Multiple toxins and a protease contribute to the aphid-killing ability of Pseudomonas fluorescens PpR24.

Aphids are globally important pests causing damage to a broad range of crops. Due to insecticide resistance, there is an urgent need to develop alternative control strategies. In our previous work, we found Pseudomonas fluorescens PpR24 can orally infect and kill the insecticide-resistant green-peach aphid (Myzus persicae). However, the genetic basis of the insecticidal capability of PpR24 remains unclear. Genome sequencing of PpR24 confirmed the presence of various insecticidal toxins such as Tc (toxin complexes), Rhs (rearrangement hotspot) elements, and other insect-killing proteases. Upon aphids infection with PpR24, RNA-Seq analysis revealed 193 aphid genes were differentially expressed with down-regulation of 16 detoxification genes. In addition, 1325 PpR24 genes (542 were upregulated and 783 downregulated) were subject to differential expression, including genes responsible for secondary metabolite biosynthesis, the iron-restriction response, oxidative stress resistance, and virulence factors. Single and double deletion of candidate virulence genes encoding a secreted protease (AprX) and four toxin components (two TcA-like; one TcB-like; one TcC-like insecticidal toxins) showed that all five genes contribute significantly to aphid killing, particularly AprX. This comprehensive host-pathogen transcriptomic analysis provides novel insight into the molecular basis of bacteria-mediated aphid mortality and the potential of PpR24 as an effective biocontrol agent.

The complete genome assemblies of 19 insect pests of worldwide importance to agriculture.

There are many insect pests worldwide that damage agricultural crop and reduce yield either by direct feeding or by the transmission of plant diseases. To date, control of pest insects has been achieved largely by applying synthetic insecticides. However, insecticide use can be seriously impacted by legislation that limits their use or by the evolution of resistance in the target pest. Thus, there is a move towards less use of insecticides and increased adoption of integrated pest management strategies using a wide range of non-chemical and chemical control methods. For good pest control there is a need to understand the mode of action and selectivity of insecticides, the life cycles of the pests and their biology and behaviours, all of which can benefit from good quality genome data. Here we present the complete assembled (chromosome level) genomes (incl. mtDNA) of 19 insect pests, Agriotes lineatus (click beetle/wireworm), Aphis gossypii (melon/cotton aphid), Bemisia tabaci (cotton whitefly), Brassicogethes aeneus (pollen beetle), Ceutorhynchus obstrictus (seedpod weevil), Chilo suppressalis (striped rice stem borer), Chrysodeixis includens (soybean looper), Diabrotica balteata (cucumber beetle), Diatraea saccharalis (sugar cane borer), Nezara viridula (green stink bug), Nilaparvata lugens (brown plant hopper), Phaedon cochleariae (mustard beetle), Phyllotreta striolata (striped flea beetle), Psylliodes chrysocephala (cabbage stem flea beetle), Spodoptera exigua (beet army worm), Spodoptera littoralis (cotton leaf worm), Diabrotica virgifera (western corn root worm), Euschistus heros (brown stink bug) and Phyllotreta cruciferae (crucifer flea beetle). For the first 15 of these we also present the annotation of genes encoding potential xenobiotic detoxification enzymes. This public resource will aid in the elucidation and monitoring of resistance mechanisms, the development of highly selective chemistry and potential techniques to disrupt behaviour in a way that limits the effect of the pests.

Proanthocyanidin biosynthesis in the developing wheat seed coat investigated by chemical and RNA-Seq analysis.

The composition of proanthocyanidins in the testa (seed coat) of bread wheat was analyzed by thiolysis of PA oligomers from developing grain and found to consist of (+)-catechin monomers, with a small amount of (+)-gallocatechin. The average chain length of soluble PA stayed relatively constant between 10 and 20 days post-anthesis, whereas that of unextractable PA increased over the same period, suggesting that increases in chain length might account for the insolubility of PAs from mature wheat grain. We carried out RNA-Seq followed by differential expression analysis from dissected tissues of developing grain from red- and white-grained near-isogenic lines differing in the presence of an active R gene that encodes a MYB transcription factor involved in control of PA biosynthesis. In addition to genes already identified encoding chalcone synthase, chalcone isomerase, flavanone 3-hydroxylase, and dihydroxyflavonoid 4-reductase, we showed that wheat genes encoding phenylalanine ammonia lyase, flavonoid 3',5'-hydroxylase, leucoanthocyanidin reductase, and a glutathione S-transferase (the orthologue of maize Bronze-2) were more highly expressed in the red NIL. We also identified candidate orthologues of other catalytic and regulatory components of flavonoid biosynthesis in wheat.

Novel molecules and target genes for vegetative heat tolerance in wheat.

To prevent yield losses caused by climate change, it is important to identify naturally tolerant genotypes with traits and related pathways that can be targeted for crop improvement. Here we report on the characterization of contrasting vegetative heat tolerance in two UK bread wheat varieties. Under chronic heat stress, the heat-tolerant cultivar Cadenza produced an excessive number of tillers which translated into more spikes and higher grain yield compared to heat-sensitive Paragon. RNAseq and metabolomics analyses revealed that over 5000 genotype-specific genes were differentially expressed, including photosynthesis-related genes, which might explain the observed ability of Cadenza to maintain photosynthetic rate under heat stress. Around 400 genes showed a similar heat-response in both genotypes. Only 71 genes showed a genotype × temperature interaction. As well as known heat-responsive genes such as heat shock proteins (HSPs), several genes that have not been previously linked to the heat response, particularly in wheat, have been identified, including dehydrins, ankyrin-repeat protein-encoding genes, and lipases. Contrary to primary metabolites, secondary metabolites showed a highly differentiated heat response and genotypic differences. These included benzoxazinoid (DIBOA, DIMBOA), and phenylpropanoids and flavonoids with known radical scavenging capacity, which was assessed via the DPPH assay. The most highly heat-induced metabolite was (glycosylated) propanediol, which is widely used in industry as an anti-freeze. To our knowledge, this is the first report on its response to stress in plants. The identified metabolites and candidate genes provide novel targets for the development of heat-tolerant wheat.

Gene-based mapping of trehalose biosynthetic pathway genes reveals association with source- and sink-related yield traits in a spring wheat panel.

Trehalose 6-phosphate (T6P) signalling regulates carbon use and allocation and is a target to improve crop yields. However, the specific contributions of trehalose phosphate synthase (TPS) and trehalose phosphate phosphatase (TPP) genes to source- and sink-related traits remain largely unknown. We used enrichment capture sequencing on TPS and TPP genes to estimate and partition the genetic variation of yield-related traits in a spring wheat (Triticum aestivum) breeding panel specifically built to capture the diversity across the 75,000 CIMMYT wheat cultivar collection. Twelve phenotypes were correlated to variation in TPS and TPP genes including plant height and biomass (source), spikelets per spike, spike growth and grain filling traits (sink) which showed indications of both positive and negative gene selection. Individual genes explained proportions of heritability for biomass and grain-related traits. Three TPS1 homologues were particularly significant for trait variation. Epistatic interactions were found within and between the TPS and TPP gene families for both plant height and grain-related traits. Gene-based prediction improved predictive ability for grain weight when gene effects were combined with the whole-genome markers. Our study has generated a wealth of information on natural variation of TPS and TPP genes related to yield potential which confirms the role for T6P in resource allocation and in affecting traits such as grain number and size confirming other studies which now opens up the possibility of harnessing natural genetic variation more widely to better understand the contribution of native genes to yield traits for incorporation into breeding programmes.

KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species.

The generation of new ideas and scientific hypotheses is often the result of extensive literature and database searches, but, with the growing wealth of public and private knowledge, the process of searching diverse and interconnected data to generate new insights into genes, gene networks, traits and diseases is becoming both more complex and more time-consuming. To guide this technically challenging data integration task and to make gene discovery and hypotheses generation easier for researchers, we have developed a comprehensive software package called KnetMiner which is open-source and containerized for easy use. KnetMiner is an integrated, intelligent, interactive gene and gene network discovery platform that supports scientists explore and understand the biological stories of complex traits and diseases across species. It features fast algorithms for generating rich interactive gene networks and prioritizing candidate genes based on knowledge mining approaches. KnetMiner is used in many plant science institutions and has been adopted by several plant breeding organizations to accelerate gene discovery. The software is generic and customizable and can therefore be readily applied to new species and data types; for example, it has been applied to pest insects and fungal pathogens; and most recently repurposed to support COVID-19 research. Here, we give an overview of the main approaches behind KnetMiner and we report plant-centric case studies for identifying genes, gene networks and trait relationships in Triticum aestivum (bread wheat), as well as, an evidence-based approach to rank candidate genes under a large Arabidopsis thaliana QTL. KnetMiner is available at: https://knetminer.org.

The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat.

Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.

A roadmap for gene functional characterisation in crops with large genomes: Lessons from polyploid wheat.

Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite their importance, a lack of genomic information and resources has hindered the functional characterisation of genes in major crops. The recent release of high-quality reference sequences for these crops underpins a suite of genetic and genomic resources that support basic research and breeding. For wheat, these include gene model annotations, expression atlases and gene networks that provide information about putative function. Sequenced mutant populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources. This review provides a helpful guide for plant scientists, especially those expanding into crop research, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of crops of vital importance for food and nutrition security.

Epigenetic patterns within the haplotype phased fig (Ficus carica L.) genome.

Due to DNA heterozygosity and repeat content, assembly of non-model plant genomes is challenging. Herein, we report a high-quality genome reference of one of the oldest known domesticated species, fig (Ficus carica L.), using Pacific Biosciences single-molecule, real-time sequencing. The fig genome is ~333 Mbp in size, of which 80% has been anchored to 13 chromosomes. Genome-wide analysis of N6 -methyladenine and N4 -methylcytosine revealed high methylation levels in both genes and transposable elements, and a prevalence of methylated over non-methylated genes. Furthermore, the characterization of N6 -methyladenine sites led to the identification of ANHGA, a species-specific motif, which is prevalent for both genes and transposable elements. Finally, exploiting the contiguity of the 13 pseudomolecules, we identified 13 putative centromeric regions. The high-quality reference genome and the characterization of methylation profiles, provides an important resource for both fig breeding and for fundamental research into the relationship between epigenetic changes and phenotype, using fig as a model species.

PHI-base: the pathogen-host interactions database.

The pathogen-host interactions database (PHI-base) is available at www.phi-base.org. PHI-base contains expertly curated molecular and biological information on genes proven to affect the outcome of pathogen-host interactions reported in peer reviewed research articles. PHI-base also curates literature describing specific gene alterations that did not affect the disease interaction phenotype, in order to provide complete datasets for comparative purposes. Viruses are not included, due to their extensive coverage in other databases. In this article, we describe the increased data content of PHI-base, plus new database features and further integration with complementary databases. The release of PHI-base version 4.8 (September 2019) contains 3454 manually curated references, and provides information on 6780 genes from 268 pathogens, tested on 210 hosts in 13,801 interactions. Prokaryotic and eukaryotic pathogens are represented in almost equal numbers. Host species consist of approximately 60% plants (split 50:50 between cereal and non-cereal plants), and 40% other species of medical and/or environmental importance. The information available on pathogen effectors has risen by more than a third, and the entries for pathogens that infect crop species of global importance has dramatically increased in this release. We also briefly describe the future direction of the PHI-base project, and some existing problems with the PHI-base curation process.

A Co-Expression Network in Hexaploid Wheat Reveals Mostly Balanced Expression and Lack of Significant Gene Loss of Homeologous Meiotic Genes Upon Polyploidization.

Polyploidization has played an important role in plant evolution. However, upon polyploidization, the process of meiosis must adapt to ensure the proper segregation of increased numbers of chromosomes to produce balanced gametes. It has been suggested that meiotic gene (MG) duplicates return to a single copy following whole genome duplication to stabilize the polyploid genome. Therefore, upon the polyploidization of wheat, a hexaploid species with three related (homeologous) genomes, the stabilization process may have involved rapid changes in content and expression of MGs on homeologous chromosomes (homeologs). To examine this hypothesis, sets of candidate MGs were identified in wheat using co-expression network analysis and orthology informed approaches. In total, 130 RNA-Seq samples from a range of tissues including wheat meiotic anthers were used to define co-expressed modules of genes. Three modules were significantly correlated with meiotic tissue samples but not with other tissue types. These modules were enriched for GO terms related to cell cycle, DNA replication, and chromatin modification and contained orthologs of known MGs. Overall, 74.4% of genes within these meiosis-related modules had three homeologous copies which was similar to other tissue-related modules. Amongst wheat MGs identified by orthology, rather than co-expression, the majority (93.7%) were either retained in hexaploid wheat at the same number of copies (78.4%) or increased in copy number (15.3%) compared to ancestral wheat species. Furthermore, genes within meiosis-related modules showed more balanced expression levels between homeologs than genes in non-meiosis-related modules. Taken together, our results do not support extensive gene loss nor changes in homeolog expression of MGs upon wheat polyploidization. The construction of the MG co-expression network allowed identification of hub genes and provided key targets for future studies.

Basic LEUCINE ZIPPER TRANSCRIPTION FACTOR67 Transactivates DELAY OF GERMINATION1 to Establish Primary Seed Dormancy in Arabidopsis.

Seed dormancy governs the timing of germination, one of the most important developmental transitions in a plant's life cycle. The DELAY OF GERMINATION1 (DOG1) gene is a key regulator of seed dormancy and a major quantitative trait locus in Arabidopsis (Arabidopsis thaliana). DOG1 expression is under tight developmental and environmental regulation, but the transcription factors involved are not known. Here we show that basic LEUCINE ZIPPER TRANSCRIPTION FACTOR67 (bZIP67) acts downstream of the central regulator of seed development, LEAFY COTYLEDON1, to transactivate DOG1 during maturation and help to establish primary dormancy. We show that bZIP67 overexpression enhances dormancy and that bZIP67 protein (but not transcript) abundance is increased in seeds matured in cool conditions, providing a mechanism to explain how temperature regulates DOG1 expression. We also show that natural allelic variation in the DOG1 promoter affects bZIP67-dependent transactivation, providing a mechanism to explain ecotypic differences in seed dormancy that are controlled by the DOG1 locus.

Natural variation in acyl editing is a determinant of seed storage oil composition.

Seeds exhibit wide variation in the fatty acid composition of their storage oil. However, the genetic basis of this variation is only partially understood. Here we have used a multi-parent advanced generation inter-cross (MAGIC) population to study the genetic control of fatty acid chain length in Arabidopsis thaliana seed oil. We mapped four quantitative trait loci (QTL) for the quantity of the major very long chain fatty acid species 11-eicosenoic acid (20:1), using multiple QTL modelling. Surprisingly, the main-effect QTL does not coincide with FATTY ACID ELONGASE 1 and a parallel genome wide association study suggested that LYSOPHOSPHATIDYLCHOLINE ACYLTRANSFERASE 2 (LPCAT2) is a candidate for this QTL. Regression analysis also suggested that LPCAT2 expression and 20:1 content in seeds of the 19 MAGIC founder accessions are related. LPCAT is a key component of the Lands cycle; an acyl editing pathway that enables acyl-exchange between the acyl-Coenzyme A and phosphatidylcholine precursor pools used for microsomal fatty acid elongation and desaturation, respectively. We Mendelianised the main-effect QTL using biparental chromosome segment substitution lines and carried out complementation tests to show that a single cis-acting polymorphism in the LPCAT2 promoter causes the variation in seed 20:1 content, by altering the LPCAT2 expression level and total LPCAT activity in developing siliques. Our work establishes that oilseed species exhibit natural variation in the enzymic capacity for acyl editing and this contributes to the genetic control of storage oil composition.

Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach.

The speed and accuracy of new scientific discoveries - be it by humans or artificial intelligence - depends on the quality of the underlying data and on the technology to connect, search and share the data efficiently. In recent years, we have seen the rise of graph databases and semi-formal data models such as knowledge graphs to facilitate software approaches to scientific discovery. These approaches extend work based on formalised models, such as the Semantic Web. In this paper, we present our developments to connect, search and share data about genome-scale knowledge networks (GSKN). We have developed a simple application ontology based on OWL/RDF with mappings to standard schemas. We are employing the ontology to power data access services like resolvable URIs, SPARQL endpoints, JSON-LD web APIs and Neo4j-based knowledge graphs. We demonstrate how the proposed ontology and graph databases considerably improve search and access to interoperable and reusable biological knowledge (i.e. the FAIRness data principles).

Transcriptome changes induced by arbuscular mycorrhizal fungi in sunflower (Helianthus annuus L.) roots.

Arbuscular mycorrhizal (AM) fungi are essential elements of soil fertility, plant nutrition and productivity, facilitating soil mineral nutrient uptake. Helianthus annuus is a non-model, widely cultivated species. Here we used an RNA-seq approach for evaluating gene expression variation at early and late stages of mycorrhizal establishment in sunflower roots colonized by the arbuscular fungus Rhizoglomus irregulare. mRNA was isolated from roots of plantlets at 4 and 16 days after inoculation with the fungus. cDNA libraries were built and sequenced with Illumina technology. Differential expression analysis was performed between control and inoculated plants. Overall 726 differentially expressed genes (DEGs) between inoculated and control plants were retrieved. The number of up-regulated DEGs greatly exceeded the number of down-regulated DEGs and this difference increased in later stages of colonization. Several DEGs were specifically involved in known mycorrhizal processes, such as membrane transport, cell wall shaping, and other. We also found previously unidentified mycorrhizal-induced transcripts. The most important DEGs were carefully described in order to hypothesize their roles in AM symbiosis. Our data add a valuable contribution for deciphering biological processes related to beneficial fungi and plant symbiosis, adding an Asteraceae, non-model species for future comparative functional genomics studies.

KnetMaps: a BioJS component to visualize biological knowledge networks.

KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.

Spatiotemporal expression patterns of wheat amino acid transporters reveal their putative roles in nitrogen transport and responses to abiotic stress.

Amino acid transporters have roles in amino acid uptake from soil, long-distance transport, remobilization from vegetative tissues and accumulation in grain. Critically, the majority of wheat grain nitrogen is derived from amino acids remobilized from vegetative organs. However, no systematic analysis of wheat AAT genes has been reported to date. Here, 283 full length wheat AAT genes representing 100 distinct groups of homeologs were identified and curated by selectively consolidating IWGSC CSSv2 and TGACv1 Triticum aestivum genome assemblies and reassembling or mapping of IWGSC CSS chromosome sorted reads to fill any gaps. Gene expression profiling was performed using public RNA-seq data from root, leaf, stem, spike, grain and grain cells (transfer cell (TC), aleurone cell (AL), and starchy endosperm (SE)). AATs highly expressed in roots are good candidates for amino acid uptake from soil whilst AATs highly expressed in senescing leaves and stems may be involved in translocation to grain. AATs in TC (TaAAP2 and TaAAP19) and SE (TaAAP13) may play important roles in determining grain protein content and grain yield. The expression levels of AAT homeologs showed unequal contributions in response to abiotic stresses and development, which may aid wheat adaptation to a wide range of environments.

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

Genome Wide Analysis of Fatty Acid Desaturation and Its Response to Temperature.

Plants modify the polyunsaturated fatty acid content of their membrane and storage lipids in order to adapt to changes in temperature. In developing seeds, this response is largely controlled by the activities of the microsomal ω-6 and ω-3 fatty acid desaturases, FAD2 and FAD3. Although temperature regulation of desaturation has been studied at the molecular and biochemical levels, the genetic control of this trait is poorly understood. Here, we have characterized the response of Arabidopsis (Arabidopsis thaliana) seed lipids to variation in ambient temperature and found that heat inhibits both ω-6 and ω-3 desaturation in phosphatidylcholine, leading to a proportional change in triacylglycerol composition. Analysis of the 19 parental accessions of the multiparent advanced generation intercross (MAGIC) population showed that significant natural variation exists in the temperature responsiveness of ω-6 desaturation. A combination of quantitative trait locus (QTL) analysis and genome-wide association studies (GWAS) using the MAGIC population suggests that ω-6 desaturation is largely controlled by cis-acting sequence variants in the FAD2 5' untranslated region intron that determine the expression level of the gene. However, the temperature responsiveness of ω-6 desaturation is controlled by a separate QTL on chromosome 2. The identity of this locus is unknown, but genome-wide association studies identified potentially causal sequence variants within ∼40 genes in an ∼450-kb region of the QTL.