Clubroot (Plasmodiophora brassicae Woronin): an agricultural and biological challenge worldwide

Clubroot disease and the causal microbe Plasmodiophora brassicae offer abundant challenges to agriculturists and biological scientists. This microbe is well fitted for the environments which it inhabits. Plasmodiophora brassicae exists in soil as microscopic well protected resting spores and then grows actively and reproduces while shielded inside the roots of host plants. The pathogen is active outside the host for only short periods. Consequently, scientific studies are made challenging by the biological context of the host and pathogen and the technology required to investigate and understand that relationship. Controlling clubroot disease is a challenge for farmers, crop consultants and plant pathology practitioners because of the limited options which are available. Full symptom expression happens solely in members of the Brassicaceae family. Currently, only a few genes expressing strong resistance to P. brassicae are known and readily available. Agrochemical control is similarly limited by difficulties in molecule formulation which combines efficacy with environmental acceptability. Manipulation of husbandry encouraging improvements in soil structure, texture, nutrient composition and moisture content can reduce populations of P. brassicae. Integrating such strategies with rotation and crop management will reduce but not eliminate this disease. There are indications that forms of biological competition may be mobilised as additions to integrated control strategies. The aim of this review is to chart key themes in the development of scientific biological understanding of this host-pathogen relationship by offering signposts to grapple with clubroot disease which devastates crops and their profitability. Particular attention is given to the link between soil and nutrient chemistry and activity of this microbe

Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.)

A transcript map has been constructed by the development and integration of genic molecular markers (GMMs) including single nucleotide polymorphism (SNP), genic microsatellite or simple sequence repeat (SSR) and intron spanning region (ISR)-based markers, on an inter-specific mapping population of chickpea, the third food legume crop of the world and the first food legume crop of India. For SNP discovery through allele re-sequencing, primer pairs were designed for 688 genes/expressed sequence tags (ESTs) of chickpea and 657 genes/ESTs of closely related species of chickpea. High-quality sequence data obtained for 220 candidate genic regions on 2–20 genotypes representing 9 Cicer species provided 1,893 SNPs with an average frequency of 1/35.83 bp and 0.34 PIC (polymorphism information content) value. On an average 2.9 haplotypes were present in 220 candidate genic regions with an average haplotype diversity of 0.6326. SNP2CAPS analysis of 220 sequence alignments, as mentioned above, provided a total of 192 CAPS candidates. Experimental analysis of these 192 CAPS candidates together with 87 CAPS candidates identified earlier through in silico mining of ESTs provided scorable amplification in 173 (62.01%) cases of which predicted assays were validated in 143 (82.66%) cases (CGMM). Alignments of chickpea unigenes with Medicago truncatula genome were used to develop 121 intron spanning region (CISR) markers of which 87 yielded scorable products. In addition, optimization of 77 EST-derived SSR (ICCeM) markers provided 51 scorable markers. Screening of easily assayable 281 markers including 143 CGMMs, 87 CISRs and 51 ICCeMs on 5 parental genotypes of three mapping populations identified 104 polymorphic markers including 90 markers on the inter-specific mapping population. Sixty-two of these GMMs together with 218 earlier published markers (including 64 GMM loci) and 20 other unpublished markers could be integrated into this genetic map. A genetic map developed here, therefore, has a total of 300 loci including 126 GMM loci and spans 766.56 cM, with an average inter-marker distance of 2.55 cM. In summary, this is the first report on the development of large-scale genic markers including development of easily assayable markers and a transcript map of chickpea. These resources should be useful not only for genome analysis and genetics and breeding applications of chickpea, but also for comparative legume genomics

Brassinosteroid leaf unrolling QTL mapping in durum wheat

Brassinosteroids are a newly reported class of plant growth phytohormones found in plants throughout the plant kingdom. Functioning at very low concentrations, they play an essential role in improving biomass yield and stress tolerance. There are no reports in the literature of the genetic variability of responsiveness of brassinosteroids in wheat; most studies on brassinosteroids have focused on the physiological effects of exogenous addition of brassinosteroids. Our aim was to study the genetic variation in the responsiveness of a doubled haploid durum wheat population to three brassinosteroid concentrations using the leaf unrolling test, which is a simple bioassay to test brassinosteroid activity. An F1-derived doubled haploid population of 77 individuals from the cross Strongfield/Blackbird was used to construct a genetic map of 427 molecular marker loci. The leaf unrolling test was performed on the parents and doubled haploid genotypes of the population using 0.2, 2 and 20 nM brassinosteroid concentrations. The results indicated significant differences in leaf unrolling between the two parents, doubled haploid genotypes, treatments and genotype-by-treatment combinations. Transgressive segregation beyond Strongfield of leaf unrolling was observed for all concentrations, with the strongest response at 20 nM. Putative quantitative trait loci were revealed in the intervals Xgwm2-Xbarc45 on chromosome 3A and Xwmc643a-Xwmc625a on chromosome 3B. Additional quantitative trait loci were associated with markers Xwmc48a, Xwmc511, Xwmc89a and Xgwmc692 on chromosome 4B, and Xwmc17 on chromosome 7A. This work should enhance the understanding of the relationship between stress tolerance and productivity, and responsiveness to brassinosteroids