The Arabidopsis thaliana onset of leaf death 12 mutation in the lectin receptor kinase P2K2 results in an autoimmune phenotype

BACKGROUND

Plant immunity relies on the perception of immunogenic signals by cell-surface and intracellular receptors and subsequent activation of defense responses like programmed cell death. Under certain circumstances, the fine-tuned innate immune system of plants results in the activation of autoimmune responses that cause constitutive defense responses and spontaneous cell death in the absence of pathogens.

RESULTS

Here, we characterized the onset of leaf death 12 (old12) mutant that was identified in the Arabidopsis accession Landsberg erecta. The old12 mutant is characterized by a growth defect, spontaneous cell death, plant-defense gene activation, and early senescence. In addition, the old12 phenotype is temperature reversible, thereby exhibiting all characteristics of an autoimmune mutant. Mapping the mutated locus revealed that the old12 phenotype is caused by a mutation in the Lectin Receptor Kinase P2-TYPE PURINERGIC RECEPTOR 2 (P2K2) gene. Interestingly, the P2K2 allele from Landsberg erecta is conserved among Brassicaceae. P2K2 has been implicated in pathogen tolerance and sensing extracellular ATP. The constitutive activation of defense responses in old12 results in improved resistance against Pseudomonas syringae pv. tomato DC3000.

CONCLUSION

We demonstrate that old12 is an auto-immune mutant and that allelic variation of P2K2 contributes to diversity in Arabidopsis immune responses.

De Novo Transcriptome Analysis of Durum Wheat Flag Leaves Provides New Insights Into the Regulatory Response to Elevated CO2 and High Temperature

Global warming is becoming a significant problem for food security, particularly in the Mediterranean basin. The use of molecular techniques to study gene-level responses to environmental changes in non-model organisms is increasing and may help to improve the mechanistic understanding of durum wheat response to elevated CO2 and high temperature. With this purpose, we performed transcriptome RNA sequencing (RNA-Seq) analyses combined with physiological and biochemical studies in the flag leaf of plants grown in field chambers at ear emergence. Enhanced photosynthesis by elevated CO2 was accompanied by an increase in biomass and starch and fructan content, and a decrease in N compounds, as chlorophyll, soluble proteins, and Rubisco content, in association with a decline of nitrate reductase and initial and total Rubisco activities. While high temperature led to a decline of chlorophyll, Rubisco activity, and protein content, the glucose content increased and starch decreased. Furthermore, elevated CO2 induced several genes involved in mitochondrial electron transport, a few genes for photosynthesis and fructan synthesis, and most of the genes involved in secondary metabolism and gibberellin and jasmonate metabolism, whereas those related to light harvesting, N assimilation, and other hormone pathways were repressed. High temperature repressed genes for C, energy, N, lipid, secondary, and hormone metabolisms. Under the combined increases in atmospheric CO2 and temperature, the transcript profile resembled that previously reported for high temperature, although elevated CO2 partly alleviated the downregulation of primary and secondary metabolism genes. The results suggest that there was a reprogramming of primary and secondary metabolism under the future climatic scenario, leading to coordinated regulation of C-N metabolism towards C-rich metabolites at elevated CO2 and a shift away from C-rich secondary metabolites at high temperature. Several candidate genes differentially expressed were identified, including protein kinases, receptor kinases, and transcription factors.

MapMan4: A Refined Protein Classification and Annotation Framework Applicable to Multi-Omics Data Analysis

Genome sequences from over 200 plant species have already been published, with this number expected to increase rapidly due to advances in sequencing technologies. Once a new genome has been assembled and the genes identified, the functional annotation of their putative translational products, proteins, using ontologies is of key importance as it places the sequencing data in a biological context. Furthermore, to keep pace with rapid production of genome sequences, this functional annotation process must be fully automated. Here we present a redesigned and significantly enhanced MapMan4 framework, together with a revised version of the associated online Mercator annotation tool. Compared with the original MapMan, the new ontology has been expanded almost threefold and enforces stricter assignment rules. This framework was then incorporated into Mercator4, which has been upgraded to reflect current knowledge across the land plant group, providing protein annotations for all embryophytes with a comparably high quality. The annotation process has been optimized to allow a plant genome to be annotated in a matter of minutes. The output results continue to be compatible with the established MapMan desktop application.

Computational aspects underlying genome to phenome analysis in plants

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features.

Is there foul play in the leaf pocket? The metagenome of floating fern Azolla reveals endophytes that do not fix N2 but may denitrify

Dinitrogen fixation by Nostoc azollae residing in specialized leaf pockets supports prolific growth of the floating fern Azolla filiculoides. To evaluate contributions by further microorganisms, the A. filiculoides microbiome and nitrogen metabolism in bacteria persistently associated with Azolla ferns were characterized. A metagenomic approach was taken complemented by detection of N₂ O released and nitrogen isotope determinations of fern biomass. Ribosomal RNA genes in sequenced DNA of natural ferns, their enriched leaf pockets and water filtrate from the surrounding ditch established that bacteria of A. filiculoides differed entirely from surrounding water and revealed species of the order Rhizobiales. Analyses of seven cultivated Azolla species confirmed persistent association with Rhizobiales. Two distinct nearly full-length Rhizobiales genomes were identified in leaf-pocket-enriched samples from ditch grown A. filiculoides. Their annotation revealed genes for denitrification but not N₂ -fixation. ¹⁵ N₂ incorporation was active in ferns with N. azollae but not in ferns without. N₂ O was not detectably released from surface-sterilized ferns with the Rhizobiales. N₂ -fixing N. azollae, we conclude, dominated the microbiome of Azolla ferns. The persistent but less abundant heterotrophic Rhizobiales bacteria possibly contributed to lowering O₂ levels in leaf pockets but did not release detectable amounts of the strong greenhouse gas N₂ O.

Is there foul play in the leaf pocket? The metagenome of floating fern Azolla reveals endophytes that do not fix N2 but may denitrify

Dinitrogen fixation by Nostoc azollae residing in specialized leaf pockets supports prolific growth of the floating fern Azolla filiculoides. To evaluate contributions by further microorganisms, the A. filiculoides microbiome and nitrogen metabolism in bacteria persistently associated with Azolla ferns were characterized. A metagenomic approach was taken complemented by detection of N₂ O released and nitrogen isotope determinations of fern biomass. Ribosomal RNA genes in sequenced DNA of natural ferns, their enriched leaf pockets and water filtrate from the surrounding ditch established that bacteria of A. filiculoides differed entirely from surrounding water and revealed species of the order Rhizobiales. Analyses of seven cultivated Azolla species confirmed persistent association with Rhizobiales. Two distinct nearly full-length Rhizobiales genomes were identified in leaf-pocket-enriched samples from ditch grown A. filiculoides. Their annotation revealed genes for denitrification but not N₂ -fixation. ¹⁵ N₂ incorporation was active in ferns with N. azollae but not in ferns without. N₂ O was not detectably released from surface-sterilized ferns with the Rhizobiales. N₂ -fixing N. azollae, we conclude, dominated the microbiome of Azolla ferns. The persistent but less abundant heterotrophic Rhizobiales bacteria possibly contributed to lowering O₂ levels in leaf pockets but did not release detectable amounts of the strong greenhouse gas N₂ O.

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

Updates in nanopore technology have made it possible to obtain gigabases of sequence data. Prior to this, nanopore sequencing technology was mainly used to analyze microbial samples. Here, we describe the generation of a comprehensive nanopore sequencing data set with a median read length of 11,979 bp for a self-compatible accession of the wild tomato species Solanum pennellii We describe the assembly of its genome to a contig N50 of 2.5 MB. The assembly pipeline comprised initial read correction with Canu and assembly with SMARTdenovo. The resulting raw nanopore-based de novo genome is structurally highly similar to that of the reference S. pennellii LA716 accession but has a high error rate and was rich in homopolymer deletions. After polishing the assembly with Illumina reads, we obtained an error rate of <0.02% when assessed versus the same Illumina data. We obtained a gene completeness of 96.53%, slightly surpassing that of the reference S. pennellii Taken together, our data indicate that such long read sequencing data can be used to affordably sequence and assemble gigabase-sized plant genomes.

Tomato facultative parthenocarpy results from SlAGAMOUS-LIKE 6 loss of function

The extreme sensitivity of the microsporogenesis process to moderately high or low temperatures is a major hindrance for tomato (Solanum lycopersicum) sexual reproduction and hence year-round cropping. Consequently, breeding for parthenocarpy, namely, fertilization-independent fruit set, is considered a valuable goal especially for maintaining sustainable agriculture in the face of global warming. A mutant capable of setting high-quality seedless (parthenocarpic) fruit was found following a screen of EMS-mutagenized tomato population for yielding under heat stress. Next-generation sequencing followed by marker-assisted mapping and CRISPR/Cas9 gene knockout confirmed that a mutation in SlAGAMOUS-LIKE 6 (SlAGL6) was responsible for the parthenocarpic phenotype. The mutant is capable of fruit production under heat stress conditions that severely hamper fertilization-dependent fruit set. Different from other tomato recessive monogenic mutants for parthenocarpy, Slagl6 mutations impose no homeotic changes, the seedless fruits are of normal weight and shape, pollen viability is unaffected, and sexual reproduction capacity is maintained, thus making Slagl6 an attractive gene for facultative parthenocarpy. The characteristics of the analysed mutant combined with the gene's mode of expression imply SlAGL6 as a key regulator of the transition between the state of 'ovary arrest' imposed towards anthesis and the fertilization-triggered fruit set.

Trimmomatic: a flexible trimmer for Illumina sequence data

MOTIVATION

Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.

RESULTS

The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.

AVAILABILITY AND IMPLEMENTATION

Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic

CONTACT

usadel@bio1.rwth-aachen.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Trimmomatic: a flexible trimmer for Illumina sequence data

Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.

Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested.

Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic

Contact:usadel@bio1.rwth-aachen.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Evolution of a complex locus for terpene biosynthesis in solanum

Functional gene clusters, containing two or more genes encoding different enzymes for the same pathway, are sometimes observed in plant genomes, most often when the genes specify the synthesis of specialized defensive metabolites. Here, we show that a cluster of genes in tomato (Solanum lycopersicum; Solanaceae) contains genes for terpene synthases (TPSs) that specify the synthesis of monoterpenes and diterpenes from cis-prenyl diphosphates, substrates that are synthesized by enzymes encoded by cis-prenyl transferase (CPT) genes also located within the same cluster. The monoterpene synthase genes in the cluster likely evolved from a diterpene synthase gene in the cluster by duplication and divergence. In the orthologous cluster in Solanum habrochaites, a new sesquiterpene synthase gene was created by a duplication event of a monoterpene synthase followed by a localized gene conversion event directed by a diterpene synthase gene. The TPS genes in the Solanum cluster encoding cis-prenyl diphosphate-utilizing enzymes are closely related to a tobacco (Nicotiana tabacum; Solanaceae) diterpene synthase encoding Z-abienol synthase (Nt-ABS). Nt-ABS uses the substrate copal-8-ol diphosphate, which is made from the all-trans geranylgeranyl diphosphate by copal-8-ol diphosphate synthase (Nt-CPS2). The Solanum gene cluster also contains an ortholog of Nt-CPS2, but it appears to encode a nonfunctional protein. Thus, the Solanum functional gene cluster evolved by duplication and divergence of TPS genes, together with alterations in substrate specificity to utilize cis-prenyl diphosphates and through the acquisition of CPT genes.

RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics

Recent rapid advances in next generation RNA sequencing (RNA-Seq)-based provide researchers with unprecedentedly large data sets and open new perspectives in transcriptomics. Furthermore, RNA-Seq-based transcript profiling can be applied to non-model and newly discovered organisms because it does not require a predefined measuring platform (like e.g. microarrays). However, these novel technologies pose new challenges: the raw data need to be rigorously quality checked and filtered prior to analysis, and proper statistical methods have to be applied to extract biologically relevant information. Given the sheer volume of data, this is no trivial task and requires a combination of considerable technical resources along with bioinformatics expertise. To aid the individual researcher, we have developed RobiNA as an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input. It supports quality checking, flexible filtering and statistical analysis of differential gene expression based on state-of-the art biostatistical methods developed in the R/Bioconductor projects. In-line help and a step-by-step manual guide users through the analysis. Installer packages for Mac OS X, Windows and Linux are available under the LGPL licence from http://mapman.gabipd.org/web/guest/robin.

Algorithm-driven artifacts in median polish summarization of microarray data

BACKGROUND

High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification.

RESULTS

In the present paper we benchmark the three most used normalization procedures (MAS5, RMA and GCRMA) in the context of inter-array correlation analysis, confirming and extending the finding that RMA and GCRMA consistently overestimate sample similarity upon normalization. We determine that median polish summarization is responsible for generating a large proportion of these over-similarity artifacts. Furthermore, we show that most affected probesets show also internal signal disagreement, and tend to be composed by individual probes hitting different gene transcripts. We finally provide a correction to the RMA/GCRMA summarization procedure that massively reduces inter-array correlation artifacts, without affecting the detection of differentially expressed genes.

CONCLUSIONS

We propose tRMA as a modification of RMA to normalize microarray experiments for correlation-based analysis.