GABA does not regulate stomatal CO2 signalling in Arabidopsis.

Optimal stomatal regulation is important for plant adaptation to changing environmental conditions and for maintaining crop yield. The guard-cell signal GABA is produced from glutamate by Glutamate Decarboxylase (GAD) during a reaction that generates carbon dioxide (CO2) as a by-product. Here, we investigated a putative connection between GABA signalling and the more clearly defined CO2 signalling pathway in guard cells. The GABA-deficient mutant lines gad2-1, gad2-2 and gad1/2/4/5 were examined for stomatal sensitivity to various CO2 concentrations. Our findings show a phenotypical discrepancy between the allelic mutant lines gad2-1 and gad2-2 - a weakened CO2 response in gad2-1 (GABI_474_E05) in contrast to a wild-type response in gad2-2 (SALK_028819) and gad1/2/4/5. Through transcriptomic and genomic investigation, we traced the response of gad2-1 to a deletion of full-length Mitogen-activated protein kinase 12 (MPK12) in the GABI-KAT line, thereafter as renamed gad2-1*. Guard cell-specific complementation of MPK12 restored the gad2-1* CO2 phenotype, which confirms the proposed importance of MPK12 to CO2 sensitivity. Additionally, we found that stomatal opening under low atmospheric CO2 occurs independently of the GABA-modulated opening-channel ALMT9. Our results confirm that GABA has a role in modulating the rate of stomatal opening and closing - but not in response to CO2  per se.

RNA-seq analysis of laser microdissected Arabidopsis thaliana leaf epidermis, mesophyll and vasculature defines tissue-specific transcriptional responses to multiple stress treatments.

Acclimation of plants to adverse conditions requires the coordination of gene expression and signalling pathways between tissues and cell types. As the energy and carbon capturing organs, leaves are significantly affected by abiotic and biotic stresses. However, tissue- or cell type-specific analyses of stress responses have focussed on the Arabidopsis root. Here, we comparatively explore the transcriptomes of three leaf tissues (epidermis, mesophyll, vasculature) after induction of diverse stress pathways by chemical stimuli (antimycin A, 3-amino-1,2,4-triazole, methyl viologen, salicylic acid) and ultraviolet light in Arabidopsis using laser capture microdissection followed by RNA sequencing. Stimulation of stress pathways caused an overall reduction in the number of genes expressed in a tissue-specific manner, though a small subset gained or changed their tissue specificity. We find no evidence of a common stress response, with only a few genes consistently responsive to two or more treatments in the analysed tissues. However, differentially expressed genes overlap between tissues for individual treatments. A focussed analysis provided evidence for an interaction of auxin and ethylene that mediates retrograde signalling during mitochondrial dysfunction specifically in the epidermis, and a gene regulatory network defined the hierarchy of interactions. Taken together, we have generated an extensive reference dataset that will be valuable for future experiments analysing transcriptional responses on a tissue or single-cell level. Our results will enable the tailoring of the tissue-specific engineering of stress-tolerant plants.

Recent advances in Cannabis sativa genomics research.

Cannabis (Cannabis sativa L.) is one of the oldest cultivated plants purported to have unique medicinal properties. However, scientific research of cannabis has been restricted by the Single Convention on Narcotic Drugs of 1961, an international treaty that prohibits the production and supply of narcotic drugs except under license. Legislation governing cannabis cultivation for research, medicinal and even recreational purposes has been relaxed recently in certain jurisdictions. As a result, there is now potential to accelerate cultivar development of this multi-use and potentially medically useful plant species by application of modern genomics technologies. Whilst genomics has been pivotal to our understanding of the basic biology and molecular mechanisms controlling key traits in several crop species, much work is needed for cannabis. In this review we provide a comprehensive summary of key cannabis genomics resources and their applications. We also discuss prospective applications of existing and emerging genomics technologies for accelerating the genetic improvement of cannabis.

Delineating the Tnt1 Insertion Landscape of the Model Legume Medicago truncatula cv. R108 at the Hi-C Resolution Using a Chromosome-Length Genome Assembly.

Legumes are of great interest for sustainable agricultural production as they fix atmospheric nitrogen to improve the soil. Medicago truncatula is a well-established model legume, and extensive studies in fundamental molecular, physiological, and developmental biology have been undertaken to translate into trait improvements in economically important legume crops worldwide. However, M. truncatula reference genome was generated in the accession Jemalong A17, which is highly recalcitrant to transformation. M. truncatula R108 is more attractive for genetic studies due to its high transformation efficiency and Tnt1-insertion population resource for functional genomics. The need to perform accurate synteny analysis and comprehensive genome-scale comparisons necessitates a chromosome-length genome assembly for M. truncatula cv. R108. Here, we performed in situ Hi-C (48×) to anchor, order, orient scaffolds, and correct misjoins of contigs in a previously published genome assembly (R108 v1.0), resulting in an improved genome assembly containing eight chromosome-length scaffolds that span 97.62% of the sequenced bases in the input assembly. The long-range physical information data generated using Hi-C allowed us to obtain a chromosome-length ordering of the genome assembly, better validate previous draft misjoins, and provide further insights accurately predicting synteny between A17 and R108 regions corresponding to the known chromosome 4/8 translocation. Furthermore, mapping the Tnt1 insertion landscape on this reference assembly presents an important resource for M. truncatula functional genomics by supporting efficient mutant gene identification in Tnt1 insertion lines. Our data provide a much-needed foundational resource that supports functional and molecular research into the Leguminosae for sustainable agriculture and feeding the future.

Characterization of disease resistance genes in the Brassica napus pangenome reveals significant structural variation.

Methods based on single nucleotide polymorphism (SNP), copy number variation (CNV) and presence/absence variation (PAV) discovery provide a valuable resource to study gene structure and evolution. However, as a result of these structural variations, a single reference genome is unable to cover the entire gene content of a species. Therefore, pangenomics analysis is needed to ensure that the genomic diversity within a species is fully represented. Brassica napus is one of the most important oilseed crops in the world and exhibits variability in its resistance genes across different cultivars. Here, we characterized resistance gene distribution across 50 B. napus lines. We identified a total of 1749 resistance gene analogs (RGAs), of which 996 are core and 753 are variable, 368 of which are not present in the reference genome (cv. Darmor-bzh). In addition, a total of 15 318 SNPs were predicted within 1030 of the RGAs. The results showed that core R-genes harbour more SNPs than variable genes. More nucleotide binding site-leucine-rich repeat (NBS-LRR) genes were located in clusters than as singletons, with variable genes more likely to be found in clusters. We identified 106 RGA candidates linked to blackleg resistance quantitative trait locus (QTL). This study provides a better understanding of resistance genes to target for genomics-based improvement and improved disease resistance.

Status and Potential of Single-Cell Transcriptomics for Understanding Plant Development and Functional Biology.

The advent of modern "omics" technologies (genomics, transcriptomics, proteomics, and metabolomics) are attributed to innovative breakthroughs in genome sequencing, bioinformatics, and analytic tools. An organism's biological structure and function is the result of the concerted action of single cells in different tissues. Single cell genomics has emerged as a ground-breaking technology that has greatly enhanced our understanding of the complexity of gene expression at a microscopic resolution and holds the potential to revolutionize the way we characterize complex cell assemblies and study their spatial organization, dynamics, clonal distribution, pathways, function, and networking. Mammalian systems have benefitted immensely from these approaches to dissect complex systems such as cancer, immunological disorders, epigenetic controls of diseases, and understanding of developmental biology. However, the applications of single-cell omics in plant research are just starting. The potential to decipher the fundamentals of developmental and functional biology of large and complex plant species at the single-cell resolution are now becoming important drivers of research. In this review, we present the status, challenges and potential of one important and most commonly used single-cell omics technique in plants, namely single cell transcriptomics. © 2020 International Society for Advancement of Cytometry.

The pangenome of hexaploid bread wheat.

There is an increasing understanding that variation in gene presence-absence plays an important role in the heritability of agronomic traits; however, there have been relatively few studies on variation in gene presence-absence in crop species. Hexaploid wheat is one of the most important food crops in the world and intensive breeding has reduced the genetic diversity of elite cultivars. Major efforts have produced draft genome assemblies for the cultivar Chinese Spring, but it is unknown how well this represents the genome diversity found in current modern elite cultivars. In this study we build an improved reference for Chinese Spring and explore gene diversity across 18 wheat cultivars. We predict a pangenome size of 140 500 ± 102 genes, a core genome of 81 070 ± 1631 genes and an average of 128 656 genes in each cultivar. Functional annotation of the variable gene set suggests that it is enriched for genes that may be associated with important agronomic traits. In addition to variation in gene presence, more than 36 million intervarietal single nucleotide polymorphisms were identified across the pangenome. This study of the wheat pangenome provides insight into genome diversity in elite wheat as a basis for genomics-based improvement of this important crop. A wheat pangenome, GBrowse, is available at http://appliedbioinformatics.com.au/cgi-bin/gb2/gbrowse/WheatPan/, and data are available to download from http://wheatgenome.info/wheat_genome_databases.php.

Homoeologous exchange is a major cause of gene presence/absence variation in the amphidiploid Brassica napus.

Homoeologous exchanges (HEs) have been shown to generate novel gene combinations and phenotypes in a range of polyploid species. Gene presence/absence variation (PAV) is also a major contributor to genetic diversity. In this study, we show that there is an association between these two events, particularly in recent Brassica napus synthetic accessions, and that these represent a novel source of genetic diversity, which can be captured for the improvement of this important crop species. By assembling the pangenome of B. napus, we show that 38% of the genes display PAV behaviour, with some of these variable genes predicted to be involved in important agronomic traits including flowering time, disease resistance, acyl lipid metabolism and glucosinolate metabolism. This study is a first and provides a detailed characterization of the association between HEs and PAVs in B. napus at the pangenome level.

Exploring the genetic and adaptive diversity of a pan-Mediterranean crop wild relative: narrow-leafed lupin.

KEY MESSAGE: This first pan-Mediterranean analysis of genetic diversity in wild narrow-leafed lupin revealed strong East-West genetic differentiation of populations, an historic eastward migration, and signatures of genetic adaptation to climatic variables. Most grain crops suffer from a narrow genetic base, which limits their potential for adapting to new challenges such as increased stresses associated with climate change. Plant breeders are returning to the wild ancestors of crops and their close relatives to broaden the genetic base of their crops. Understanding the genetic adaptation of these wild relatives will help plant breeders most effectively use available wild diversity. Here, we took narrow-leafed lupin (Lupinus angustifolius L.) as a model to understand adaptation in a wild crop ancestor. A set of 142 wild accessions of narrow-leafed lupin from across the Mediterranean basin were subjected to genotyping-by-sequencing using Diversity Arrays Technology. Phylogenetic, linkage disequilibrium and demographic analyses were employed to explore the history of narrow-leafed lupin within the Mediterranean region. We found strong genetic differentiation between accessions from the western and eastern Mediterranean, evidence of an historic West to East migration, and that eastern Mediterranean narrow-leafed lupin experienced a severe and recent genetic bottleneck. We showed that these two populations differ for flowering time as a result of local adaptation, with the West flowering late while the East flowers early. A genome-wide association study identified single nucleotide polymorphism markers associated with climatic adaptation. Resolving the origin of wild narrow-leafed lupin and how its migration has induced adaptation to specific regions of the Mediterranean serves as a useful resource not only for developing narrow-leafed lupin cultivars with greater resilience to a changing climate, but also as a model which can be applied to other legumes.

Insights into respiratory disease through bioinformatics.

Respiratory diseases such as asthma, chronic obstructive pulmonary disease and lung cancer represent a critical area for medical research as millions of people are affected globally. The development of new strategies for treatment and/or prevention, and the identification of biomarkers for patient stratification and early detection of disease inception are essential to reducing the impact of lung diseases. The successful translation of research into clinical practice requires a detailed understanding of the underlying biology. In this regard, the advent of next-generation sequencing and mass spectrometry has led to the generation of an unprecedented amount of data spanning multiple layers of biological regulation (genome, epigenome, transcriptome, proteome, metabolome and microbiome). Dealing with this wealth of data requires sophisticated bioinformatics and statistical tools. Here, we review the basic concepts in bioinformatics and genomic data analysis and illustrate the application of these tools to further our understanding of lung diseases. We also highlight the potential for data integration of multi-omic profiles and computational drug repurposing to define disease subphenotypes and match them to targeted therapies, paving the way for personalized medicine.

Assembly and comparison of two closely related Brassica napus genomes.

As an increasing number of plant genome sequences become available, it is clear that gene content varies between individuals, and the challenge arises to predict the gene content of a species. However, genome comparison is often confounded by variation in assembly and annotation. Differentiating between true gene absence and variation in assembly or annotation is essential for the accurate identification of conserved and variable genes in a species. Here, we present the de novo assembly of the B. napus cultivar Tapidor and comparison with an improved assembly of the Brassica napus cultivar Darmor-bzh. Both cultivars were annotated using the same method to allow comparison of gene content. We identified genes unique to each cultivar and differentiate these from artefacts due to variation in the assembly and annotation. We demonstrate that using a common annotation pipeline can result in different gene predictions, even for closely related cultivars, and repeat regions which collapse during assembly impact whole genome comparison. After accounting for differences in assembly and annotation, we demonstrate that the genome of Darmor-bzh contains a greater number of genes than the genome of Tapidor. Our results are the first step towards comparison of the true differences between B. napus genomes and highlight the potential sources of error in future production of a B. napus pangenome.

A comprehensive draft genome sequence for lupin (Lupinus angustifolius), an emerging health food: insights into plant-microbe interactions and legume evolution.

Lupins are important grain legume crops that form a critical part of sustainable farming systems, reducing fertilizer use and providing disease breaks. It has a basal phylogenetic position relative to other crop and model legumes and a high speciation rate. Narrow-leafed lupin (NLL; Lupinus angustifolius L.) is gaining popularity as a health food, which is high in protein and dietary fibre but low in starch and gluten-free. We report the draft genome assembly (609 Mb) of NLL cultivar Tanjil, which has captured >98% of the gene content, sequences of additional lines and a dense genetic map. Lupins are unique among legumes and differ from most other land plants in that they do not form mycorrhizal associations. Remarkably, we find that NLL has lost all mycorrhiza-specific genes, but has retained genes commonly required for mycorrhization and nodulation. In addition, the genome also provided candidate genes for key disease resistance and domestication traits. We also find evidence of a whole-genome triplication at around 25 million years ago in the genistoid lineage leading to Lupinus. Our results will support detailed studies of legume evolution and accelerate lupin breeding programmes.

A Practical Guide to Inferring Multi-Omics Networks in Plant Systems.

The inference of gene regulatory networks can reveal molecular connections underlying biological processes and improve our understanding of complex biological phenomena in plants. Many previous network studies have inferred networks using only one type of omics data, such as transcriptomics. However, given more recent work applying multi-omics integration in plant biology, such as combining (phospho)proteomics with transcriptomics, it may be advantageous to integrate multiple omics data types into a comprehensive network prediction. Here, we describe a state-of-the-art approach for integrating multi-omics data with gene regulatory network inference to describe signaling pathways and uncover novel regulators. We detail how to download and process transcriptomics and (phospho)proteomics data for network inference, using an example dataset from the plant hormone signaling field. We provide a step-by-step protocol for inference, visualization, and analysis of an integrative multi-omics network using currently available methods. This chapter serves as an accessible guide for novice and intermediate bioinformaticians to analyze their own datasets and reanalyze published work.

Annotation of Protein-Coding Genes in Plant Genomes.

Advances in next-generation sequencing technologies and the lower sequencing costs are paving the way to more plant genome sequencing, assembly, and annotation projects. While genome assembly is the first step toward elucidating the genome structure of a species, it is the annotation of the protein-coding genes that provide meaningful information to biologists. However, genome annotation is not a trivial task. Therefore, the aim of this chapter is to provide a detailed view of this important process, including tools and commands that can be used to carry out such a process.

Applications of cell- and tissue-specific 'omics to improve plant productivity.

The individual tissues and cell types of plants each have characteristic properties that contribute to the function of the plant as a whole. These are reflected by unique patterns of gene expression, protein and metabolite content, which enable cell-type-specific patterns of growth, development and physiology. Gene regulatory networks act within the cell types to govern the production and activity of these components. For the broader organism to grow and reproduce successfully, cell-type-specific activity must also function within the context of surrounding cell types, which is achieved by coordination of signalling pathways. We can investigate how gene regulatory networks are constructed and function using integrative 'omics technologies. Historically such experiments in plant biological research have been performed at the bulk tissue level, to organ resolution at best. In this review, we describe recent advances in cell- and tissue-specific 'omics technologies that allow investigation at much improved resolution. We discuss the advantages of these approaches for fundamental and translational plant biology, illustrated through the examples of specialised metabolism in medicinal plants and seed germination. We also discuss the challenges that must be overcome for such approaches to be adopted widely by the community.

How 'omics technologies can drive plant engineering, ecosystem surveillance, human and animal health.

'Omics describes a broad collection of research tools and techniques that enable researchers to collect data about biological systems at a very large, or near-complete, scale. These include sequencing of individual and community genomes (genomics, metagenomics), characterization and quantification of gene expression (transcriptomics), metabolite abundance (metabolomics), protein content (proteomics) and phosphorylation (phospho-proteomics), amongst many others. Though initially exploited as tools for fundamental discovery, 'omics techniques are now used extensively in applied and translational research, for example in plant and animal breeding, biomarker development and drug discovery. In this collection of reviews, we aimed to introduce readers to current and future applications of 'omics technologies to solve real-world problems.

Insights into opium poppy (Papaver spp.) genetic diversity from genotyping-by-sequencing analysis.

Opium poppy (Papaver somniferum) is one of the world's oldest medicinal plants and a versatile model system to study secondary metabolism. However, our knowledge of its genetic diversity is limited, restricting utilization of the available germplasm for research and crop improvement. We used genotyping-by-sequencing to investigate the extent of genetic diversity and population structure in a collection of poppy germplasm consisting of 91 accessions originating in 30 countries of Europe, North Africa, America, and Asia. We identified five genetically distinct subpopulations using discriminate analysis of principal components and STRUCTURE analysis. Most accessions obtained from the same country were grouped together within subpopulations, likely a consequence of the restriction on movement of poppy germplasm. Alkaloid profiles of accessions were highly diverse, with morphine being dominant. Phylogenetic analysis identified genetic groups that were largely consistent with the subpopulations detected and that could be differentiated broadly based on traits such as number of branches and seed weight. These accessions and the associated genotypic data are valuable resources for further genetic diversity analysis, which could include definition of poppy core sets to facilitate genebank management and use of the diversity for genetic improvement of this valuable crop.

SNP Discovery Using a Pangenome: Has the Single Reference Approach Become Obsolete?

Increasing evidence suggests that a single individual is insufficient to capture the genetic diversity within a species due to gene presence absence variation. In order to understand the extent to which genomic variation occurs in a species, the construction of its pangenome is necessary. The pangenome represents the complete set of genes of a species; it is composed of core genes, which are present in all individuals, and variable genes, which are present only in some individuals. Aside from variations at the gene level, single nucleotide polymorphisms (SNPs) are also an important form of genetic variation. The advent of next-generation sequencing (NGS) coupled with the heritability of SNPs make them ideal markers for genetic analysis of human, animal, and microbial data. SNPs have also been extensively used in crop genetics for association mapping, quantitative trait loci (QTL) analysis, analysis of genetic diversity, and phylogenetic analysis. This review focuses on the use of pangenomes for SNP discovery. It highlights the advantages of using a pangenome rather than a single reference for this purpose. This review also demonstrates how extra information not captured in a single reference alone can be used to provide additional support for linking genotypic data to phenotypic data.

Short Read Alignment Using SOAP2.

Next-generation sequencing (NGS) technologies have rapidly evolved in the last 5 years, leading to the generation of millions of short reads in a single run. Consequently, various sequence alignment algorithms have been developed to compare these reads to an appropriate reference in order to perform important downstream analysis. SOAP2 from the SOAP series is one of the most commonly used alignment programs to handle NGS data, and it efficiently does so using low computer memory usage and fast alignment speed. This chapter describes the protocol used to align short reads to a reference genome using SOAP2, and highlights the significance of using the in-built command-line options to tune the behavior of the algorithm according to the inputs and the desired results.

An efficient approach to BAC based assembly of complex genomes.

BACKGROUND: There has been an exponential growth in the number of genome sequencing projects since the introduction of next generation DNA sequencing technologies. Genome projects have increasingly involved assembly of whole genome data which produces inferior assemblies compared to traditional Sanger sequencing of genomic fragments cloned into bacterial artificial chromosomes (BACs). While whole genome shotgun sequencing using next generation sequencing (NGS) is relatively fast and inexpensive, this method is extremely challenging for highly complex genomes, where polyploidy or high repeat content confounds accurate assembly, or where a highly accurate 'gold' reference is required. Several attempts have been made to improve genome sequencing approaches by incorporating NGS methods, to variable success. RESULTS: We present the application of a novel BAC sequencing approach which combines indexed pools of BACs, Illumina paired read sequencing, a sequence assembler specifically designed for complex BAC assembly, and a custom bioinformatics pipeline. We demonstrate this method by sequencing and assembling BAC cloned fragments from bread wheat and sugarcane genomes. CONCLUSIONS: We demonstrate that our assembly approach is accurate, robust, cost effective and scalable, with applications for complete genome sequencing in large and complex genomes.