Nicolas Delhomme

The Norway spruce genome sequence and conifer genome evolution

Conifers have dominated forests for more than 200 million years and are of huge ecological and economic importance. Here we present the draft assembly of the 20-gigabase genome of Norway spruce (Picea abies), the first available for any gymnosperm. The number of well-supported genes (28,354) is similar to the >100 times smaller genome of Arabidopsis thaliana, and there is no evidence of a recent whole-genome duplication in the gymnosperm lineage. Instead, the large genome size seems to result from the slow and steady accumulation of a diverse set of long-terminal repeat transposable elements, possibly owing to the lack of an efficient elimination mechanism. Comparative sequencing of Pinus sylvestris, Abies sibirica, Juniperus communis, Taxus baccata and Gnetum gnemon reveals that the transposable element diversity is shared among extant conifers. Expression of 24-nucleotide small RNAs, previously implicated in transposable element silencing, is tissue-specific and much lower than in other plants. We further identify numerous long (>10,000 base pairs) introns, gene-like fragments, uncharacterized long non-coding RNAs and short RNAs. This opens up new genomic avenues for conifer forestry and breeding.

The Plant Genome Integrative Explorer Resource: PlantGenIE.org

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight.

AspWood : High-Spatial-Resolution Transcriptome Profiles Reveal Uncharacterized Modularity of Wood Formation in Populus tremula

The AspWood large-scale data set comprises high-spatial-resolution RNA-seq transcriptome profiles collected across the phloem-cambium-xylem developmental zone of aspen trees. Trees represent the largest terrestrial carbon sink and a renewable source of ligno-cellulose. There is significant scope for yield and quality improvement in these largely undomesticated species, and efforts to engineer elite varieties will benefit from improved understanding of the transcriptional network underlying cambial growth and wood formation. We generated high-spatial-resolution RNA sequencing data spanning the secondary phloem, vascular cambium, and wood-forming tissues of Populus tremula. The transcriptome comprised 28,294 expressed, annotated genes, 78 novel protein-coding genes, and 567 putative long intergenic noncoding RNAs. Most paralogs originating from the Salicaceae whole-genome duplication had diverged expression, with the exception of those highly expressed during secondary cell wall deposition. Coexpression network analyses revealed that regulation of the transcriptome underlying cambial growth and wood formation comprises numerous modules forming a continuum of active processes across the tissues. A comparative analysis revealed that a majority of these modules are conserved in Picea abies. The high spatial resolution of our data enabled identification of novel roles for characterized genes involved in xylan and cellulose biosynthesis, regulators of xylem vessel and fiber differentiation and lignification. An associated web resource (AspWood, http://aspwood.popgenie.org) provides interactive tools for exploring the expression profiles and coexpression network.

Populus tremula (European aspen) shows no evidence of sexual dimorphism

BackgroundEvolutionary theory suggests that males and females may evolve sexually dimorphic phenotypic and biochemical traits concordant with each sex having different optimal strategies of resource investment to maximise reproductive success and fitness. Such sexual dimorphism would result in sex biased gene expression patterns in non-floral organs for autosomal genes associated with the control and development of such phenotypic traits.ResultsWe examined morphological, biochemical and herbivory traits to test for sexually dimorphic resource allocation strategies within collections of sexually mature and immature Populus tremula (European aspen) trees. In addition we profiled gene expression in mature leaves of sexually mature wild trees using whole-genome oligonucleotide microarrays and RNA-Sequencing.ConclusionsWe found no evidence of sexual dimorphism or differential resource investment strategies between males and females in either sexually immature or mature trees. Similarly, single-gene differential expression and machine learning approaches revealed no evidence of large-scale sex biased gene expression. However, two significantly differentially expressed genes were identified from the RNA-Seq data, one of which is a robust diagnostic marker of sex in P. tremula.

Serendipitous meta-transcriptomics: the fungal community of Norway Spruce (Picea abies)

After performing de novo transcript assembly of >1 billion RNA-Sequencing reads obtained from 22 samples of different Norway spruce (Picea abies) tissues that were not surface sterilized, we found that assembled sequences captured a mix of plant, lichen, and fungal transcripts. The latter were likely expressed by endophytic and epiphytic symbionts, indicating that these organisms were present, alive, and metabolically active. Here, we show that these serendipitously sequenced transcripts need not be considered merely as contamination, as is common, but that they provide insight into the plant’s phyllosphere. Notably, we could classify these transcripts as originating predominantly from Dothideomycetes and Leotiomycetes species, with functional annotation of gene families indicating active growth and metabolism, with particular regards to glucose intake and processing, as well as gene regulation.

A Key Role for Apoplastic H2O2 in Norway Spruce Phenolic Metabolism

The redox state of the apoplast has a profound influence on cellular metabolism. Apoplastic events such as monolignol oxidation and lignin polymerization are difficult to study in intact trees. To investigate the role of apoplastic hydrogen peroxide (H2O2) in gymnosperm phenolic metabolism, an extracellular lignin-forming cell culture of Norway spruce (Picea abies) was used as a research model. Scavenging of apoplastic H2O2 by potassium iodide repressed lignin formation, in line with peroxidases activating monolignols for lignin polymerization. Time-course analyses coupled to candidate substrate-product pair network propagation revealed differential accumulation of low-molecular-weight phenolics, including (glycosylated) oligolignols, (glycosylated) flavonoids, and proanthocyanidins, in lignin-forming and H2O2-scavenging cultures and supported that monolignols are oxidatively coupled not only in the cell wall but also in the cytoplasm, where they are coupled to other monolignols and proanthocyanidins. Dilignol glycoconjugates with reduced structures were found in the culture medium, suggesting that cells are able to transport glycosylated dilignols to the apoplast. Transcriptomic analyses revealed that scavenging of apoplastic H2O2 resulted in remodulation of the transcriptome, with reduced carbon flux into the shikimate pathway propagating down to monolignol biosynthesis. Aggregated coexpression network analysis identified candidate enzymes and transcription factors for monolignol oxidation and apoplastic H2O2 production in addition to potential H2O2 receptors. The results presented indicate that the redox state of the apoplast has a profound influence on cellular metabolism.

Darkened leaves use different metabolic strategies for senescence and survival

A robust working model delineates the main axes of the divergent metabolic strategies used by Arabidopsis thaliana in response to partial or total darkening treatments. In plants, an individually darkened leaf initiates senescence much more rapidly than a leaf from a whole darkened plant. Combining transcriptomic and metabolomic approaches in Arabidopsis (Arabidopsis thaliana), we present an overview of the metabolic strategies that are employed in response to different darkening treatments. Under darkened plant conditions, the perception of carbon starvation drove a profound metabolic readjustment in which branched-chain amino acids and potentially monosaccharides released from cell wall loosening became important substrates for maintaining minimal ATP production. Concomitantly, the increased accumulation of amino acids with a high nitrogen-carbon ratio may provide a safety mechanism for the storage of metabolically derived cytotoxic ammonium and a pool of nitrogen for use upon returning to typical growth conditions. Conversely, in individually darkened leaf, the metabolic profiling that followed our 13C-enrichment assays revealed a temporal and differential exchange of metabolites, including sugars and amino acids, between the darkened leaf and the rest of the plant. This active transport could be the basis for a progressive metabolic shift in the substrates fueling mitochondrial activities, which are central to the catabolic reactions facilitating the retrieval of nutrients from the senescing leaf. We propose a model illustrating the specific metabolic strategies employed by leaves in response to these two darkening treatments, which support either rapid senescence or a strong capacity for survival.

Transcriptional Roadmap to Seasonal Variation in Wood Formation of Norway Spruce

Seasonal wood transcriptomes of Norway spruce suggest mechanisms underlying specific aspects of gymnosperm wood biology, such as latewood formation, lignin biosynthesis, and tracheid longevity. Seasonal cues influence several aspects of the secondary growth of tree stems, including cambial activity, wood chemistry, and transition to latewood formation. We investigated seasonal changes in cambial activity, secondary cell wall formation, and tracheid cell death in woody tissues of Norway spruce (Picea abies) throughout one seasonal cycle. RNA sequencing was performed simultaneously in both the xylem and cambium/phloem tissues of the stem. Principal component analysis revealed gradual shifts in the transcriptomes that followed a chronological order throughout the season. A notable remodeling of the transcriptome was observed in the winter, with many genes having maximal expression during the coldest months of the year. A highly coexpressed set of monolignol biosynthesis genes showed high expression during the period of secondary cell wall formation as well as a second peak in midwinter. This midwinter peak in expression did not trigger lignin deposition, as determined by pyrolysis-gas chromatography/mass spectrometry. Coexpression consensus network analyses suggested the involvement of transcription factors belonging to the ASYMMETRIC LEAVES2/LATERAL ORGAN BOUNDARIES and MYELOBLASTOSIS-HOMEOBOX families in the seasonal control of secondary cell wall formation of tracheids. Interestingly, the lifetime of the latewood tracheids stretched beyond the winter dormancy period, correlating with a lack of cell death-related gene expression. Our transcriptomic analyses combined with phylogenetic and microscopic analyses also identified the cellulose and lignin biosynthetic genes and putative regulators for latewood formation and tracheid cell death in Norway spruce, providing a toolbox for further physiological and functional assays of these important phase transitions.

Seidr: A toolkit for calculation of crowd networks

Gene network analysis offers a powerful tool to extract key players in complex RNA sequencing experiments which cannot be adequately examined via binary differential expression analysis. A number of gene network inference algorithms have been published, but any algorithm based on a single statistic tends to sufer from bias towards a particular type of interaction. The DREAM 5 challenge ofered a potential solution via aggregation of several methods into a combined crowd network. Here we present Seidr, a unified tool to create gene networks and combine them into a unified meta-network. Seidr is implemented with a focus on speed and makes heavy use of parallelism where applicable.Abstract Summary Gene network analysis is a powerful tool to identify and prioritize candidate genes, especially from data sets where experimental design renders other approaches, such as differential expression analysis, limiting or infeasible. Numerous gene network inference algorithms have been published and are commonly individually applied in transcriptomics studies. It has, however, been shown that every algorithm is biased towards identifying specific types of gene interaction and that an ensemble of inference methods can reconstruct more accurate networks. This approach has been hindered by lack of an implementation to run and combine such combinations of inference algorithms. Here, we present Seidr: a toolkit to perform multiple gene network inferences and combine their results into a unified meta-network. Availability and implementation Seidr code is open-source, available from GitHub and also compiled in docker and singularity containers. It is implemented in C++ for fast computation and supports massive parallelisation through MPI. Documentation, tutorials and exemplary use are available from https://seidr.readthedocs.io. Contact bastian.schiffthaler@umu.se, nicolas.delhomme@slu.se

Training in High-Throughput Sequencing: Common Guidelines to Enable Material Sharing, Dissemination, and Reusability.

The advancement of high-throughput sequencing (HTS) technologies and the rapid development of numerous analysis algorithms and pipelines in this field has resulted in an unprecedentedly high demand for training scientists in HTS data analysis. Embarking on developing new training materials is challenging for many reasons. Trainers often do not have prior experience in preparing or delivering such materials and struggle to keep them up to date. A repository of curated HTS training materials would support trainers in materials preparation, reduce the duplication of effort by increasing the usage of existing materials, and allow for the sharing of teaching experience among the HTS trainers’ community. To achieve this, we have developed a strategy for materials’ curation and dissemination. Standards for describing training materials have been proposed and applied to the curation of existing materials. A Git repository has been set up for sharing annotated materials that can now be reused, modified, or incorporated into new courses. This repository uses Git; hence, it is decentralized and self-managed by the community and can be forked/built-upon by all users. The repository is accessible at http://bioinformatics.upsc.se/htmr.