Soil coring at multiple field environments can directly quantify variation in deep root traits to select wheat genotypes for breeding.

We aim to incorporate deep root traits into future wheat varieties to increase access to stored soil water during grain development, which is twice as valuable for yield as water captured at younger stages. Most root phenotyping efforts have been indirect studies in the laboratory, at young plant stages, or using indirect shoot measures. Here, soil coring to 2 m depth was used across three field environments to directly phenotype deep root traits on grain development (depth, descent rate, density, length, and distribution). Shoot phenotypes at coring included canopy temperature depression, chlorophyll reflectance, and green leaf scoring, with developmental stage, biomass, and yield. Current varieties, and genotypes with breeding histories and plant architectures expected to promote deep roots, were used to maximize identification of variation due to genetics. Variation was observed for deep root traits (e.g. 111.4-178.5cm (60%) for depth; 0.09-0.22cm/°C day (144%) for descent rate) using soil coring in the field environments. There was significant variation for root traits between sites, and variation in the relative performance of genotypes between sites. However, genotypes were identified that performed consistently well or poorly at both sites. Furthermore, high-performing genotypes were statistically superior in root traits than low-performing genotypes or commercial varieties. There was a weak but significant negative correlation between green leaf score (-0.5), CTD (0.45), and rooting depth and a positive correlation for chlorophyll reflectance (0.32). Shoot phenotypes did not predict other root traits. This study suggests that field coring can directly identify variation in deep root traits to speed up selection of genotypes for breeding programmes.

Traits and selection strategies to improve root systems and water uptake in water-limited wheat crops.

Wheat yields globally will depend increasingly on good management to conserve rainfall and new varieties that use water efficiently for grain production. Here we propose an approach for developing new varieties to make better use of deep stored water. We focus on water-limited wheat production in the summer-dominant rainfall regions of India and Australia, but the approach is generally applicable to other environments and root-based constraints. Use of stored deep water is valuable because it is more predictable than variable in-season rainfall and can be measured prior to sowing. Further, this moisture is converted into grain with twice the efficiently of in-season rainfall since it is taken up later in crop growth during the grain-filling period when the roots reach deeper layers. We propose that wheat varieties with a deeper root system, a redistribution of branch root density from the surface to depth, and with greater radial hydraulic conductivity at depth would have higher yields in rainfed systems where crops rely on deep water for grain fill. Developing selection systems for mature root system traits is challenging as there are limited high-throughput phenotyping methods for roots in the field, and there is a risk that traits selected in the lab on young plants will not translate into mature root system traits in the field. We give an example of a breeding programme that combines laboratory and field phenotyping with proof of concept evaluation of the trait at the beginning of the selection programme. This would greatly enhance confidence in a high-throughput laboratory or field screen, and avoid investment in screens without yield value. This approach requires careful selection of field sites and years that allow expression of deep roots and increased yield. It also requires careful selection and crossing of germplasm to allow comparison of root expression among genotypes that are similar for other traits, especially flowering time and disease and toxicity resistances. Such a programme with field and laboratory evaluation at the outset will speed up delivery of varieties with improved root systems for higher yield.

Genes expressed in zoospores of Phytophthora nicotianae.

The genus Phytophthora includes many highly destructive plant pathogens. In many Phytophthora species, pathogen dispersal and initiation of plant infection are achieved by motile, biflagellate zoospores that are chemotactically attracted to suitable infection sites. In order to study gene expression in zoospores, we have constructed a cDNA library using mRNA from zoospores of Phytophthora nicotianae. The library was arrayed and screened using probes derived from mycelium or zoospore mRNA. More than 400 clones representing genes preferentially expressed in zoospores were identified and sequenced from the 5' end of the insert. The expressed sequence tags (ESTs) generated were found to represent 240 genes. The ESTs were compared to sequences in GenBank and in the Phytophthora Genome Consortium database, and classified according to putative function based on homology to known proteins. To further characterize the identified genes, a colony array was created on replicate nylon filters and screened with probes derived from four Phytophthora developmental stages including zoospores, germinating cysts, vegetative mycelium and sporulating hyphae, and from inoculated and uninoculated tobacco seedlings. Data from sequence analysis and colony array screening were compiled into a local database, and searched to identify genes that are preferentially expressed in zoospores for future functional analysis.