Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork

Polygenic pathogen networks influence transcriptional plasticity in the Arabidopsis-Botrytis pathosystem

Bidirectional flow of information shapes the outcome of the host-pathogen interactions and depends on the genetics of each organism. Recent work has begun to use co-transcriptomic studies to shed light on this bidirectional flow, but it is unclear how plastic the co-transcriptome is in response to genetic variation in both the host and pathogen. To study co-transcriptome plasticity, we conducted transcriptomics using natural genetic variation in the pathogen, Botrytis cinerea, and large-effect genetic variation abolishing defense signaling pathways within the host, Arabidopsis thaliana. We show that genetic variation in the pathogen has a greater influence on the co-transcriptome than mutations that abolish defense signaling pathways in the host. Genome-wide association mapping using the pathogens' genetic variation and both organisms' transcriptomes allowed an assessment of how the pathogen modulates plasticity in response to the host. This showed that the differences in both organism's responses were linked to trans-expression quantitative trait loci (eQTL) hotspots within the pathogen's genome. These hotspots control gene sets in either the host or pathogen and show differential allele sensitivity to the host's genetic variation rather than qualitative host specificity. Interestingly, nearly all the trans-eQTL hotspots were unique to the host or pathogen transcriptomes. In this system of differential plasticity, the pathogen mediates the shift in the co-transcriptome more than the host.

Gene Pyramiding for Sustainable Crop Improvement against Biotic and Abiotic Stresses

Sustainable agricultural production is endangered by several ecological factors, such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop-breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker-assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to biotic and abiotic stresses for sustainable crop improvement.

Characterisation of barley resistance to rhynchosporium on chromosome 6HS

Major resistance gene to rhynchosporium, Rrs18, maps close to the telomere on the short arm of chromosome 6H in barley. Rhynchosporium or barley scald caused by a fungal pathogen Rhynchosporium commune is one of the most destructive and economically important diseases of barley in the world. Testing of Steptoe × Morex and CIho 3515 × Alexis doubled haploid populations has revealed a large effect QTL for resistance to R. commune close to the telomere on the short arm of chromosome 6H, present in both populations. Mapping markers flanking the QTL from both populations onto the 2017 Morex genome assembly revealed a rhynchosporium resistance locus independent of Rrs13 that we named Rrs18. The causal gene was fine mapped to an interval of 660 Kb using Steptoe × Morex backcross 1 S₂ and S₃ lines with molecular markers developed from Steptoe exome capture variant calling. Sequencing RNA from CIho 3515 and Alexis revealed that only 4 genes within the Rrs18 interval were transcribed in leaf tissue with a serine/threonine protein kinase being the most likely candidate for Rrs18.

Prior knowledge guided eQTL mapping for identifying candidate genes

Background

Expression quantitative trait loci (eQTL) mapping is often used to identify genetic loci and candidate genes correlated with traits. Although usually a group of genes affect complex traits, genes in most eQTL mapping methods are considered as independent. Recently, some eQTL mapping methods have accounted for correlated genes, used biological prior knowledge and applied these in model species such as yeast or mouse. However, biological prior knowledge might be very limited for most species.

Results

We proposed a data-driven prior knowledge guided eQTL mapping for identifying candidate genes. At first, quantitative trait loci (QTL) analysis was used to identify single nucleotide polymorphisms (SNP) markers that are associated with traits. Then co-expressed gene modules were generated and gene modules significantly associated with traits were selected. Prior knowledge from QTL mapping was used for eQTL mapping on the selected modules. We tested and compared prior knowledge guided eQTL mapping to the eQTL mapping with no prior knowledge in a simulation study and two barley stem rust resistance case studies.

The results in simulation study and real barley case studies show that models using prior knowledge outperform models without prior knowledge. In the first case study, three gene modules were selected and one of the gene modules was enriched with defense response Gene Ontology (GO) terms. Also, one probe in the gene module is mapped to Rpg1, previously identified as resistance gene to stem rust. In the second case study, four gene modules are identified, one gene module is significantly enriched with defense response to fungus and bacterium.

Conclusions

Prior knowledge guided eQTL mapping is an effective method for identifying candidate genes. The case studies in stem rust show that this approach is robust, and outperforms methods with no prior knowledge in identifying candidate genes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1387-9) contains supplementary material, which is available to authorized users.

Multiple quantitative trait analysis using bayesian networks

Models for genome-wide prediction and association studies usually target a single phenotypic trait. However, in animal and plant genetics it is common to record information on multiple phenotypes for each individual that will be genotyped. Modeling traits individually disregards the fact that they are most likely associated due to pleiotropy and shared biological basis, thus providing only a partial, confounded view of genetic effects and phenotypic interactions. In this article we use data from a Multiparent Advanced Generation Inter-Cross (MAGIC) winter wheat population to explore Bayesian networks as a convenient and interpretable framework for the simultaneous modeling of multiple quantitative traits. We show that they are equivalent to multivariate genetic best linear unbiased prediction (GBLUP) and that they are competitive with single-trait elastic net and single-trait GBLUP in predictive performance. Finally, we discuss their relationship with other additive-effects models and their advantages in inference and interpretation. MAGIC populations provide an ideal setting for this kind of investigation because the very low population structure and large sample size result in predictive models with good power and limited confounding due to relatedness.

Organ specificity and transcriptional control of metabolic routes revealed by expression QTL profiling of source--sink tissues in a segregating potato population

BACKGROUND

With the completion of genome sequences belonging to some of the major crop plants, new challenges arise to utilize this data for crop improvement and increased food security. The field of genetical genomics has the potential to identify genes displaying heritable differential expression associated to important phenotypic traits. Here we describe the identification of expression QTLs (eQTLs) in two different potato tissues of a segregating potato population and query the potato genome sequence to differentiate between cis- and trans-acting eQTLs in relation to gene subfunctionalization.

RESULTS

Leaf and tuber samples were analysed and screened for the presence of conserved and tissue dependent eQTLs. Expression QTLs present in both tissues are predominantly cis-acting whilst for tissue specific QTLs, the percentage of trans-acting QTLs increases. Tissue dependent eQTLs were assigned to functional classes and visualized in metabolic pathways. We identified a potential regulatory network on chromosome 10 involving genes crucial for maintaining circadian rhythms and controlling clock output genes. In addition, we show that the type of genetic material screened and sampling strategy applied, can have a high impact on the output of genetical genomics studies.

CONCLUSIONS

Identification of tissue dependent regulatory networks based on mapped differential expression not only gives us insight in tissue dependent gene subfunctionalization but brings new insights into key biological processes and delivers targets for future haplotyping and genetic marker development.

Genetic dissection of barley morphology and development

Since the early 20th century, barley (Hordeum vulgare) has been a model for investigating the effects of physical and chemical mutagens and for exploring the potential of mutation breeding in crop improvement. As a consequence, extensive and well-characterized collections of morphological and developmental mutants have been assembled that represent a valuable resource for exploring a wide range of complex and fundamental biological processes. We constructed a collection of 881 backcrossed lines containing mutant alleles that induce a majority of the morphological and developmental variation described in this species. After genotyping these lines with up to 3,072 single nucleotide polymorphisms, comparison to their recurrent parent defined the genetic location of 426 mutant alleles to chromosomal segments, each representing on average <3% of the barley genetic map. We show how the gene content in these segments can be predicted through conservation of synteny with model cereal genomes, providing a route to rapid gene identification.

Pathogenesis-associated transcriptional patterns in Triticeae

The Triticeae tribe of the plant Poaceae family contains some of the most important cereal crop plants for nutrition of humans and livestock such as wheat and barley. Despite the agronomical relevance of plant immunity, knowledge on mechanisms of disease or resistance in Triticeae is limited. It is hardly understood what actually stops a microbial invader when restricted by the plant and in how far a susceptible host plant contributes to pathogenesis. Transcriptional reprogramming of the host plant may be involved in both immunity and disease. This paper gives an overview about recent analyses of global pathogenesis-related transcriptional patterns in response of Triticeae to biotrophic or non-biotrophic fungal pathogens and their toxins. It highlights enriched biological functions in association with successful plant defence or disease as well as experiments that successfully translated gene expression data into analysis of gene functions.

Making the most of 'omics' for crop breeding

Adoption of new breeding technologies is likely to underpin future gains in crop productivity. The rapid advances in 'omics' technologies provide an opportunity to generate new datasets for crop species. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding. In this review, we discuss these advances, which have opened the door to new techniques for construction and screening of breeding populations, to increase ultimately the efficiency of selection and accelerate the rates of genetic gain.

Exploiting induced variation to dissect quantitative traits in barley

The identification of genes underlying complex quantitative traits such as grain yield by means of conventional genetic analysis (positional cloning) requires the development of several large mapping populations. However, it is possible that phenotypically related, but more extreme, allelic variants generated by mutational studies could provide a means for more efficient cloning of QTLs (quantitative trait loci). In barley (Hordeum vulgare), with the development of high-throughput genome analysis tools, efficient genome-wide identification of genetic loci harbouring mutant alleles has recently become possible. Genotypic data from NILs (near-isogenic lines) that carry induced or natural variants of genes that control aspects of plant development can be compared with the location of QTLs to potentially identify candidate genes for development­-related traits such as grain yield. As yield itself can be divided into a number of allometric component traits such as tillers per plant, kernels per spike and kernel size, mutant alleles that both affect these traits and are located within the confidence intervals for major yield QTLs may represent extreme variants of the underlying genes. In addition, the development of detailed comparative genomic models based on the alignment of a high-density barley gene map with the rice and sorghum physical maps, has enabled an informed prioritization of ‘known function’ genes as candidates for both QTLs and induced mutant genes.

Documentation system for plant transformation service and research

BACKGROUND

In plant transformation, method compliance is critical for success. Transformation methods are complicated and tend to evolve over time. Until the complete method is published, method details are often partially orally transmitted and thus bound to a few people. Their documentation in text files are often a mixture of material and method description with many references to other sources especially to media description. These media are complex and often composed from several commercially available mixtures plus individually prepared stocks. The actual transformation experiment is generally documented in lab books, in which deviations from the methods and results are reported. Additionally, work schedules are planned in diaries. Both paper-based sources lack backup copies and miss unambiguous links to method descriptions and media recipes.

DESCRIPTION

To solve the problem, we devised a standard-operation-procedure system based on a Microsoft Access database containing the interlinked modules 'Media', 'Methods' and 'Experiments'. The Media module contains all basic chemicals, stocks and complex media. In this module, complex media are composed from other elements of the Media module, thus mimicking the workflows of media preparation in the lab. The Media module is made attractive to the user by functions that generate file cards and labels. The Methods module describes each method stepwise and links the steps to the media. Copy functions allow cloning of old methods to document method evolution without alteration of the old methods. Activation and inactivation functions in the Media and the Methods module remove outdated entries from active use. The Experiments module links the method to experiment specific information. This module generates a lab-book like user interface and a work schedule, and it contains a simple result section.

CONCLUSION

The system has been evolved and tested over several years in a transformation service unit, where it increased efficiency. Additionally, the system provided rapid access to data for quality control and decision making. The system can be easily modified for the use in other research environments.

Genetical toxicogenomics in Drosophila identifies master-modulatory loci that are regulated by developmental exposure to lead

The genetics of gene expression in recombinant inbred lines (RILs) can be mapped as expression quantitative trait loci (eQTLs). So-called "genetical genomics" studies have identified locally acting eQTLs (cis-eQTLs) for genes that show differences in steady-state RNA levels. These studies have also identified distantly acting master-modulatory trans-eQTLs that regulate tens or hundreds of transcripts (hotspots or transbands). We expand on these studies by performing genetical genomics experiments in two environments in order to identify trans-eQTL that might be regulated by developmental exposure to the neurotoxin lead. Flies from each of 75 RIL were raised from eggs to adults on either control food (made with 250 microM sodium acetate), or lead-treated food (made with 250 microM lead acetate, PbAc). RNA expression analyses of whole adult male flies (5-10 days old) were performed with Affymetrix DrosII whole genome arrays (18,952 probesets). Among the 1389 genes with cis-eQTL, there were 405 genes unique to control flies and 544 genes unique to lead-treated ones (440 genes had the same cis-eQTLs in both samples). There are 2396 genes with trans-eQTL which mapped to 12 major transbands with greater than 95 genes. Permutation analyses of the strain labels but not the expression data suggests that the total number of eQTL and the number of transbands are more important criteria for validation than the size of the transband. Two transbands, one located on the 2nd chromosome and one on the 3rd chromosome, co-regulate 33 lead-induced genes, many of which are involved in neurodevelopmental processes. For these 33 genes, rather than allelic variation at one locus exerting differential effects in two environments, we found that variation at two different loci are required for optimal effects on lead-induced expression.

What has natural variation taught us about plant development, physiology, and adaptation?

Nearly 100 genes and functional polymorphisms underlying natural variation in plant development and physiology have been identified. In crop plants, these include genes involved in domestication traits, such as those related to plant architecture, fruit and seed structure and morphology, as well as yield and quality traits improved by subsequent crop breeding. In wild plants, comparable traits have been dissected mainly in Arabidopsis thaliana. In this review, we discuss the major contributions of the analysis of natural variation to our understanding of plant development and physiology, focusing in particular on the timing of germination and flowering, plant growth and morphology, primary metabolism, and mineral accumulation. Overall, functional polymorphisms appear in all types of genes and gene regions, and they may have multiple mutational causes. However, understanding this diversity in relation to adaptation and environmental variation is a challenge for which tools are now available.