Agim Ballvora

Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis

Early water stress recognition is of great relevance in precision plant breeding and production. Hyperspectral imaging sensors can be a valuable tool for early stress detection with high spatio-temporal resolution. They gather large, high dimensional data cubes posing a significant challenge to data analysis. Classical supervised learning algorithms often fail in applied plant sciences due to their need of labelled datasets, which are difficult to obtain. Therefore, new approaches for unsupervised learning of relevant patterns are needed. We apply for the first time a recent matrix factorisation technique, simplex volume maximisation (SiVM), to hyperspectral data. It is an unsupervised classification approach, optimised for fast computation of massive datasets. It allows calculation of how similar each spectrum is to observed typical spectra. This provides the means to express how likely it is that one plant is suffering from stress. The method was tested for drought stress, applied to potted barley plants in a controlled rain-out shelter experiment and to agricultural corn plots subjected to a two factorial field setup altering water and nutrient availability. Both experiments were conducted on the canopy level. SiVM was significantly better than using a combination of established vegetation indices. In the corn plots, SiVM clearly separated the different treatments, even though the effects on leaf and canopy traits were subtle.

A genetic map of cassava (Manihot esculenta Crantz) with integrated physical mapping of immunity-related genes

BackgroundCassava, Manihot esculenta Crantz, is one of the most important crops world-wide representing the staple security for more than one billion of people. The development of dense genetic and physical maps, as the basis for implementing genetic and molecular approaches to accelerate the rate of genetic gains in breeding program represents a significant challenge. A reference genome sequence for cassava has been made recently available and community efforts are underway for improving its quality. Cassava is threatened by several pathogens, but the mechanisms of defense are far from being understood. Besides, there has been a lack of information about the number of genes related to immunity as well as their distribution and genomic organization in the cassava genome.ResultsA high dense genetic map of cassava containing 2,141 SNPs has been constructed. Eighteen linkage groups were resolved with an overall size of 2,571 cM and an average distance of 1.26 cM between markers. More than half of mapped SNPs (57.4%) are located in coding sequences. Physical mapping of scaffolds of cassava whole genome sequence draft using the mapped markers as anchors resulted in the orientation of 687 scaffolds covering 45.6% of the genome. One hundred eighty nine new scaffolds are anchored to the genetic cassava map leading to an extension of the present cassava physical map with 30.7 Mb. Comparative analysis using anchor markers showed strong co-linearity to previously reported cassava genetic and physical maps. In silico based searching for conserved domains allowed the annotation of a repertory of 1,061 cassava genes coding for immunity-related proteins (IRPs). Based on physical map of the corresponding sequencing scaffolds, unambiguous genetic localization was possible for 569 IRPs.ConclusionsThis is the first study reported so far of an integrated high density genetic map using SNPs with integrated genetic and physical localization of newly annotated immunity related genes in cassava. These data build a solid basis for future studies to map and associate markers with single loci or quantitative trait loci for agronomical important traits. The enrichment of the physical map with novel scaffolds is in line with the efforts of the cassava genome sequencing consortium.

Non-invasive assessment of leaf water status using a dual-mode microwave resonator

The water status in plant leaves is a good indicator for the water status in the whole plant revealing stress if the water supply is reduced. The analysis of dynamic aspects of water availability in plant tissues provides useful information for the understanding of the mechanistic basis of drought stress tolerance, which may lead to improved plant breeding and management practices. The determination of the water content in plant tissues during plant development has been a challenge and is currently feasible based on destructive analysis only. We present here the application of a non-invasive quantitative method to determine the volumetric water content of leaves and the ionic conductivity of the leaf juice from non-invasive microwave measurements at two different frequencies by one sensor device. A semi-open microwave cavity loaded with a ceramic dielectric resonator and a metallic lumped-element capacitor- and inductor structure was employed for non-invasive microwave measurements at 150 MHz and 2.4 Gigahertz on potato, maize, canola and wheat leaves. Three leaves detached from each plant were chosen, representing three developmental stages being representative for tissue of various age. Clear correlations between the leaf- induced resonance frequency shifts and changes of the inverse resonator quality factor at 2.4 GHz to the gravimetrically determined drying status of the leaves were found. Moreover, the ionic conductivity of Maize leaves, as determined from the ratio of the inverse quality factor and frequency shift at 150 MHz by use of cavity perturbation theory, was found to be in good agreement with direct measurements on plant juice. In conjunction with a compact battery- powered circuit board- microwave electronic module and a user-friendly software interface, this method enables rapid in-vivo water amount assessment of plants by a handheld device for potential use in the field.

Allelic variations and differential expressions detected at quantitative trait loci for salt stress tolerance in wheat: GWAS reveals gene loci for salt tolerance in wheat

The increasing salinization of agricultural lands is a threat to global wheat production. Understanding of the mechanistic basis of salt tolerance (ST) is essential for developing breeding and selection strategies that would allow for increased wheat production under saline conditions to meet the increasing global demand. We used a set that consists of 150 internationally derived winter and facultative wheat cultivars genotyped with a 90K SNP chip and phenotyped for ST across three growth stages and for ionic (leaf K+ and Na+  contents) traits to dissect the genetic architecture regulating ST in wheat. Genome-wide association mapping revealed 187 Single Nucleotide Polymorphism (SNPs) (R2  = 3.00-30.67%), representing 37 quantitative trait loci (QTL), significantly associated with the ST traits. Of these, four QTL on 1BS, 2AL, 2BS and 3AL were associated with ST across the three growth stages and with the ionic traits. Novel QTL were also detected on 1BS and 1DL. Candidate genes linked to these polymorphisms were uncovered, and expression analyses were performed and validated on them under saline and non-saline conditions using transcriptomics and qRT-PCR data. Expressed sequence comparisons in contrasting ST wheat genotypes identified several non-synonymous/missense mutation sites that are contributory to the ST trait variations, indicating the biological relevance of these polymorphisms that can be exploited in breeding for ST in wheat.

“Deep Phenotyping” of Early Plant Response to Abiotic Stress Using Non-invasive Approaches in Barley

The basic mechanisms of yield maintenance under drought conditions are far from being understood. Pre-symptomatic water stress recognition would help to get insides into complex plant mechanistic basis of plant response when confronted to water shortage conditions and is of great relevance in precision plant breeding and production. The plant reactions to drought stress result in spatial, temporal and tissue-specific pattern changes which can be detected using non-invasive sensor techniques, such as hyperspectral imaging. The “response turning time-point” in the temporal curve of plant response to stress rather than the maxima is the most relevant time-point for guided sampling to get insights into mechanistic basis of plant response to drought stress. Comparative hyperspectral image analysis was performed on barley (Hordeum vulgare) plants grown under well-watered and water stress conditions in two consecutive years. The obtained massive, high-dimensional data cubes were analysed with a recent matrix factorization technique based on simplex volume maximization of hyperspectral data and compared to several drought-related traits. The results show that it was possible to detect and visualize the accelerated senescence signature in stressed plants earlier than symptoms become visible by the naked eye.

Allelic variations and differential expressions detected at quantitative trait loci for salt stress tolerance in wheat

The increasing salinization of agricultural lands is a threat to global wheat production. Understanding of the mechanistic basis of salt tolerance (ST) is essential for developing breeding and selection strategies that would allow for increased wheat production under saline conditions to meet the increasing global demand. We used a set that consists of 150 internationally derived winter and facultative wheat cultivars genotyped with a 90K SNP chip and phenotyped for ST across three growth stages and for ionic (leaf K+ and Na+  contents) traits to dissect the genetic architecture regulating ST in wheat. Genome-wide association mapping revealed 187 Single Nucleotide Polymorphism (SNPs) (R2  = 3.00-30.67%), representing 37 quantitative trait loci (QTL), significantly associated with the ST traits. Of these, four QTL on 1BS, 2AL, 2BS and 3AL were associated with ST across the three growth stages and with the ionic traits. Novel QTL were also detected on 1BS and 1DL. Candidate genes linked to these polymorphisms were uncovered, and expression analyses were performed and validated on them under saline and non-saline conditions using transcriptomics and qRT-PCR data. Expressed sequence comparisons in contrasting ST wheat genotypes identified several non-synonymous/missense mutation sites that are contributory to the ST trait variations, indicating the biological relevance of these polymorphisms that can be exploited in breeding for ST in wheat.

Major Novel QTL for Resistance to Cassava Bacterial Blight Identified through a Multi-Environmental Analysis

Cassava, Manihot esculenta Crantz, has been positioned as one of the most promising crops world-wide representing the staple security for more than one billion people mainly in poor countries. Cassava production is constantly threatened by several diseases, including cassava bacterial blight (CBB) caused by Xanthomonas axonopodis pv. manihotis (Xam), it is the most destructive disease causing heavy yield losses. Here, we report the detection and localization on the genetic map of cassava QTL (Quantitative Trait Loci) conferring resistance to CBB. An F1 mapping population of 117 full sibs was tested for resistance to two Xam strains (Xam318 and Xam681) at two locations in Colombia: La Vega, Cundinamarca and Arauca. The evaluation was conducted in rainy and dry seasons and additional tests were carried out under controlled greenhouse conditions. The phenotypic evaluation of the response to Xam revealed continuous variation. Based on composite interval mapping analysis, 5 strain-specific QTL for resistance to Xam explaining between 15.8 and 22.1% of phenotypic variance, were detected and localized on a high resolution SNP-based genetic map of cassava. Four of them show stability among the two evaluated seasons. Genotype by environment analysis detected three QTL by environment interactions and the broad sense heritability for Xam318 and Xam681 were 20 and 53%, respectively. DNA sequence analysis of the QTL intervals revealed 29 candidate defense-related genes (CDRGs), and two of them contain domains related to plant immunity proteins, such as NB-ARC-LRR and WRKY.

Allelic variations and differential expressions detected at QTL loci for salt stress tolerance in wheat

The increasing salinization of agricultural lands is a threat to global wheat production. Understanding of the mechanistic basis of salt tolerance (ST) is essential for developing breeding and selection strategies that would allow for increased wheat production under saline conditions to meet the increasing global demand. We used a set that consists of 150 internationally derived winter and facultative wheat cultivars genotyped with a 90K SNP chip and phenotyped for ST across three growth stages and for ionic (leaf K+ and Na+  contents) traits to dissect the genetic architecture regulating ST in wheat. Genome-wide association mapping revealed 187 Single Nucleotide Polymorphism (SNPs) (R2  = 3.00-30.67%), representing 37 quantitative trait loci (QTL), significantly associated with the ST traits. Of these, four QTL on 1BS, 2AL, 2BS and 3AL were associated with ST across the three growth stages and with the ionic traits. Novel QTL were also detected on 1BS and 1DL. Candidate genes linked to these polymorphisms were uncovered, and expression analyses were performed and validated on them under saline and non-saline conditions using transcriptomics and qRT-PCR data. Expressed sequence comparisons in contrasting ST wheat genotypes identified several non-synonymous/missense mutation sites that are contributory to the ST trait variations, indicating the biological relevance of these polymorphisms that can be exploited in breeding for ST in wheat.