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Plants serve as host to numerous microorganisms. The members of these microbial communities interact among each other and with the plant, and there is increasing evidence to suggest that the microbial community may promote plant growth, improve drought tolerance, facilitate pathogen defense and even assist in environmental remediation. Therefore, it is important to better understand the mechanisms that influence the composition and structure of microbial communities, and what role the host may play in the recruitment and control of its microbiome. In particular, there is a growing body of research to suggest that plant defense systems not only provide a layer of protection against pathogens but may also actively manage the composition of the overall microbiome. In this review, we provide an overview of the current research into mechanisms employed by the plant host to select for and control its microbiome. We specifically review recent research that expands upon the role of keystone microbial species, phytohormones, and abiotic stress, and in how they relate to plant driven dynamic microbial structuring.

To understand the genetic mechanisms underlying wood anatomical and morphological traits in Populus trichocarpa , we used 869 unrelated genotypes from a common garden in Clatskanie, Oregon that were previously collected from across the distribution range in western North America. Using GEMMA mixed model analysis, we tested for the association of 25 phenotypic traits and nine multitrait combinations with 6.741 million SNPs covering the entire genome. Broad-sense trait heritabilities ranged from 0.117 to 0.477. Most traits were significantly correlated with geoclimatic variables suggesting a role of climate and geography in shaping the variation of this species. Fifty-seven SNPs from single trait GWAS and 11 SNPs from multitrait GWAS passed an FDR threshold of 0.05, leading to the identification of eight and seven nearby candidate genes, respectively. The percentage of phenotypic variance explained (PVE) by the significant SNPs for both single and multitrait GWAS ranged from 0.01% to 6.18%. To further evaluate the potential roles of candidate genes, we used a multi-omic network containing five additional data sets, including leaf and wood metabolite GWAS layers and coexpression and comethylation networks. We also performed a functional enrichment analysis on coexpression nearest neighbors for each gene model identified by the wood anatomical and morphological trait GWAS analyses. Genes affecting cell wall composition and transport related genes were enriched in wood anatomy and stomatal density trait networks. Signaling and metabolism related genes were also common in networks for stomatal density. For leaf morphology traits (leaf dry and wet weight) the networks were significantly enriched for GO terms related to photosynthetic processes as well as cellular homeostasis. The identified genes provide further insights into the genetic control of these traits, which are important determinants of the suitability and sustainability of improved genotypes for lignocellulosic biofuel production.

Understanding the regulatory network controlling cell wall biosynthesis is of great interest in Populus trichocarpa , both because of its status as a model woody perennial and its importance for lignocellulosic products. We searched for genes with putatively unknown roles in regulating cell wall biosynthesis using an extended network-based Lines of Evidence (LOE) pipeline to combine multiple omics data sets in P. trichocarpa , including gene coexpression, gene comethylation, population level pairwise SNP correlations, and two distinct SNP-metabolite Genome Wide Association Study (GWAS) layers. By incorporating validation, ranking, and filtering approaches we produced a list of nine high priority gene candidates for involvement in the regulation of cell wall biosynthesis. We subsequently performed a detailed investigation of candidate gene GROWTH-REGULATING FACTOR 9 ( PtGRF9 ). To investigate the role of PtGRF9 in regulating cell wall biosynthesis, we assessed the genome-wide connections of PtGRF9 and a paralog across data layers with functional enrichment analyses, predictive transcription factor binding site analysis, and an independent comparison to eQTN data. Our findings indicate that PtGRF9 likely affects the cell wall by directly repressing genes involved in cell wall biosynthesis, such as PtCCoAOMT and PtMYB.41 , and indirectly by regulating homeobox genes. Furthermore, evidence suggests that PtGRF9 paralogs may act as transcriptional co-regulators that direct the global energy usage of the plant. Using our extended pipeline, we show multiple lines of evidence implicating the involvement of these genes in cell wall regulatory functions and demonstrate the value of this method for prioritizing candidate genes for experimental validation.

Metabolite genome-wide association studies (mGWASs) are increasingly used to discover the genetic basis of target phenotypes in plants such as Populus trichocarpa , a biofuel feedstock and model woody plant species. Despite their growing importance in plant genetics and metabolomics, few mGWASs are experimentally validated. Here, we present a functional genomics workflow for validating mGWAS-predicted enzyme–substrate relationships. We focus on uridine diphosphate–glycosyltransferases (UGTs), a large family of enzymes that catalyze sugar transfer to a variety of plant secondary metabolites involved in defense, signaling, and lignification. Glycosylation influences physiological roles, localization within cells and tissues, and metabolic fates of these metabolites. UGTs have substantially expanded in P. trichocarpa , presenting a challenge for large-scale characterization. Using a high-throughput assay, we produced substrate acceptance profiles for 40 previously uncharacterized candidate enzymes. Assays confirmed 10 of 13 leaf mGWAS associations, and a focused metabolite screen demonstrated varying levels of substrate specificity among UGTs. A substrate binding model case study of UGT-23 rationalized observed enzyme activities and mGWAS associations, including glycosylation of trichocarpinene to produce trichocarpin, a major higher-order salicylate in P. trichocarpa. We identified UGTs putatively involved in lignan, flavonoid, salicylate, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress response that determine sustainable biomass crop production. Our results provide new support for in silico analyses and evidence-based guidance for in vivo functional characterization.

Corrigendum: In the originally published article by Salvachua et al. (2019), the author Anna Furches was accidentally omitted from the byline of manuscript, ‘Metabolic engineering of Pseudomonas putida for increased polyhydroxyalkanoate production from lignin’ Volume 13, Issue 1, Pages 290–298. The byline should read as given above. https://doi.org/10.1111/1751-7915.13481

As time progresses and technology improves, biological data sets are continuously increasing in size. New methods and new implementations of existing methods are needed to keep pace with this increase. In this paper, we present a high-performance computing (HPC)-capable implementation of Iterative Random Forest (iRF). This new implementation enables the explainable-AI eQTL analysis of SNP sets with over a million SNPs. Using this implementation, we also present a new method, iRF Leave One Out Prediction (iRF-LOOP), for the creation of Predictive Expression Networks on the order of 40,000 genes or more. We compare the new implementation of iRF with the previous R version and analyze its time to completion on two of the world’s fastest supercomputers, Summit and Titan. We also show iRF-LOOP’s ability to capture biologically significant results when creating Predictive Expression Networks. This new implementation of iRF will enable the analysis of biological data sets at scales that were previously not possible.

Summary Microbial conversion offers a promising strategy for overcoming the intrinsic heterogeneity of the plant biopolymer, lignin. Soil microbes that natively harbour aromatic‐catabolic pathways are natural choices for chassis strains, and Pseudomonas putida KT2440 has emerged as a viable whole‐cell biocatalyst for funnelling lignin‐derived compounds to value‐added products, including its native carbon storage product, medium‐chain‐length polyhydroxyalkanoates (mcl‐PHA). In this work, a series of metabolic engineering targets to improve mcl‐PHA production are combined in the P. putida chromosome and evaluated in strains growing in a model aromatic compound, p‐coumaric acid, and in lignin streams. Specifically, the PHA depolymerase gene phaZ was knocked out, and the genes involved in β‐oxidation (fadBA1 and fadBA2) were deleted. Additionally, to increase carbon flux into mcl‐PHA biosynthesis, phaG, alkK, phaC1 and phaC2 were overexpressed. The best performing strain – which contains all the genetic modifications detailed above – demonstrated a 53% and 200% increase in mcl‐PHA titre (g l−1) and a 20% and 100% increase in yield (g mcl‐PHA per g cell dry weight) from p‐coumaric acid and lignin, respectively, compared with the wild type strain. Overall, these results present a promising strain to be employed in further process development for enhancing mcl‐PHA production from aromatic compounds and lignin. In this work, a series of metabolic engineering targets to improve mcl‐PHA production were combined in the P. putida chromosome and evaluated in strains growing in a model aromatic compound, p‐coumaric acid, and in lignin streams. Specifically, the PHA depolymerase gene (phaZ) and genes involved in β‐oxidation (fadBA1 and fadBA2) were deleted, while phaG, alkK, phaC1, and phaC2 were overexpressed to increase carbon flux from fatty acid biosynthesis to mcl‐PHA production. This strain demonstrated an increase in mcl‐PHA titer (g l−1) and yield (g mcl‐PHA per g cell dry weight) from p‐coumaric acid and from lignin compared to the wild‐type strain, resulting in a promising strain to be employed in further process development for enhancing mcl‐PHA production from aromatic compounds and lignin.

Premise of the study: Narrow-ranging, rare species often exhibit levels of genetic diversity lower than more common or wide-spread congeners. These taxa are at increased risk of extinction due to threats associated with natural as well as anthropogenic events. We assessed genetic variation in three federally endangered Sarracenia species. We discuss maintenance of genetic diversity and evolutionary implications of rarity. Methods: We analyzed three noncoding chloroplast regions and nine microsatellite loci in populations spanning the geographic ranges of S. oreophila, S. alabamensis, and S. jonesii. The same microsatellite loci were used to examine a single field site of three more widespread species (S. alata, S. leucophylla, and S. rubra subsp. wherryi). Key results: All three endangered species have experienced reductions in population size and numbers. All show considerably less variation than more widespread members of the genus. Sarracenia alabamensis maintains the greatest microsatellite variation but has the fewest remaining populations and may be under the greatest threat. More widespread S. oreophila maintains surprising chloroplast diversity, yet exhibits little microsatellite diversity. Sarracenia jonesii lacks chloroplast diversity, yet maintains greater microsatellite diversity than S. oreophila. Conclusions: The three endangered species differ in levels and structure of diversity, yet not in predictable ways, emphasizing that unique demographic and ecological histories, rather than current distribution and population size, best explain present patterns of genetic variation. Maintenance of remaining genetic variation is important, but preventing further habitat loss and degradation is critical.

• Premise of the study: The role of hybridization in plant evolution remains a source of intense debate. Potential consequences range from genetic dead-ends to species fusion or hybrid speciation. While much has been learned from model systems such as Populus, Iris, and Helianthus, many questions remain. Consisting of 11 species that are all capable of hybridizing, Sarracenia presents an excellent system in which to study hybridization.• Methods: Using microsatellites, we examined a single field site consisting of three species: S. leucophylla, S. alata, and S. rubra subsp. wherryi. We determined the level of genetic admixture and compared it with allopatric sites of the same taxa.• Key results: In contrast to the well-defined clusters formed when we examined the allopatric sites, the sympatric field site exhibited a wide range of admixture. Additionally, when the relative genetic makeup of “pure” species at the site was compared with the makeup of hybrids, we found that Sarracenia alata contributed disproportionately to the hybrid genomes.• Conclusions: Our study provides further evidence that hybridization is contributing to interspecific gene flow in the genus and that all species do not contribute equally to hybridization. Implications for conservation are discussed.

The model woody plant Populus trichocarpa displays an atypical alkene-diverse wax cuticle likely driven by copy number variation (CNV) of 3-ketoacyl-CoA synthases (KCS), which has been difficult to confirm based on short-read assemblies. New long-read sequencing provides opportunities to develop telomere-to-telomere resources to detect cryptic variation, including CNVs, which are currently missed in traditional analyses. Integrating this information can improve genomic prediction for breeding and provide insights into the evolutionary basis of important traits. Our analysis of 78 telomere-to-telomere long-read haplotypes identified more than twice as many KCS genes as previously reported, along with numerous intragenic non-synonymous substitutions. Random forest predictive models highlighted the importance of Potri.010G079500 in producing very long chain alkenes; however, its absence did not predict previously reported alkene-deficient phenotypes. Instead, alkene levels are best predicted by the combinations of KCS copies. Amino acid substitutions clustered around ligand and donor binding pockets, suggesting they contribute to differing wax cuticle composition. Finally, each KCS gene and copy was linked to a helitron transposon. A phylogenetic analysis indicates they are the evolutionary mechanism for generating KCS tandem arrays. Long-read sequencing and telomere-to-telomere assembles revealed large-effect loci critical to genetic studies that are unattainable from short-reads. These approaches also have the potential to reveal novel insights into genome structure and function, such as the helitrons identified here. Our results highlight that, given current challenges in annotation and assembly, detailed and focused long-read sequences are key to interpreting complex genomic regions that contain tandem copy number variants.