Improved genomic prediction using machine learning with Variational Bayesian sparsity.

BACKGROUND: Genomic prediction has become a powerful modelling tool for assessing line performance in plant and livestock breeding programmes. Among the genomic prediction modelling approaches, linear based models have proven to provide accurate predictions even when the number of genetic markers exceeds the number of data samples. However, breeding programmes are now compiling data from large numbers of lines and test environments for analyses, rendering these approaches computationally prohibitive. Machine learning (ML) now offers a solution to this problem through the construction of fully connected deep learning architectures and high parallelisation of the predictive task. However, the fully connected nature of these architectures immediately generates an over-parameterisation of the network that needs addressing for efficient and accurate predictions. RESULTS: In this research we explore the use of an ML architecture governed by variational Bayesian sparsity in its initial layers that we have called VBS-ML. The use of VBS-ML provides a mechanism for feature selection of important markers linked to the trait, immediately reducing the network over-parameterisation. Selected markers then propagate to the remaining fully connected feed-forward components of the ML network to form the final genomic prediction. We illustrated the approach with four large Australian wheat breeding data sets that range from 2665 lines to 10375 lines genotyped across a large set of markers. For all data sets, the use of the VBS-ML architecture improved genomic prediction accuracy over legacy linear based modelling approaches. CONCLUSIONS: An ML architecture governed under a variational Bayesian paradigm was shown to improve genomic prediction accuracy over legacy modelling approaches. This VBS-ML approach can be used to dramatically decrease the parameter burden on the network and provide a computationally feasible approach for improving genomic prediction conducted with large breeding population numbers and genetic markers.

Applicability of a "Multi-Stage Pulse Labeling" 15N Approach to Phenotype N Dynamics in Maize Plant Components during the Growing Season.

Highlights This work utilizes "multi-stage pulse labeling" 15N applications, primarily during reproductive growth stages, as a phenotyping strategy to identify maize hybrids with superior N use efficiency (NUE) under low N conditions. Research using labeled isotopic N (15N) can precisely quantify fertilizer nitrogen (N) uptake and organ-specific N allocation in field crops such as maize (Zea mays L.). The overall research objective was to study plant N uptake patterns potentially correlated with N use efficiency (NUE) in field-grown maize hybrids using a "multi-stage pulse labeling" 15N phenotyping strategy with an emphasis on the reproductive period. Five hybrids varying in NUE were compared under zero N fertilizer application (0N) plus a moderate rate of 112 kg N ha-1 (112N) in 2013 (2 locations) and 2014 growing seasons. The equivalent of 3.2 (2013) to 2.1 (2014) kg of 15N ha-1, as labeled Ca(15NO3)2, was injected into soil on both sides of consecutive plants at multiple stages between V14 and R5. Aboveground plant biomass was primarily collected in short-term intervals (4-6 days after each 15N application) in both years, and following a single long-term interval (at R6 after 15N injection at R1) in 2014. Averaged across hybrids and site-years, the moderate N rate (112N) increased absolute 15N uptake at all stages; however, plants in the 0N treatment allocated proportionally more 15N to reproductive organs. Before flowering, short-term recovery of 15N (15Nrec) totaled ~0.30 or 0.40 kg kg-1 of the 15N applied, and ~50% of that accumulated 15Nu was found in leaves and 40% in stems. After flowering, plant 15Nrec totaled ~0.30 kg kg-1 of 15N applied, and an average 30% of accumulated 15Nu was present in leaves, 17% in stems, and the remainder-usually the majority-in ears. At the R5 stage, despite a declining overall rate of 15N uptake per GDD thermal unit, plant 15Nrec represented ~0.25 kg kg-1 of 15N applied, of which ~65% was allocated to kernels. Overall long-term 15Nrec during grain filling was ~0.45 and 0.70 kg kg-1 of total 15N applied at R1 with 0 and 112N, respectively, and most (~77%) 15N uptake was found in kernels. The "multi-stage pulse labeling" technique proved to be a robust phenotyping strategy to differentiate reproductive-stage N uptake/allocation patterns to plant organs and maize efficiencies with newly available fertilizer N.

Understanding Molecular Mechanisms of Durable and Non-durable Resistance to Stripe Rust in Wheat Using a Transcriptomics Approach.

Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici, continues to cause severe damage worldwide. Durable resistance is necessary for sustainable control of the disease. High-temperature adult-plant (HTAP) resistance, which expresses when the weather becomes warm and plants grow older, has been demonstrated to be durable. We conducted numerous studies to understand the molecular mechanisms of different types of stripe rust resistance using a transcriptomics approach. Through comparing gene expression patterns with race-specific, all-stage resistance controlled by various genes, we found that a greater diversity of genes is involved in HTAP resistance than in all-stage resistance. The genes involved in HTAP resistance are induced more slowly and their expression induction is less dramatic than genes involved in all-stage resistance. The high diversity of genes and less dramatic induction may explain durability and the incomplete expression level of HTAP resistance. Identification of transcripts may be helpful in identifying resistance controlled by different genes and in selecting better combinations of genes to combine for achieving adequate and durable resistance.

Development and characterization of 37 novel EST-SSR markers in Pisum sativum (Fabaceae).

PREMISE OF THE STUDY: Simple sequence repeat markers were developed based on expressed sequence tags (EST-SSR) and screened for polymorphism among 23 Pisum sativum individuals to assist development and refinement of pea linkage maps. In particular, the SSR markers were developed to assist in mapping of white mold disease resistance quantitative trait loci. • METHODS AND RESULTS: Primer pairs were designed for 46 SSRs identified in EST contiguous sequences assembled from a 454 pyrosequenced transcriptome of the pea cultivar, 'LIFTER'. Thirty-seven SSR markers amplified PCR products, of which 11 (30%) SSR markers produced polymorphism in 23 individuals, including parents of recombinant inbred lines, with two to four alleles. The observed and expected heterozygosities ranged from 0 to 0.43 and from 0.31 to 0.83, respectively. • CONCLUSIONS: These EST-SSR markers for pea will be useful for refinement of pea linkage maps, and will likely be useful for comparative mapping of pea and as tools for marker-based pea breeding.

Rapid transcriptome characterization and parsing of sequences in a non-model host-pathogen interaction; pea-Sclerotinia sclerotiorum.

BACKGROUND: White mold, caused by Sclerotinia sclerotiorum, is one of the most important diseases of pea (Pisum sativum L.), however, little is known about the genetics and biochemistry of this interaction. Identification of genes underlying resistance in the host or pathogenicity and virulence factors in the pathogen will increase our knowledge of the pea-S. sclerotiorum interaction and facilitate the introgression of new resistance genes into commercial pea varieties. Although the S. sclerotiorum genome sequence is available, no pea genome is available, due in part to its large genome size (~3500 Mb) and extensive repeated motifs. Here we present an EST data set specific to the interaction between S. sclerotiorum and pea, and a method to distinguish pathogen and host sequences without a species-specific reference genome. RESULTS: 10,158 contigs were obtained by de novo assembly of 128,720 high-quality reads generated by 454 pyrosequencing of the pea-S. sclerotiorum interactome. A method based on the tBLASTx program was modified to distinguish pea and S. sclerotiorum ESTs. To test this strategy, a mixture of known ESTs (18,490 pea and 17,198 S. sclerotiorum ESTs) from public databases were pooled and parsed; the tBLASTx method successfully separated 90.1% of the artificial EST mix with 99.9% accuracy. The tBLASTx method successfully parsed 89.4% of the 454-derived EST contigs, as validated by PCR, into pea (6,299 contigs) and S. sclerotiorum (2,780 contigs) categories. Two thousand eight hundred and forty pea ESTs and 996 S. sclerotiorum ESTs were predicted to be expressed specifically during the pea-S. sclerotiorum interaction as determined by homology search against 81,449 pea ESTs (from flowers, leaves, cotyledons, epi- and hypocotyl, and etiolated and light treated etiolated seedlings) and 57,751 S. sclerotiorum ESTs (from mycelia at neutral pH, developing apothecia and developing sclerotia). Among those ESTs specifically expressed, 277 (9.8%) pea ESTs were predicted to be involved in plant defense and response to biotic or abiotic stress, and 93 (9.3%) S. sclerotiorum ESTs were predicted to be involved in pathogenicity/virulence. Additionally, 142 S. sclerotiorum ESTs were identified as secretory/signal peptides of which only 21 were previously reported. CONCLUSIONS: We present and characterize an EST resource specific to the pea-S. sclerotiorum interaction. Additionally, the tBLASTx method used to parse S. sclerotiorum and pea ESTs was demonstrated to be a reliable and accurate method to distinguish ESTs without a reference genome.

An improved algorithm for the detection of genomic variation using short oligonucleotide expression microarrays.

High-throughput microarray experiments often generate far more biological information than is required to test the experimental hypotheses. Many microarray analyses are considered finished after differential expression and additional analyses are typically not performed, leaving untapped biological information left undiscovered. This is especially true if the microarray experiment is from an ecological study of multiple populations. Comparisons across populations may also contain important genomic polymorphisms, and a subset of these polymorphisms may be identified with microarrays using techniques for the detection of single feature polymorphisms (SFP). SFPs are differences in microarray probe level intensities caused by genetic polymorphisms such as single-nucleotide polymorphisms and small insertions/deletions and not expression differences. In this study, we provide a new algorithm for the detection of SFPs, evaluate the algorithm using existing data from two publicly available Affymetrix Barley (Hordeum vulgare) microarray data sets and compare them to two previously published SFP detection algorithms. Results show that our algorithm provides more consistent and sensitive calling of SFPs with a lower false discovery rate. Simultaneous analysis of SFPs and differential expression is a low-cost method for the enhanced analysis of microarray data, enabling additional biological inferences to be made.

Gene expression profiling of Puccinia striiformis f. sp. tritici during development reveals a highly dynamic transcriptome.

Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. cDNA libraries had been constructed from urediniospores, germinated urediniospores and haustoria. However, little is known about the expression patterns of the genes related to the infection process and sporulation of the pathogen. In this study, a custom oligonucleotide microarray was constructed using sequences of 442 gene transcripts selected from Pst cDNA libraries. The expression patterns of the genes were determined by hybridizing the microarray with cDNA from Pst in vitro and Pst-infected wheat leaves. The time course study identified 55 transcripts that were differentially expressed during the infection process in a compatible interaction. They were identified to have functions related to the following biological processes, including carbohydrate and lipid metabolism, energy, cell signaling, protein synthesis, cell structure and division. In an incompatible interaction, 17 transcripts of the pathogen were differentially expressed in resistant wheat leaves inoculated with an avirulent Pst race, ten of which had similar expression patterns to those in the compatible interaction. Several candidates for pathogenicity and virulence/avirulence related genes were also identified. The results of quantitative real-time PCR validated the expression patterns of some selected genes. The study demonstrates that the custom oligonucleotide microarray technology is useful to determine the expression patterns of the pathogen genes involved in different types of the host-pathogen interactions and stages of development.

Meta-analysis of transcripts associated with race-specific resistance to stripe rust in wheat demonstrates common induction of blue copper-binding protein, heat-stress transcription factor, pathogen-induced WIR1A protein, and ent-kaurene synthase transcripts.

Resistance to stripe rust in wheat is a preferred method of disease prevention. Race-specific all-stage resistance usually provides complete protection; thus an understanding of the molecular control of race-specific resistance is important. To build on previous studies of race-specific resistance controlled by the Yr5 gene, this study reports the construction and use of a custom oligonucleotide microarray to perform a meta-analysis of the transcriptional response involved in race-specific resistance conferred by Yr1, Yr5, Yr7, Yr8, Yr9, Yr10, Yr15, and Yr17. By profiling the response of eight resistance genes in a common background, we identified 28 transcripts significantly involved in the resistance phenotype across all genotypes. The most significant of these were annotated as blue copper-binding protein, heat-stress transcription factor, pathogen-induced WIR1A protein, and ent-kaurene synthase transcripts. Unique transcripts significant in each genotype were also identified, which highlighted some transcriptional events specific to certain genotypes. The approach was effective in narrowing down the list of candidate genes in comparison to studying individual genotypes. Annotation revealed key gene expression events involved in race-specific resistance. The results confirm the activity of known R-gene-mediated pathway race-specific resistance, including an oxidative burst that likely contributes to a hypersensitive response, as well as pathogenesis-related protein expression and activity of the phenylpropanoid pathway. However, several identified transcripts remained unknown and may prove interesting candidates for further characterization.

Large-scale analysis of antisense transcription in wheat using the Affymetrix GeneChip Wheat Genome Array.

BACKGROUND: Natural antisense transcripts (NATs) are transcripts of the opposite DNA strand to the sense-strand either at the same locus (cis-encoded) or a different locus (trans-encoded). They can affect gene expression at multiple stages including transcription, RNA processing and transport, and translation. NATs give rise to sense-antisense transcript pairs and the number of these identified has escalated greatly with the availability of DNA sequencing resources and public databases. Traditionally, NATs were identified by the alignment of full-length cDNAs or expressed sequence tags to genome sequences, but an alternative method for large-scale detection of sense-antisense transcript pairs involves the use of microarrays. In this study we developed a novel protocol to assay sense- and antisense-strand transcription on the 55 K Affymetrix GeneChip Wheat Genome Array, which is a 3' in vitro transcription (3'IVT) expression array. We selected five different tissue types for assay to enable maximum discovery, and used the 'Chinese Spring' wheat genotype because most of the wheat GeneChip probe sequences were based on its genomic sequence. This study is the first report of using a 3'IVT expression array to discover the expression of natural sense-antisense transcript pairs, and may be considered as proof-of-concept. RESULTS: By using alternative target preparation schemes, both the sense- and antisense-strand derived transcripts were labeled and hybridized to the Wheat GeneChip. Quality assurance verified that successful hybridization did occur in the antisense-strand assay. A stringent threshold for positive hybridization was applied, which resulted in the identification of 110 sense-antisense transcript pairs, as well as 80 potentially antisense-specific transcripts. Strand-specific RT-PCR validated the microarray observations, and showed that antisense transcription is likely to be tissue specific. For the annotated sense-antisense transcript pairs, analysis of the gene ontology terms showed a significant over-representation of transcripts involved in energy production. These included several representations of ATP synthase, photosystem proteins and RUBISCO, which indicated that photosynthesis is likely to be regulated by antisense transcripts. CONCLUSION: This study demonstrated the novel use of an adapted labeling protocol and a 3'IVT GeneChip array for large-scale identification of antisense transcription in wheat. The results show that antisense transcription is relatively abundant in wheat, and may affect the expression of valuable agronomic phenotypes. Future work should select potentially interesting transcript pairs for further functional characterization to determine biological activity.

Effectiveness of an innovative prototype subtracted diversity array (SDA) for fingerprinting plant species of medicinal importance.

The accurate identification of medicinal plants is becoming increasingly important due to reported concerns about purity, quality and safety. The previously developed prototype subtracted diversity array (SDA) had been validated for the ability to distinguish clade-level targets in a phylogenetically accurate manner. This study represents the rigorous investigation of the SDA for genotyping capabilities, including the genotyping of plant species not included during the construction of the SDA, as well as to lower classification levels including family and species. The results show that the SDA, in its current form, has the ability to accurately genotype species not included during SDA development to clade level. Additionally, for those species that were included during SDA development, genotyping is successful to the family level, and to the species level with minor exceptions. Twenty polymorphic SDA features were sequenced in a first attempt to characterize the polymorphic DNA between species, which showed that transposon-like sequences may be valuable as polymorphic features to differentiate angiosperm families and species. Future refinements of the SDA to allow more sensitive genotyping are discussed with the overall goal of accurate medicinal plant identification in mind.

Transcriptome analysis of the wheat-Puccinia striiformis f. sp. tritici interaction.

Stripe rust [caused by Puccinia striiformis Westend. f. sp. tritici Eriks. (Pst)] is a destructive disease of wheat (Triticum aestivum L.) worldwide. Genetic resistance is the preferred method for control and the Yr5 gene, originally identified in Triticum spelta var. album, represents a major resistance (R) gene that confers all-stage resistance to all currently known races of Pst in the United States. To identify transcripts associated with the Yr5-mediated incompatible interaction and the yr5-compatible interaction, the Wheat GeneChip was used to profile the changes occurring in wheat isolines that differed for the presence of the Yr5 gene after inoculation with Pst. This time-course study (6, 12, 24 and 48 h post-inoculation) identified 115 transcripts that were induced during the R-gene-mediated incompatible interaction, and 73 induced during the compatible interaction. Fifty-four transcripts were induced in both interactions and were considered as basal defence transcripts, whilst 61 transcripts were specific to the incompatible interaction [hypersensitive response (HR)-specific transcripts] and 19 were specific to the compatible interaction (biotrophic interaction-specific transcripts). The temporal pattern of transcript accumulation showed a peak at 24 h after infection that may reflect haustorial penetration by Pst at ~16 h. An additional 12 constitutive transcript differences were attributed to the presence of Yr5 after eliminating those considered as incomplete isogenicity. Annotation of the induced transcripts revealed that the presence of Yr5 resulted in a rapid and amplified resistance response involving signalling pathways and defence-related transcripts known to occur during R-gene-mediated responses, including protein kinase signalling and the production of reactive oxygen species leading to a hypersensitive response. Basal defence also involved substantial induction of many defence-related transcripts but the lack of R-gene signalling resulted in weaker response.

Transcriptome analysis of high-temperature adult-plant resistance conditioned by Yr39 during the wheat-Puccinia striiformis f. sp. tritici interaction.

Stripe rust [caused by Puccinia striiformis Westend. f. sp. tritici Eriks. (Pst)] is a destructive disease of wheat (Triticum aestivum L.) worldwide. High-temperature adult-plant (HTAP) resistance to stripe rust is race non-specific, inherited quantitatively and durable. Previously, we identified and mapped the single Yr39 HTAP stripe rust resistance gene in the spring wheat cultivar Alpowa, which was identified on chromosome 7BL and accounted for 64.2% of the variation in resistance. To identify transcripts associated with Yr39-mediated resistance, we selected two F(7 )recombinant inbred lines (RILs) from an 'Avocet S/Alpowa' cross that differed at the Yr39 locus to represent an incompatible (Yr39) and compatible (yr39) interaction with Pst. Using the Affymetrix Wheat GeneChip, we profiled the transcript changes occurring in flag leaves of these two RILs over a time-course after treatment with Pst urediniospores and mock-inoculation. This time-course study identified 99 induced transcripts that were classified as HTAP resistance-specific. The temporal pattern of transcript accumulation showed a peak at 48 h after infection, which was supported by microscopic observation of fungal development and quantitative PCR assays that showed a rapid increase in fungal biomass after this time in the compatible interaction. More than half (50.5%) of the annotated transcripts specifically induced during HTAP resistance were involved in defence and/or signal transduction, including R gene homologues and transcripts associated with pathogenesis-related protein production, phenylpropanoid biosynthesis and protein kinase signalling. This study represents the first transcript profiling of HTAP resistance to stripe rust in wheat, and we compare our results with other transcript studies of race-specific and race non-specific resistance.

Surveying expression level polymorphism and single-feature polymorphism in near-isogenic wheat lines differing for the Yr5 stripe rust resistance locus.

DNA polymorphisms are valuable for several applications including genotyping, molecular mapping and marker-assisted selection. The 55 K Affymetrix Wheat GeneChip was used to survey expression level polymorphisms (ELPs) and single-feature polymorphisms (SFPs) between two near-isogenic wheat genotypes (BC(7):F(4)) that differ for the Yr5 stripe rust resistance locus, with the objective of developing genetic markers linked to Yr5. Ninety-one probe sets showing ELPs and 118 SFP-containing probe sets were identified between isolines, of which just nine ELP probe sets also contained SFPs. The proportion of the transcriptome estimated to be variable between isolines from this analysis was 0.30% for the ELPs and 0.39% for the SFPs, which was highly similar to the theoretical genome difference between isolines of ~0.39%. Using wheat-rice synteny, both ELPs and SFPs mainly clustered on long arms of rice chromosomes four and seven, which are syntenous to wheat chromosomes 2L (Yr5 locus) and 2S, respectively. The strong physical correlation between the two types of polymorphism indicated that the ELPs may be regulated by cis-acting DNA polymorphisms. Twenty SFPs homologous to rice 4L were used to develop additional genetic markers for Yr5. Physical mapping of the probe sets containing SFPs to wheat chromosomes identified nine on the target chromosome 2BL, thus wheat-rice synteny greatly enhanced the selection of SFPs that were located on the desired wheat chromosome. Of these nine, four were converted into polymorphic cleaved amplified polymorphic sequence (CAPS) markers between Yr5 and yr5 isolines, and one was mapped within 5.3 cM of the Yr5 locus. This study represents the first array-based polymorphism survey in near-isogenic genotypes, and the results are applied to an agriculturally important trait.

Transcriptional profiling of chickpea genes differentially regulated in response to high-salinity, cold and drought.

BACKGROUND: Cultivated chickpea (Cicer arietinum) has a narrow genetic base making it difficult for breeders to produce new elite cultivars with durable resistance to major biotic and abiotic stresses. As an alternative to genome mapping, microarrays have recently been applied in crop species to identify and assess the function of putative genes thought to be involved in plant abiotic stress and defence responses. In the present study, a cDNA microarray approach was taken in order to determine if the transcription of genes, from a set of previously identified putative stress-responsive genes from chickpea and its close relative Lathyrus sativus, were altered in chickpea by the three abiotic stresses; drought, cold and high-salinity. For this, chickpea genotypes known to be tolerant and susceptible to each abiotic stress were challenged and gene expression in the leaf, root and/or flower tissues was studied. The transcripts that were differentially expressed among stressed and unstressed plants in response to the particular stress were analysed in the context of tolerant/susceptible genotypes. RESULTS: The transcriptional change of more than two fold was observed for 109, 210 and 386 genes after drought, cold and high-salinity treatments, respectively. Among these, two, 15 and 30 genes were consensually differentially expressed (DE) between tolerant and susceptible genotypes studied for drought, cold and high-salinity, respectively. The genes that were DE in tolerant and susceptible genotypes under abiotic stresses code for various functional and regulatory proteins. Significant differences in stress responses were observed within and between tolerant and susceptible genotypes highlighting the multiple gene control and complexity of abiotic stress response mechanism in chickpea. CONCLUSION: The annotation of these genes suggests that they may have a role in abiotic stress response and are potential candidates for tolerance/susceptibility.

Construction and validation of a prototype microarray for efficient and high-throughput genotyping of angiosperms.

Until recently, the identification of plants relied on conventional techniques, such as morphological, anatomical and chemical profiling, that are often inefficient or unfeasible in certain situations. Extensive literature exists describing the use of polymerase chain reaction (PCR) DNA-based identification techniques, which offer a reliable platform, but their broad application is often limited by a low throughput. However, hybridization-based microarray technology represents a rapid and high-throughput tool for genotype identification at a molecular level. Using an innovative technique, a 'Subtracted Diversity Array' (SDA) of 376 features was constructed from a pooled genomic DNA library of 49 angiosperm species, from which pooled non-angiosperm genomic DNA was subtracted. Although not the first use of a subtraction technique for genotyping, the SDA method was superior in accuracy, sensitivity and efficiency, and showed high-throughput capacity and broad application. The SDA technique was validated for potential genotyping use, and the results indicated a successful subtraction of non-angiosperm DNA. Statistical analysis of the polymorphic features from the pilot study enabled the establishment of accurate phylogenetic relationships, confirming the potential use of the SDA technique for genotyping. Further, the technique substantially enriched the presence of polymorphic sequences; 68% were polymorphic when using the array to differentiate six angiosperm clades (Asterids, Rosids, Caryophyllids, Ranunculids, Monocots and Eumagnoliids). The 'proof of concept' experiments demonstrate the potential of establishing a highly informative, reliable and high-throughput microarray-based technique for novel application to sequence independent genotyping of major angiosperm clades.

Transcriptional profiling of chickpea genes differentially regulated by salicylic acid, methyl jasmonate and aminocyclopropane carboxylic acid to reveal pathways of defence-related gene regulation.

Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes and grasspea (Lathyrus sativus L.) expressed sequence tags, chickpea responses to treatments with the defence signalling compounds salicylic acid (SA), methyl jasmonate (MeJA) and aminocyclopropane carboxylic acid (ACC) were studied in three chickpea genotypes with ranging levels of resistance to ascochyta blight [Ascochyta rabiei (Pass.) L.]. The experimental system minimised environmental effects and was conducted in reference design, where samples from untreated controls acted as references against post-treatment samples. Microarray observations were also validated by quantitative reverse transcription-polymerase chain reaction. The time-course expression patterns of 715 experimental microarray features resulted in differential expression of 425 transcripts. The A. rabiei resistant chickpea genotypes showed a more substantial range of defence-related gene induction by all treatments, indicating that they may possess stronger abilities to resist pathogens. Further, the involvement of SA, MeJA and ACC signalling was identified for the regulation of some important A. rabiei responsive transcripts, as well as cross-talk between these pathways. In the current study we also found evidence to suggest the involvement of A. rabiei-specific signalling mechanisms for the induction of several transcripts that were previously implicated in A. rabiei resistance. This study characterised the regulatory mechanisms of many chickpea transcripts that may be important in defence against various pathogens, as well as other cellular functions. These results provide novel insights to the molecular control of chickpea cellular processes, which may assist the understanding of chickpea defence mechanisms and allow enhanced development of disease resistant cultivars.

Functional genomics in chickpea: an emerging frontier for molecular-assisted breeding.

Chickpea is a valuable and important agricultural crop, but yield potential is limited by a series of biotic and abiotic stresses, including Ascochyta blight, Fusarium wilt, drought, cold and salinity. To accelerate molecular breeding efforts for the discovery and introgression of stress tolerance genes into cultivated chickpea, functional genomics approaches are rapidly growing. Recently a series of genetic tools for chickpea have become available that have allowed high-powered functional genomics studies to proceed, including a dense genetic map, large insert genome libraries, expressed sequence tag libraries, microarrays, serial analysis of gene expression, transgenics and reverse genetics. This review summarises the development of these genomic tools and the achievements made in initial and emerging functional genomics studies. Much of the initial research focused on Ascochyta blight resistance, and a resistance model has been synthesised based on the results of various studies. Use of the rich comparative genomics resources from the model legumes Medicago truncatula and Lotus japonicus is also discussed. Finally, perspectives on the future directions for chickpea functional genomics, with the goal of developing elite chickpea cultivars, are discussed.

Expression profiling of chickpea genes differentially regulated during a resistance response to Ascochyta rabiei.

Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) expressed sequence tags (ESTs) and lentil (Lens culinaris Med.) resistance gene analogues, the ascochyta blight (Ascochyta rabiei (Pass.) L.) resistance response was studied in four chickpea genotypes, including resistant, moderately resistant, susceptible and wild relative (Cicer echinospermum L.) genotypes. The experimental system minimized environmental effects and was conducted in reference design, in which samples from mock-inoculated controls acted as reference against post-inoculation samples. Robust data quality was achieved through the use of three biological replicates (including a dye swap), the inclusion of negative controls and strict selection criteria for differentially expressed genes, including a fold change cut-off determined by self-self hybridizations, Student's t-test and multiple testing correction (P < 0.05). Microarray observations were also validated by quantitative reverse transcriptase-polymerase chain reaction (RT-PCR). The time course expression patterns of 756 microarray features resulted in the differential expression of 97 genes in at least one genotype at one time point. k-means clustering grouped the genes into clusters of similar observations for each genotype, and comparisons between A. rabiei-resistant and A. rabiei-susceptible genotypes revealed potential gene 'signatures' predictive of effective A. rabiei resistance. These genes included several pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein, Ca-binding protein and several unknown proteins. The potential involvement of these genes and their pathways of induction are discussed. This study represents the first large-scale gene expression profiling in chickpea, and future work will focus on the functional validation of the genes of interest.