Flexure wood formation via growth reprogramming in hybrid aspen involves jasmonates and polyamines and transcriptional changes resembling tension wood development.

Stem bending in trees induces flexure wood but its properties and development are poorly understood. Here, we investigated the effects of low-intensity multidirectional stem flexing on growth and wood properties of hybrid aspen, and on its transcriptomic and hormonal responses. Glasshouse-grown trees were either kept stationary or subjected to several daily shakes for 5 wk, after which the transcriptomes and hormones were analyzed in the cambial region and developing wood tissues, and the wood properties were analyzed by physical, chemical and microscopy techniques. Shaking increased primary and secondary growth and altered wood differentiation by stimulating gelatinous-fiber formation, reducing secondary wall thickness, changing matrix polysaccharides and increasing cellulose, G- and H-lignin contents, cell wall porosity and saccharification yields. Wood-forming tissues exhibited elevated jasmonate, polyamine, ethylene and brassinosteroids and reduced abscisic acid and gibberellin signaling. Transcriptional responses resembled those during tension wood formation but not opposite wood formation and revealed several thigmomorphogenesis-related genes as well as novel gene networks including FLA and XTH genes encoding plasma membrane-bound proteins. Low-intensity stem flexing stimulates growth and induces wood having improved biorefinery properties through molecular and hormonal pathways similar to thigmomorphogenesis in herbaceous plants and largely overlapping with the tension wood program of hardwoods.

Seiðr: Efficient calculation of robust ensemble gene networks.

Gene regulatory and gene co-expression networks are powerful research tools for identifying biological signal within high-dimensional gene expression data. In recent years, research has focused on addressing shortcomings of these techniques with regard to the low signal-to-noise ratio, non-linear interactions and dataset dependent biases of published methods. Furthermore, it has been shown that aggregating networks from multiple methods provides improved results. Despite this, few useable and scalable software tools have been implemented to perform such best-practice analyses. Here, we present Seidr (stylized Seiðr), a software toolkit designed to assist scientists in gene regulatory and gene co-expression network inference. Seidr creates community networks to reduce algorithmic bias and utilizes noise corrected network backboning to prune noisy edges in the networks. Using benchmarks in real-world conditions across three eukaryotic model organisms, Saccharomyces cerevisiae, Drosophila melanogaster, and Arabidopsis thaliana, we show that individual algorithms are biased toward functional evidence for certain gene-gene interactions. We further demonstrate that the community network is less biased, providing robust performance across different standards and comparisons for the model organisms. Finally, we apply Seidr to a network of drought stress in Norway spruce (Picea abies (L.) H. Krast) as an example application in a non-model species. We demonstrate the use of a network inferred using Seidr for identifying key components, communities and suggesting gene function for non-annotated genes.

Centromere-Specific Retrotransposons and Very-Long-Chain Fatty Acid Biosynthesis in the Genome of Yellowhorn (Xanthoceras sorbifolium, Sapindaceae), an Oil-Producing Tree With Significant Drought Resistance.

In-depth genome characterization is still lacking for most of biofuel crops, especially for centromeres, which play a fundamental role during nuclear division and in the maintenance of genome stability. This study applied long-read sequencing technologies to assemble a highly contiguous genome for yellowhorn (Xanthoceras sorbifolium), an oil-producing tree, and conducted extensive comparative analyses to understand centromere structure and evolution, and fatty acid biosynthesis. We produced a reference-level genome of yellowhorn, ∼470 Mb in length with ∼95% of contigs anchored onto 15 chromosomes. Genome annotation identified 22,049 protein-coding genes and 65.7% of the genome sequence as repetitive elements. Long terminal repeat retrotransposons (LTR-RTs) account for ∼30% of the yellowhorn genome, which is maintained by a moderate birth rate and a low removal rate. We identified the centromeric regions on each chromosome and found enrichment of centromere-specific retrotransposons of LINE1 and Gypsy in these regions, which have evolved recently (∼0.7 MYA). We compared the genomes of three cultivars and found frequent inversions. We analyzed the transcriptomes from different tissues and identified the candidate genes involved in very-long-chain fatty acid biosynthesis and their expression profiles. Collinear block analysis showed that yellowhorn shared the gamma (γ) hexaploidy event with Vitis vinifera but did not undergo any further whole-genome duplication. This study provides excellent genomic resources for understanding centromere structure and evolution and for functional studies in this important oil-producing plant.