study overlapped with hotspots, whereas the bin 6.06/6.07 and bin 9.06 QTLs appeared to be unique. QTL for flowering time (bin 1.07, 4.09) in this population did not correspond to QTL for GLS resistance.ConclusionsQTL mapping of a RIL population from the subtropical maize parents CML444 and SC Malawi identified seven QTL for resistance to gray leaf spot disease caused by C. zeina. These QTL together with QTL from eleven studies were allocated to bins on the IBM2005 map to provide a basis for comparison. Hotspots of GLS QTL were identified on chromosomes one, two, four, five and seven, with QTL in the current study overlapping with two of these. Two QTL from this study did not overlap with previously reported QTL.

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.

Obesity prevalences are increasing in industrialized and developing countries. As a pilot for a comparative study of physical activity and weight change, we assessed energy expenditure (EE) in young black South African adults living in an urban informal settlement. Total EE (TEE) was assessed using doubly labeled water, activity EE (AEE) and activity patterns by accelerometry and body composition by isotope dilution. Twenty young women and eight men were enrolled. Over 50% of the women and no men were obese (mean BMI 31.0 and 21.6 kg/m 2 , respectively). Women had significantly lower TEE and AEE after adjustment for body size, as well as lower levels of moderate and vigorous activity. Neither TEE nor AEE was associated with BMI or percent body fat, whereas percent time in vigorous activity was modestly negatively associated with adiposity. These data add to the small literature on EE and activity among populations undergoing epidemiologic transitions. ( The prevalence of obesity, coupled with rising rates of type II diabetes and cardiovascular diseases, is increasing dramatically in many developing countries (Zimmet, 2003;Popkin and Gordon-Larsen 2004). These trends mirror a number of environmental changes associated with increased globalization of economies and societal behaviors; quantitative data on even the most basic aspects of these changes are limited. European Journal of Clinical NutritionAt a superficial level, overweight is caused by chronic energy imbalance, that is, this has been attributed to both population-level declines in habitual physical activity and dietary changes and increases in consumption of energy dense foods (Popkin and Gordon-Larsen, 2004). There are, however, relatively few data on total energy expenditure (TEE) and physical activity patterns from developing country populations.We present EE data from black South African young adults residing in an urban informal settlement, collected using the doubly labeled water (DLW) method and accelerometry.These pilot data were collected as part of an international comparative study on EE and weight change.Twenty women and eight men were recruited from Khayelitsha, an urban informal settlement, located in Cape Town, South Africa, in 2006. All participants were healthy by self-report, not taking medications and free of conditions, which might impede activity. The study was approved by the Research and Ethics Committees of the University of Cape Town and the Institutional Review Board of Loyola University Chicago. All participants gave written informed consent.Participants had TEE measured using the DLW two-point method, described earlier (Schoeller and van Santen, 1982). Resting EE (REE) was estimated from fat-free mass (FFM) (Cunningham, 1991). Activity EE (AEE) was calculated: AEE ¼ (0.9*TEE)ÀREE, the term '(0.9*TEE)' represents the estimated 10% of TEE expended as the thermic effect of food. Body composition was measured using the isotope dilution method (Schoeller et al., 1985). Accelerometry was used in a subset of the participants (thirtee...