High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar.

Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid "84K" (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

Chromosome-level genome assembly of a parent species of widely cultivated azaleas.

Azaleas (Ericaceae) comprise one of the most diverse ornamental plants, renowned for their cultural and economic importance. We present a chromosome-scale genome assembly for Rhododendron simsii, the primary ancestor of azalea cultivars. Genome analyses unveil the remnants of an ancient whole-genome duplication preceding the radiation of most Ericaceae, likely contributing to the genomic architecture of flowering time. Small-scale gene duplications contribute to the expansion of gene families involved in azalea pigment biosynthesis. We reconstruct entire metabolic pathways for anthocyanins and carotenoids and their potential regulatory networks by detailed analysis of time-ordered gene co-expression networks. MYB, bHLH, and WD40 transcription factors may collectively regulate anthocyanin accumulation in R. simsii, particularly at the initial stages of flower coloration, and with WRKY transcription factors controlling progressive flower coloring at later stages. This work provides a cornerstone for understanding the underlying genetics governing flower timing and coloration and could accelerate selective breeding in azalea.

A resource for characterizing genome-wide binding and putative target genes of transcription factors expressed during secondary growth and wood formation in Populus.

Identifying transcription factor target genes is essential for modeling the transcriptional networks underlying developmental processes. Here we report a chromatin immunoprecipitation sequencing (ChIP-seq) resource consisting of genome-wide binding regions and associated putative target genes for four Populus homeodomain transcription factors expressed during secondary growth and wood formation. Software code (programs and scripts) for processing the Populus ChIP-seq data are provided within a publically available iPlant image, including tools for ChIP-seq data quality control and evaluation adapted from the human Encyclopedia of DNA Elements (ENCODE) project. Basic information for each transcription factor (including members of Class I KNOX, Class III HD ZIP, BEL1-like families) binding are summarized, including the number and location of binding regions, distribution of binding regions relative to gene features, associated putative target genes, and enriched functional categories of putative target genes. These ChIP-seq data have been integrated within the Populus Genome Integrative Explorer (PopGenIE) where they can be analyzed using a variety of web-based tools. We present an example analysis that shows preferential binding of transcription factor ARBORKNOX1 to the nearest neighbor genes in a pre-calculated co-expression network module, and enrichment for meristem-related genes within this module including multiple orthologs of Arabidopsis KNOTTED-like Arabidopsis 2/6.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation.

BACKGROUND: Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. RESULTS: We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. CONCLUSIONS: We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis.

The physiological, transcriptional and genetic responses of an ozone-sensitive and an ozone tolerant poplar and selected extremes of their F2 progeny.

Relatively little is known about the transcriptional response or genetic control of response and adaptation of trees to tropospheric ozone exposure. Such understanding is needed as up to 50% of forests, globally, may be subjected to phytotoxic concentrations of ozone. The physiological, transcriptional and genetic response to ozone was examined in Populus trichocarpa and P. deltoides, which show extreme sensitivity and tolerance to ozone, respectively. Using an inbred F2 mapping population derived from these two species, we mapped quantitative trait loci (QTL) for traits associated with ozone response, examined segregation of the transcriptional response to ozone and co-located genes showing divergent responses between tolerant and sensitive genotypes with QTL. QTL were identified linking detrimental effects of ozone with leaf and biomass traits and differential responses were found for key genes involved in ethylene production and response.

The Populus Genome Integrative Explorer (PopGenIE): a new resource for exploring the Populus genome.

Populus has become an important model plant system. However, utilization of the increasingly extensive collection of genetics and genomics data created by the community is currently hindered by the lack of a central resource, such as a model organism database (MOD). Such MODs offer a single entry point to the collection of resources available within a model system, typically including tools for exploring and querying those resources. As a starting point to overcoming the lack of such an MOD for Populus, we present the Populus Genome Integrative Explorer (PopGenIE), an integrated set of tools for exploring the Populus genome and transcriptome. The resource includes genome, synteny and quantitative trait locus (QTL) browsers for exploring genetic data. Expression tools include an electronic fluorescent pictograph (eFP) browser, expression profile plots, co-regulation within collated transcriptomics data sets, and identification of over-represented functional categories and genomic hotspot locations. A number of collated transcriptomics data sets are made available in the eFP browser to facilitate functional exploration of gene function. Additional homology and data extraction tools are provided. PopGenIE significantly increases accessibility to Populus genomics resources and allows exploration of transcriptomics data without the need to learn or understand complex statistical analysis methods. PopGenIE is available at www.popgenie.org or via www.populusgenome.info.

Five QTL hotspots for yield in short rotation coppice bioenergy poplar: the Poplar Biomass Loci.

BACKGROUND: Concern over land use for non-food bioenergy crops requires breeding programmes that focus on producing biomass on the minimum amount of land that is economically-viable. To achieve this, the maximum potential yield per hectare is a key target for improvement. For long lived tree species, such as poplar, this requires an understanding of the traits that contribute to biomass production and their genetic control. An important aspect of this for long lived plants is an understanding of genetic interactions at different developmental stages, i.e. how genes or genetic regions impact on yield over time. RESULTS: QTL mapping identified regions of genetic control for biomass yield. We mapped consistent QTL across multiple coppice cycles and identified five robust QTL hotspots on linkage groups III, IV, X, XIV and XIX, calling these 'Poplar Biomass Loci' (PBL 1-5). In total 20% of the variation in final harvest biomass yield was explained by mapped QTL. We also investigated the genetic correlations between yield related traits to identify 'early diagnostic' indicators of yield showing that early biomass was a reasonable predictor of coppice yield and that leaf size, cell number and stem and sylleptic branch number were also valuable traits. CONCLUSION: These findings provide insight into the genetic control of biomass production and correlation to 'early diagnostic' traits determining yield in poplar SRC for bioenergy. QTL hotspots serve as useful targets for directed breeding for improved biomass productivity that may also be relevant across additional poplar hybrids.

A cross-species transcriptomics approach to identify genes involved in leaf development.

BACKGROUND: We have made use of publicly available gene expression data to identify transcription factors and transcriptional modules (regulons) associated with leaf development in Populus. Different tissue types were compared to identify genes informative in the discrimination of leaf and non-leaf tissues. Transcriptional modules within this set of genes were identified in a much wider set of microarray data collected from leaves in a number of developmental, biotic, abiotic and transgenic experiments. RESULTS: Transcription factors that were over represented in leaf EST libraries and that were useful for discriminating leaves from other tissues were identified, revealing that the C2C2-YABBY, CCAAT-HAP3 and 5, MYB, and ZF-HD families are particularly important in leaves. The expression of transcriptional modules and transcription factors was examined across a number of experiments to select those that were particularly active during the early stages of leaf development. Two transcription factors were found to collocate to previously published Quantitative Trait Loci (QTL) for leaf length. We also found that miRNA family 396 may be important in the control of leaf development, with three members of the family collocating with clusters of leaf development QTL. CONCLUSION: This work provides a set of candidate genes involved in the control and processes of leaf development. This resource can be used for a wide variety of purposes such as informing the selection of candidate genes for association mapping or for the selection of targets for reverse genetics studies to further understanding of the genetic control of leaf size and shape.

The genetics and genomics of the drought response in Populus.

The genetic nature of tree adaptation to drought stress was examined by utilizing variation in the drought response of a full-sib second generation (F(2)) mapping population from a cross between Populus trichocarpa (93-968) and P. deltoides Bart (ILL-129) and known to be highly divergent for a vast range of phenotypic traits. We combined phenotyping, quantitative trait loci (QTL) analysis and microarray experiments to demonstrate that 'genetical genomics' can be used to provide information on adaptation at the species level. The grandparents and F(2) population were subjected to soil drying, and contrasting responses to drought across genotypes, including leaf coloration, expansion and abscission, were observed, and QTL for these traits mapped. A subset of extreme genotypes exhibiting extreme sensitivity and insensitivity to drought on the basis of leaf abscission were defined, and microarray experiments conducted on these genotypes and the grandparent species. The extreme genotype groups induced a different set of genes: 215 and 125 genes differed in their expression response between groups in control and drought, respectively, suggesting species adaptation at the gene expression level. Co-location of differentially expressed genes with drought-specific and drought-responsive QTLs was examined, and these may represent candidate genes contributing to the variation in drought response.