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Record W2789745689 · doi:10.1093/treephys/tpy026

Branching out: a new era of investigating physiological processes in forest trees using genomic tools

2018· editorial· en· W2789745689 on OpenAlexaff
Chung‐Jui Tsai, Scott A. Harding, Janice E. K. Cooke

Bibliographic record

VenueTree Physiology · 2018
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBranching (polymer chemistry)BiologyDendrochronologyBotanyChemistryPaleontology

Abstract

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In just over a decade since the publication of the first forest tree genome—that of Populus trichocarpa (Salicaceae; Tuskan et al. 2006)—we have witnessed tremendous advances in tree physiology leveraged from forest tree genomic resources. Prepublication release of draft sequence data from the Populus genome project (Tuskan et al. 2004), together with pioneering efforts to develop expressed sequence tag (EST) resources for Populus spp. (e.g., Sterky et al. 1998, 2004) and loblolly pine (Pinus taeda, Pinaceae; Allona et al. 1998), revolutionized the way in which the forest tree community conducts physiological experiments. Indeed, an Editorial in this journal penned by Stan Wullschleger, Jerry Tuskan and Stephen DiFazio soon after the announcement of the Populus genome project was prescient in identifying innovative new avenues in which genomics would be brought to bear on forest tree physiology, from molecular to ecosystem scales (Wullschleger et al. 2002). In this Invited Issue, entitled Tree Physiology and Genomics, we bring together 12 articles that skillfully illustrate uses of an ever-expanding forest genomics toolkit to further our insight into various physiological processes. The status of P. trichocarpa as the flagship tree genome sequence is reflected in this Invited Issue, in which half of the articles use this resource and related omic tools in their investigations. The remaining articles draw from genome sequence and transcriptomic resources developed for a number of other taxa. In recent years, advances in technologies, increased access to sequencing and bioinformatics expertise and decreased costs have spurred the community to develop significant genomic and transcriptomic resources for a dizzying number of economically, ecologically and evolutionarily important forest tree species from both the Northern and Southern hemispheres. These species represent commercially important fast-growing short rotation woody crops, ecosystem-dominating species such as slow-growing conifers, threatened species and species from fragile ecosystems, as well as species occupying key positions on the tree of life. As of early 2018, the list of forest tree genome sequences comprised several eudicot species, including additional poplar species (Populus euphratica, Salicaceae; Ma et al. 2013), gum (Eucalyptus grandis, Myrtaceae; Myburg et al. 2014), willow (Salix suchowensis, Salicaceae; Dai et al. 2014), birch (Betula pendula and Betula nana, Betulaceae; Wang et al. 2013, Salojarvi et al. 2017), ash (Fraxinus excelsior, Oleaceae; Sollars et al. 2017), oak (Quercus robur, Fagaceae; Plomion et al. 2016a) and rubber tree (Hevea brasiliensis, Euphorbiaceae; Rahman et al. 2013); the basal angiosperm Amborella trichopoda (Amborellaceae; Amborella Genome Project 2013); and the even earlier diverging giga-genome conifers Norway spruce, white spruce, loblolly pine and sugar pine (Picea abies, Picea glauca, P. taeda and Pinus lambertiana, respectively, all Pinaceae; Nystedt et al. 2013, Zimin et al. 2014, Warren et al. 2015, Stevens et al. 2016). Genome sequences of several other forest tree species have been released prior to publication (e.g., Phytozome v12; Goodstein et al. 2012), and many more are on track to be publicly released and/or published in the near- and mid-term. Genome sequences are also available for a wide array of agronomically important fruit tree species (summarized in Chagné 2015 and Neale et al. 2017), which serve as important resources for comparative genomic analyses of perennial processes. Articles in this Invited Issue illustrate how the growing diversity in genomic resources for forest tree species that are adapted to a wide range of environments and other ecological parameters provides unprecedented power to examine adaptive traits. This Invited Issue also highlights the maturation that has taken place in genomics-enabled physiology over the last decade. Wullschleger et al. (2002) envisioned that the availability of genomic-scale sequence resources would open the doors to unprecedented interdisciplinary approaches to investigate physiological processes important to forest trees’ perennial lifestyle in a more integrated, comprehensive fashion across scales of biological organization. While they predicted that these types of integrated approaches may take years to come to fruition, this promise is already beginning to be realized, as evidenced by articles in this Invited Issue. For example, systems biology approaches are now feasible for forest trees due to major technological and analytical advances in other omics domains, such as proteomics and metabolomics, together with more targeted protein and metabolite profiling methods. These omics technologies, alongside broad-scale and targeted functional genomics techniques, enable more holistic examinations of gene families, metabolic pathways and signaling networks to advance our understanding of physiological mechanisms. Working at the nexus of functional genomics, population genomics and quantitative genomics, forest tree biologists are also increasingly exploiting the natural genetic variation that exists in these undomesticated species to investigate how this natural genetic variation manifests itself in phenotypic variation associated with functional traits. Connecting genotype with phenotype is one of the grand challenges in contemporary biology, and physiology is central to this endeavor. Forest trees interact with a plethora of organisms in their natural environments, and genomics is also transforming the way in which researchers investigate forest tree interactions with symbiotic, pathogenic, saprotrophic and endophytic microbes. In tandem with the explosion in genomic-scale sequence information for forest tree species, genomic resources have been generated for hundreds of fungal species (MycoCosm; Grigoriev et al. 2011, Grigoriev et al. 2014) and other organisms such as bacteria, insects, nematodes and viruses (e.g., Büttner et al. 2013, Futai 2013, Gugerli et al. 2013, Keeling et al. 2013, Martin et al. 2017, Gschloessl et al. 2018) that interact with forest trees. These genomic resources generated remarkable new insights about how pathogenic and mycorrhizal fungal interact with their hosts (e.g., Duplessis et al. 2011, Martin et al. 2016), and have enabled new ways to finely dissect a tree host’s response to interaction with these fungi. Excitingly, it is now possible to examine host and fungal/bacterial responses simultaneously (e.g., Meyer et al. 2016). Within the above context, we introduce the 12 articles of this Invited Issue in the following sections within the broad themes of abiotic stress, development of wood and bark, cell wall biosynthesis, nitrogen metabolism, pathogen interactions and multi-omics approaches. This Invited Issue is dedicated to the memory of Dr Carl Douglas, our colleague, friend and mentor, whose life was cut tragically short in a mountaineering accident. Carl was a leader in our field in so many ways. Carl’s group was amongst the first to use molecular tools in forest trees, choosing Populus as his system of choice, and was a tireless advocate for Populus as a model genomic system. Carl played instrumental roles in developing landmark Populus genomic resources, such as his contributions to the P. trichocarpa genome sequence paper (Tuskan et al. 2006), and a unique integrated genetic, genomic and phenotypic dataset for P. trichocarpa (e.g., Porth et al. 2013; Suarez-Gonzalez et al. 2016) that will be exploited for years to come. Carl and his group published over 100 papers in Populus, Arabidopsis and other systems, making outstanding contributions to the areas of phenylpropanoid metabolism and biosynthesis of lignin, pollen exine and plant cell walls. Many of these papers appeared in the very best journals in our field. Carl took on several other leadership roles over his career, including at the University of British Columbia where he was a faculty member for nearly 30 years, and for national and international plant biology organizations. Carl was a remarkable, kind and caring individual whose presence in our international community is greatly missed. The triumvirate of drought, heat and cold comprises perhaps the most persistent and widespread abiotic challenge to forests worldwide, even in non-arid regions. As the old adage about sessile plants suggests, trees cannot manipulate or avoid environmental fluctuations, but they can often tolerate and acclimate over their long lifespan. Many of the studies featured in this Invited Issue explore development and survival of long-lived organisms in a way that trees are uniquely qualified to facilitate. The study foci ranged from transcriptomic investigations of stress responses to the acquisition and curation of new gene data related to drought tolerance. Fox et al. (2018) focused on Pinus halepensis (Aleppo pine) native to semi-arid regions throughout the Mediterranean basin. Aleppo pine has played an important historical role in anti-desertification programs and forest plantations in Israel. These forests have grown well in the past, but in recent years the impact of climate change has resulted in decreased vitality. Using rooted cuttings propagated from a mature tree living in a sub-optimal environment, Fox et al. (2018) have assembled a rich body of physiological and transcriptomic data on the response course of this robust species during prolonged drought and recovery. The molecular response of P. halepensis roots to drought was reported earlier by others (Sathyan et al. 2005), but this paper examined needle response. Of more than 6000 drought-responsive transcripts, fewer than half were reported previously and the rest were assembled de novo from this study. A striking finding was the strong contribution by retrotransposons, which make up over 60% of the P. taeda genome (Neale et al. 2014), during Aleppo pine recovery from drought. Differential expression of genes potentially involved in histone modifications was also noted. As epigenetic mechanisms are known to suppress retrotransposon activity during stress (Ito et al. 2011), the authors discussed their findings regarding the interplay between epigenetics and retrotransposon activity as a potential mechanism of long-lived trees to adapt to future stress. Sena et al. (2018) report on the comparatively large family of dehydrin genes found in conifers native to Boreal forests. Dehydrins are group 2 Late Embryogenesis Abundant (LEA) proteins that confer cellular tolerance to dehydration partly via hydration-dependent conformational changes (Hanin et al. 2011). Using powerful genome search algorithms like those based on Hidden Markov principles (Eddy 1998), Sena et al. (2018) conducted comprehensive searches of dehydrin sequences in the Pinaceae as well as representative angiosperm species. Following up on their discovery that conifers may have as many as fourfold the number of dehydrin genes as angiosperms (Rigault et al. 2011), Sena and colleagues delve into the evolutionary basis for the expansion. Differences in gene structure between angiosperm and conifer dehydrins are presented, as is the drought-induced expression of a subset of conifer-specific dehydrins. Their work implies greater sub-functionalization and a broader functional repertory for dehydrins than previously estimated based on angiosperm lineages. Trees provide not only a host of environmental services, they also yield marketplace products. Perhaps nowhere have post-genomics era technologies had greater application than toward the post-harvest utilization of tree biomass (Grattapaglia et al. 2009). Several studies in this issue investigated the dependence of cell wall traits on environmental and circadian cues. Given the ever-changing environment and longevity of woody bioenergy crops, trees harvested for biorefineries are bound to have experienced episodic stress or sub-optimal conditions during their multi-year growth. In this regard, it is imperative to understand how wood properties change in response to stress, and whether and how such changes affect bioprocessing. Ployet et al. (2018) studied the effects of cold temperatures on wood traits in a frost-tolerant hybrid Eucalyptus gundal (E. gunnii × E. dalrympleana). Arguably the most-planted hardwood species in the world, commercial plantations of Eucalyptus remain limited to tropical and subtropical regions due to frost sensitivity (Wisniewski et al. 2014). Ployet et al. (2018) showed that cold treatments induced secondary cell wall thickening and increased deposition of lignin and extractives, reminiscent of the difference between autumn/winter wood and summer wood. This, along with increased pentose-to-hexose polysaccharide ratio in cold-stressed wood, led the authors to suggest that increased lignin and hemicellulose contributed to cell wall reinforcement against freezing damage. Coexpression network analysis with transcription factors known to regulate secondary cell wall biogenesis (Ye and Zhong 2015) identified cold-regulated transcription factors that are promising candidates to decipher the crosstalk between cell wall biogenesis and cold stress response. Wildhagen et al. (2018) investigated the genetic canalization and drought responsiveness of wood anatomical and chemical traits relevant to biofuel conversion in black poplar (Populus nigra). Three genotypes originating from habitats with varying water availability exhibited different wood anatomies, lignin contents and fermentable sugar yields. Xylem transcriptomics analysis revealed a greater of genotype than drought stress stress as against the that drought would lignin to cell wall lignin was by drought stress in all genotypes et al. to of wood to was increased than Their findings that lignin wood anatomical with sugar yield those of et al. and that is by factors other or in lignin cell wall were not in this gene network analysis revealed an of with and with the of between and that even abiotic to increased lignin wood from trees as a is not more to sugar than that of trees. The findings of Wildhagen et al. (2018) the that a of cell has a major on of biomass and 2013, et al. 2014, cell wall but not were by of in Populus wood et al. Following up on their findings that of in Populus in response to drought et al. et al. (2018) cell wall and transcriptomics to dissect the The increased in at the of the hemicellulose via utilization of and/or for the et al. on published of circadian of cell wall biogenesis et al. 2015) and poplar expression data et al. 2011), the authors that expression the of for polysaccharide and and which in the The study showed that the the of expression can have circadian of gene expression in tree species. and approaches are increasingly alongside transcriptomic analysis for functional This Invited Issue studies that proteomics et al. 2018) and et al. 2018) to the of wood et al. (2018) focused on genes with expression to develop a P. trichocarpa wood The network from and interaction with publicly available The most in the network is to a transcription after their with other proteins and involved in et al. have not been to wood but the interactions in reported by et al. (2018) the of their in cell that to and data the authors showed that wood is not only by but also by their predicted interactions with and proteins in the work that a interaction study of genes with can and to community resources. of on molecular and genetic of the lignin have in a wide range of and woody species et al. This into and metabolic of lignin traits lignin and across species. fewer studies have examined the responses to lignin As many of the are into different phenylpropanoid and to different of or their responses to genetic a greater of than the lignin traits et al. In this et al. (2018) conducted comparative on of for lignin or increased ratio in hybrid Populus × and Populus × The previously reported changes in lignin or ratio were with in In changes in metabolite were between and were by the genetic and the analytical et al. that genetic to quantitative changes of lignin had a greater and more impact on metabolism than genetic modifications that lignin This is with the in et al. but not et al. The work the of approaches for of metabolic as well as metabolic associated with metabolic or variation from or natural to significant advances in our understanding of biosynthesis and development a of wood The may be due in to and not in all species, and it can be as early as years or as as years on the species and is as by of that to many of such as and that are for wood and and In this Invited Issue, and (2018) a new model to challenge the and that of living in the of A recent functional genomics study of biosynthesis in identified a of and with expression in et al. 2016). This led to the discovery and of a that the of major et al. 2016). and (2018) now that a number of their and for biosynthesis, other cell This with in which are to be or in the The by and (2018) the of whether of in the is the or the Given the of and our limited understanding of their from the may be a for and of genes involved in biosynthesis of While the on may be mature In all the first of against water and is the with In tree the to a secondary known as the which the The comprises with which remain as after cell is in and by and abiotic to as a and 1998, et al. many of biosynthesis remain et al. 2016). et al. (2018) now report on a transcriptomic dataset for the of biosynthesis in to development and plant in Their data on the that many of Arabidopsis genes have been for biosynthesis in In the developing those genes were with as from other that may to cell wall may of a that is in poplar and one of and in this study. In the authors reported expression on in developing of poplar that may be to with abiotic stress The of et al. (2018) the way for poplar genotypes with greater to as well as abiotic the years, many comparative studies have identified several and metabolic during and maturation and to at 2016). the molecular of potential to For conifer systems in is a to plants for functional analysis of The work of et al. (2018) in this Invited Issue one such on biosynthesis and of in pine (Pinus has the ratio protein and is a major and of for of the nitrogen in proteins of several plant species, including pine et al. the pine et al. 2014), et al. (2018) identified of all known and Their were in with increased protein deposition during as well as increased during These were not in with biosynthesis and throughout their The work a molecular basis for the of proteins in mature to 2016), and may future modifications to maturation and of metabolic proteins reported by et al. (2018) to for the first a of by only not in the This that the pathways for biosynthesis are with the biosynthesis in and the biosynthesis of et al. 2015, et al. change is not only and of trees, but perhaps more so their associated and and predicted forest including holistic understanding of mechanisms and et al. (2018) important insights about the between and abiotic stress on poplar by the work by et al. on the of to abiotic stress tolerance and signaling in Populus, et al. (2018) possible between metabolism and poplar against is an in the biosynthesis of family from but in this Invited Issue, et al. (2018) showed that is in poplar that and on that also with the authors metabolic and as mechanisms by which biosynthesis may with against The are since and but important stress mechanisms in pine has significant range during this which is the in pine a that species of to as the fungi. These which are that within the of their host has been as a of the (e.g., et al. 2016), but is also to fungal (e.g., and an for of these et al. (2018) this by developing a more and quantitative that they to of in of and genomic-scale data revealed that is not a of the of fungal along the of of fungal growth. this et al. (2018) that in but not fungal between treatments or individual represent in The new quantitative developed by et al. (2018) will not only for further of this but can be for in of in a wide range of plant and other environmental As the of 12 papers that make up this Invited Issue a range of contemporary genomic to investigate key physiological processes in the of metabolism and responses to and abiotic These papers the that we have as a community understanding of these processes since the of the Populus genome sequencing project in the early from Wullschleger et al. we can to an even greater of over the decade. The Populus system to provide the genomic resources and biological that an range of we that advances in technologies such as genome et al. 2015) will to even more in the decade. the the of genomic resources for several other forest tree species et al. Neale et al. that the community is into a era of genomics, and that we can an number of functional genomics studies for a broader range of species. can also more studies that examine adaptive traits for species from a wide range of ecological in holistic As we to genomic tools with other the community will the of Wullschleger et al. (2002) to explore how genotype and environment phenotype across scales of biological organization. his career, Dr Carl was an and early of new and technologies, and interdisciplinary a on our community his and his As a we can Carl’s memory by to as he would have

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.009
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0040.007
Open science0.0020.002
Research integrity0.0090.023
Insufficient payload (model declined to judge)0.0050.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.299
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2018
Admission routes1
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