Plant training for induced defense against insect pests: a promising tool for integrated pest management in cotton.

Enhancing cotton pest management using plant natural defenses has been described as a promising way to improve the management of crop pests. We here reviewed various studies on cotton growing systems to illustrate how an ancient technique called plant training, which includes plant topping and pruning, may contribute to this goal. Using examples from cotton crops, we show how trained plants can be brought to a state of enhanced defense that causes faster and more robust activation of their defense responses. We revisit the agricultural benefits associated with this technique in cotton crops, with a focus on its potential as a supplementary tool for integrated pest management (IPM). In particular, we examine its role in mediating plant interactions with conspecific neighboring plants, pests and associated natural enemies. We propose a new IPM tool, plant training for induced defense, which involves inducing plant defense through artificial injury. Experimental evidence from various studies shows that cotton training is a promising technique, particularly for smallholders, which can be used as part of an IPM program to significantly reduce insecticide use and to improve productivity in cotton farming. © 2018 Society of Chemical Industry.

cDNA-AFLP-based genetical genomics in cotton fibers.

Genetical genomics, or genetic analysis applied to gene expression data, has not been widely used in plants. We used quantitative cDNA-AFLP to monitor the variation in the expression level of cotton fiber transcripts among a population of inter-specific Gossypium hirsutum × G. barbadense recombinant inbred lines (RILs). Two key fiber developmental stages, elongation (10 days post anthesis, dpa), and secondary cell wall thickening (22 dpa), were studied. Normalized intensity ratios of 3,263 and 1,201 transcript-derived fragments (TDFs) segregating over 88 RILs were analyzed for quantitative trait loci (QTL) mapping for the 10 and 22 dpa fibers, respectively. Two-thirds of all TDFs mapped between 1 and 6 eQTLs (LOD > 3.5). Chromosome 21 had a higher density of eQTLs than other chromosomes in both data sets and, within chromosomes, hotspots of presumably trans-acting eQTLs were identified. The eQTL hotspots were compared to the location of phenotypic QTLs for fiber characteristics among the RILs, and several cases of co-localization were detected. Quantitative RT-PCR for 15 sequenced TDFs showed that 3 TDFs had at least one eQTL at a similar location to those identified by cDNA-AFLP, while 3 other TDFs mapped an eQTL at a similar location but with opposite additive effect. In conclusion, cDNA-AFLP proved to be a cost-effective and highly transferable platform for genome-wide and population-wide gene expression profiling. Because TDFs are anonymous, further validation and interpretation (in silico analysis, qPCR gene profiling) of the eQTL and eQTL hotspots will be facilitated by the increasing availability of cDNA and genomic sequence resources in cotton.

Meta-analysis of cotton fiber quality QTLs across diverse environments in a Gossypium hirsutum x G. barbadense RIL population.

BACKGROUND: Cotton fibers (produced by Gossypium species) are the premier natural fibers for textile production. The two tetraploid species, G. barbadense (Gb) and G. hirsutum (Gh), differ significantly in their fiber properties, the former having much longer, finer and stronger fibers that are highly prized. A better understanding of the genetics and underlying biological causes of these differences will aid further improvement of cotton quality through breeding and biotechnology. We evaluated an inter-specific Gh x Gb recombinant inbred line (RIL) population for fiber characteristics in 11 independent experiments under field and glasshouse conditions. Sites were located on 4 continents and 5 countries and some locations were analyzed over multiple years. RESULTS: The RIL population displayed a large variability for all major fiber traits. QTL analyses were performed on a per-site basis by composite interval mapping. Among the 651 putative QTLs (LOD > 2), 167 had a LOD exceeding permutation based thresholds. Coincidence in QTL location across data sets was assessed for the fiber trait categories strength, elongation, length, length uniformity, fineness/maturity, and color. A meta-analysis of more than a thousand putative QTLs was conducted with MetaQTL software to integrate QTL data from the RIL and 3 backcross populations (from the same parents) and to compare them with the literature. Although the global level of congruence across experiments and populations was generally moderate, the QTL clustering was possible for 30 trait x chromosome combinations (5 traits in 19 different chromosomes) where an effective co-localization of unidirectional (similar sign of additivity) QTLs from at least 5 different data sets was observed. Most consistent meta-clusters were identified for fiber color on chromosomes c6, c8 and c25, fineness on c15, and fiber length on c3. CONCLUSIONS: Meta-analysis provided a reliable means of integrating phenotypic and genetic mapping data across multiple populations and environments for complex fiber traits. The consistent chromosomal regions contributing to fiber quality traits constitute good candidates for the further dissection of the genetic and genomic factors underlying important fiber characteristics, and for marker-assisted selection.