Multi-omics atlas of combinatorial abiotic stress responses in wheat.

Field-grown crops rarely experience growth conditions in which yield can be maximized. Environmental stresses occur in combination, with advancements in crop tolerance further complicated by its polygenic nature. Strategic targeting of causal genes is required to meet future crop production needs. Here, we employed a systems biology approach in wheat (Triticum aestivum L.) to investigate physio-metabolic adjustments and transcriptome reprogramming involved in acclimations to heat, drought, salinity and all combinations therein. A significant shift in magnitude and complexity of plant response was evident across stress scenarios based on the agronomic losses, increased proline concentrations and 8.7-fold increase in unique differentially expressed transcripts (DETs) observed under the triple stress condition. Transcriptome data from all stress treatments were assembled into an online, open access eFP browser for visualizing gene expression during abiotic stress. Weighted gene co-expression network analysis revealed 152 hub genes of which 32% contained the ethylene-responsive element binding factor-associated amphiphilic repression (EAR) transcriptional repression motif. Cross-referencing against the 31 DETs common to all stress treatments isolated TaWRKY33 as a leading candidate for greater plant tolerance to combinatorial stresses. Integration of our findings with available literature on gene functional characterization allowed us to further suggest flexible gene combinations for future adaptive gene stacking in wheat. Our approach demonstrates the strength of robust multi-omics-based data resources for gene discovery in complex environmental conditions. Accessibility of such datasets will promote cross-validation of candidate genes across studies and aid in accelerating causal gene validation for crop resiliency.

Correction to: MeioCapture: an efficient method for staging and isolation of meiocytes in the prophase I sub-stages of meiosis in wheat.

Following publication of the original article [1], a reader spotted an incorrect citation of the reference 14 [2] in the 'Background'. The male meiocyte isolation work described in this article [2] was carried out in rice and not in Brassica as originally stated in the 'Background' [1]. Thus, the following amendment to the Background section should be noted.

MeioCapture: an efficient method for staging and isolation of meiocytes in the prophase I sub-stages of meiosis in wheat.

BACKGROUND: Molecular analysis of meiosis has been hindered by difficulties in isolating high purity subpopulations of sporogenous cells representing the succeeding stages of meiosis. Isolation of purified male meiocytes from defined meiotic stages is crucial in discovering meiosis specific genes and associated regulatory networks. RESULTS: We describe an optimized method termed MeioCapture for simultaneous isolation of uncontaminated male meiocytes from wheat (Triticum spp.), specifically from the pre-meiotic G2 and the five sub-stages of meiotic prophase I. The MeioCapture protocol builds on the traditional anther squash technique and the capillary collection method, and involves extrusion of intact sporogenous archesporial columns (SACs) containing meiocytes. This improved method exploits the natural meiotic synchrony between anthers of the same floret, the correlation between the length of anthers and meiotic stage, and the occurrence of meiocytes in intact SACs largely free of somatic cells. The main advantage of MeioCapture, compared to previous methods, is that it allows simultaneous collection of meiocytes from different sub-stages of prophase I at a very high level of purity, through correlation of stages with anther sizes. A detailed description is provided for all steps, including the collection of tissue, isolation and size sorting of anthers, extrusion of intact SACs, and staging of meiocytes. Precautions for individual steps throughout the procedure are also provided to facilitate efficient isolation of pure meiocytes. The proof-of-concept was successfully established in wheat, and a light microscopic atlas of meiosis, encompassing all stages from pre-meiosis to telophase II, was developed. CONCLUSION: The MeioCapture method provides an essential technique to study the molecular basis of chromosome pairing and exchange of genetic information in wheat, leading to strategies for manipulating meiotic recombination frequencies. The method also provides a foundation for similar studies in other crop species.

Targeted mutagenesis in wheat microspores using CRISPR/Cas9.

CRISPR/Cas9 genome editing is a transformative technology that will facilitate the development of crops to meet future demands. However, application of gene editing is hindered by the long life cycle of many crop species and because desired genotypes generally require multiple generations to achieve. Single-celled microspores are haploid cells that can develop into double haploid plants and have been widely used as a breeding tool to generate homozygous plants within a generation. In this study, we combined the CRISPR/Cas9 system with microspore technology and developed an optimized haploid mutagenesis system to induce genetic modifications in the wheat genome. We investigated a number of factors that may affect the delivery of CRISPR/Cas9 reagents into microspores and found that electroporation of a minimum of 75,000 cells using 10-20 µg DNA and a pulsing voltage of 500 V is optimal for microspore transfection using the Neon transfection system. Using multiple Cas9 and sgRNA constructs, we present evidence for the seamless introduction of targeted modifications in an exogenous DsRed gene and two endogenous wheat genes, including TaLox2 and TaUbiL1. This study demonstrates the value and feasibility of combining microspore technology and CRISPR/Cas9-based gene editing for trait discovery and improvement in plants.

The developmental transcriptome atlas of the biofuel crop Camelina sativa.

Camelina sativa is currently being embraced as a viable industrial bio-platform crop due to a number of desirable agronomic attributes and the unique fatty acid profile of the seed oil that has applications for food, feed and biofuel. The recent completion of the reference genome sequence of C. sativa identified a young hexaploid genome. To complement this work, we have generated a genome-wide developmental transcriptome map by RNA sequencing of 12 different tissues covering major developmental stages during the life cycle of C. sativa. We have generated a digital atlas of this comprehensive transcriptome resource that enables interactive visualization of expression data through a searchable database of electronic fluorescent pictographs (eFP browser). An analysis of this dataset supported expression of 88% of the annotated genes in C. sativa and provided a global overview of the complex architecture of temporal and spatial gene expression patterns active during development. Conventional differential gene expression analysis combined with weighted gene expression network analysis uncovered similarities as well as differences in gene expression patterns between different tissues and identified tissue-specific genes and network modules. A high-quality census of transcription factors, analysis of alternative splicing and tissue-specific genome dominance provided insight into the transcriptional dynamics and sub-genome interplay among the well-preserved triplicated repertoire of homeologous loci. The comprehensive transcriptome atlas in combination with the reference genome sequence provides a powerful resource for genomics research which can be leveraged to identify functional associations between genes and understand the regulatory networks underlying developmental processes.

Analysis of Genotyping-by-Sequencing (GBS) Data.

The development of genotyping-by-sequencing (GBS) to rapidly detect nucleotide variation at the whole genome level, in many individuals simultaneously, has provided a transformative genetic profiling technique. GBS can be carried out in species with or without reference genome sequences yields huge amounts of potentially informative data. One limitation with the approach is the paucity of tools to transform the raw data into a format that can be easily interrogated at the genetic level. In this chapter we describe bioinformatics tools developed to address this shortfall together with experimental design considerations to fully leverage the power of GBS for genetic analysis.

Single-nucleotide polymorphism identification and genotyping in Camelina sativa.

Camelina sativa, a largely relict crop, has recently returned to interest due to its potential as an industrial oilseed. Molecular markers are key tools that will allow C. sativa to benefit from modern breeding approaches. Two complementary methodologies, capture of 3' cDNA tags and genomic reduced-representation libraries, both of which exploited second generation sequencing platforms, were used to develop a low density (768) Illumina GoldenGate single nucleotide polymorphism (SNP) array. The array allowed 533 SNP loci to be genetically mapped in a recombinant inbred population of C. sativa. Alignment of the SNP loci to the C. sativa genome identified the underlying sequenced regions that would delimit potential candidate genes in any mapping project. In addition, the SNP array was used to assess genetic variation among a collection of 175 accessions of C. sativa, identifying two sub-populations, yet low overall gene diversity. The SNP loci will provide useful tools for future crop improvement of C. sativa.

The emerging biofuel crop Camelina sativa retains a highly undifferentiated hexaploid genome structure.

Camelina sativa is an oilseed with desirable agronomic and oil-quality attributes for a viable industrial oil platform crop. Here we generate the first chromosome-scale high-quality reference genome sequence for C. sativa and annotated 89,418 protein-coding genes, representing a whole-genome triplication event relative to the crucifer model Arabidopsis thaliana. C. sativa represents the first crop species to be sequenced from lineage I of the Brassicaceae. The well-preserved hexaploid genome structure of C. sativa surprisingly mirrors those of economically important amphidiploid Brassica crop species from lineage II as well as wheat and cotton. The three genomes of C. sativa show no evidence of fractionation bias and limited expression-level bias, both characteristics commonly associated with polyploid evolution. The highly undifferentiated polyploid genome of C. sativa presents significant consequences for breeding and genetic manipulation of this industrial oil crop.

Identification of metabolites related to mechanisms of resistance in barley against Fusarium graminearum, based on mass spectrometry.

Fusarium head blight (FHB) is an economically important disease of the family Triticeae, as, apart from yield reduction it also causes quality deterioration by producing mycotoxins. Host resistance is the most promising way to control the disease. Metabolic profiling was applied to identify resistance related (RR) metabolites against Fusarium graminearum in five FHB-resistant genotypes ('Chevron', 'H5277-44', 'H5277-164', 'M92-513' and 'M122') relative to one FHB-susceptible genotype ('Stander'). The disease severity was assessed in greenhouse to group the genotypes based on FHB-resistance. The disease was quantified as the proportion of diseased spikelets (PSD) and the area under the disease progress curve (AUDPC). Spikelets were collected at 72 h post inoculation. Metabolites were extracted into an aqueous solution of methanol and analyzed using a LC-hybrid-MS system. Metabolite abundances were subjected to a resistant versus susceptible pair-wise analysis, using a t test. Resistance related (RR) metabolites, both constitutive (RRC) and induced (RRI), were identified amongst metabolites whose levels were significantly higher in resistant genotype than in susceptible. Among 1,430 RR metabolites, 115 were putatively identified. These RR metabolites belonged to different chemical groups: fatty acids: linolenic acid; phenylpropanoids: p-coumaric, sinapic acid; flavonoids: naringenin, kaempferol glucoside, catechol glucoside. In addition, resistance indicator metabolites, such as deoxynivalenol (DON) and DON-3-O-glucoside (D3G) were also detected. The amount of total DON synthesized converted to D3G (PDC) was the greatest in resistant genotype 'Chevron' (PDC = 0.76). The role of the resistance-related and resistance-indicator metabolites on plant defense, and their use as potential biomarkers to screen barley genotypes for FHB resistance is discussed.

Mass spectrometry-based metabolomics application to identify quantitative resistance-related metabolites in barley against Fusarium head blight.

Quantitative resistance is generally controlled by several genes. More than 100 resistance quantitative trait loci (QTLs) have been identified in wheat and barley against Fusarium head blight (FHB), caused by Gibberella zeae (anamorph: Fusarium graminearum), implying the possible occurrence of several resistance mechanisms. The objective of this study was to apply metabolomics to identify the metabolites in barley that are related to resistance against FHB. Barley genotypes, Chevron and Stander, were inoculated with mock or pathogen during the anthesis stage. The disease severity was assessed as the proportion of spikelets diseased. The genotype Chevron (0.33) was found to have a higher level of quantitative resistance than Stander (0.88). Spikelet samples were harvested at 48 h post-inoculation; metabolites were extracted and analysed using an LC-ESI-LTQ-Orbitrap (Thermo Fisher, Waltham, MA, USA). The output was imported to an XCMS 1.12.1 platform, the peaks were deconvoluted and the adducts were sieved. Of the 1826 peaks retained, a t-test identified 496 metabolites with significant treatment effects. Among these, 194 were resistance-related (RR) constitutive metabolites, whose abundance was higher in resistant mock-inoculated than in susceptible mock-inoculated genotypes. Fifty metabolites were assigned putative names on the basis of accurate mass, fragmentation pattern and number of carbons in the formula. The RR metabolites mainly belonged to phenylpropanoid, flavonoid, fatty acid and terpenoid metabolic pathways. Selected RR metabolites were assayed in vitro for antifungal activity on the basis of fungal biomass production. The application of these RR metabolites as potential biomarkers for screening and the potential of mass spectrometry-based metabolomics for the identification of gene functions are discussed.