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Background: Second generation (2G) bioenergy from lignocellulosic feedstocks has the potential to develop as a sustainable source of renewable energy; however, significant hurdles still remain for large-scale commercialisation. Populus is considered as a promising 2G feedstock and understanding the genetic basis of biomass yield and feedstock quality are a research priority in this model tree species. Results: We report the first coppiced biomass study for 714 members of a wide population of European black poplar (Populus nigra L.), a native European tree, selected from 20 river populations ranging in latitude and longitude between 40.5 and 52.1°N and 1.0 and 16.4°E, respectively. When grown at a single site in southern UK, significant Site of Origin (SO) effects were seen for 14 of the 15 directly measured or derived traits including biomass yield, leaf area and stomatal index. There was significant correlation (p < 0.001) between biomass yield traits over 3 years of harvest which identified leaf size and cell production as strong predictors of biomass yield. A 12 K Illumina genotyping array (constructed from 10,331 SNPs in 14 QTL regions and 4648 genes) highlighted significant population genetic structure with pairwise FST showing strong differentiation (p < 0.001) between the Spanish and Italian subpopulations. Robust associations reaching genome-wide significance are reported for main stem height and cell number per leaf; two traits tightly linked to biomass yield. These genotyping and phenotypic data were also used to show the presence of significant isolation by distance (IBD) and isolation by adaption (IBA) within this population. Conclusions: The three associations identified reaching genome-wide significance at p < 0.05 include a transcription factor; a putative stress response gene and a gene of unknown function. None of them have been previously linked to bioenergy yield; were shown to be differentially expressed in a panel of three selected genotypes from the collection and represent exciting, novel candidates for further study in a bioenergy tree native to Europe and Euro-Asia. A further 26 markers (22 genes) were found to reach putative significance and are also of interest for biomass yield, leaf area, epidermal cell expansion and stomatal patterning. This research on European P. nigra provides an important foundation for the development of commercial native trees for bioenergy and for advanced, molecular breeding in these species. [ABSTRACT FROM AUTHOR]

Background: Consuming watercress is thought to provide health benefits as a consequence of its phytonutrient composition. However, for watercress there are currently limited genetic resources underpinning breeding efforts for either yield or phytonutritional traits. In this paper, we use RNASeq data from twelve watercress accessions to characterize the transcriptome, perform candidate gene mining and conduct differential expression analysis for two key phytonutritional traits: antioxidant (AO) capacity and glucosinolate (GLS) content. Results: The watercress transcriptome was assembled to 80,800 transcripts (48,732 unigenes); 71 % of which were annotated based on orthology to Arabidopsis. Differential expression analysis comparing watercress accessions with 'high' and 'low' AO and GLS resulted in 145 and 94 differentially expressed loci for AO capacity and GLS respectively. Differentially expressed loci between high and low AO watercress were significantly enriched for genes involved in plant defence and response to stimuli, in line with the observation that AO are involved in plant stress-response. Differential expression between the high and low GLS watercress identified links to GLS regulation and also novel transcripts warranting further investigation. Additionally, we successfully identified watercress orthologs for Arabidopsis phenylpropanoid, GLS and shikimate biosynthesis pathway genes, and compiled a catalogue of polymorphic markers for future applications. Conclusions: Our work describes the first transcriptome of watercress and establishes the foundation for further molecular study by providing valuable resources, including sequence data, annotated transcripts, candidate genes and markers. [ABSTRACT FROM AUTHOR]

Background: There is an increasing demand for renewable resources to replace fossil fuels. However, different applications such as the production of secondary biofuels or combustion for energy production require different wood properties. Therefore, high-throughput methods are needed for rapid screening of wood in large scale samples, e.g., to evaluate the outcome of tree breeding or genetic engineering. In this study, we investigated the intra-specific variability of lignin and energy contents in extractive-free wood of hybrid poplar progenies (Populus trichocarpa × deltoides) and tested if the range was sufficient for the development of quantitative prediction models based on Fourier transform infrared spectroscopy (FTIR). Since lignin is a major energy-bearing compound, we expected that the energy content of wood would be positively correlated with the lignin content. Results: Lignin contents of extractive-free poplar wood samples determined by the acetyl bromide method ranged from 23.4% to 32.1%, and the calorific values measured with a combustion calorimeter varied from 17260 to 19767 J g-1. For the development of calibration models partial least square regression and cross validation was applied to correlate FTIR spectra determined with an attenuated total reflectance (ATR) unit to measured values of lignin or energy contents. The best models with high coefficients of determination (R² (calibration) = 0.91 and 0.90; R² (crossvalidation) = 0.81 and 0.79) and low root mean square errors of cross validation (RMSECV = 0.77% and 62 J g-1) for lignin and energy determination, respectively, were obtained after data pre-processing and automatic wavenumber restriction. The calibration models were validated by analyses of independent sets of wood samples yielding R² = 0.88 and 0.86 for lignin and energy contents, respectively. Conclusions: These results show that FTIR-ATR spectroscopy is suitable as a high-throughput method for lignin and energy estimations in large data sets. Our study revealed that the intra-specific variations in lignin and energy contents were unrelated to each other and that the lignin content, therefore, was no predictor of the energy content. Employing principle component analyses we showed that factor loadings for the energy content were mainly associated with carbohydrate ring vibrations, whereas those for lignin were mainly related to aromatic compounds. Therefore, our analysis suggests that it may be possible to optimize the energy content of trees without concomitant increase in lignin. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: There is an increasing demand for renewable resources to replace fossil fuels. However, different applications such as the production of secondary biofuels or combustion for energy production require different wood properties. Therefore, high-throughput methods are needed for rapid screening of wood in large scale samples, e.g., to evaluate the outcome of tree breeding or genetic engineering. In this study, we investigated the intra-specific variability of lignin and energy contents in extractive-free wood of hybrid poplar progenies (Populus trichocarpa × deltoides) and tested if the range was sufficient for the development of quantitative prediction models based on Fourier transform infrared spectroscopy (FTIR). Since lignin is a major energy-bearing compound, we expected that the energy content of wood would be positively correlated with the lignin content., Results: Lignin contents of extractive-free poplar wood samples determined by the acetyl bromide method ranged from 23.4% to 32.1%, and the calorific values measured with a combustion calorimeter varied from 17260 to 19767 J g-1. For the development of calibration models partial least square regression and cross validation was applied to correlate FTIR spectra determined with an attenuated total reflectance (ATR) unit to measured values of lignin or energy contents. The best models with high coefficients of determination (R2 (calibration) = 0.91 and 0.90; R2 (cross-validation) = 0.81 and 0.79) and low root mean square errors of cross validation (RMSECV = 0.77% and 62 J g-1) for lignin and energy determination, respectively, were obtained after data pre-processing and automatic wavenumber restriction. The calibration models were validated by analyses of independent sets of wood samples yielding R2 = 0.88 and 0.86 for lignin and energy contents, respectively., Conclusions: These results show that FTIR-ATR spectroscopy is suitable as a high-throughput method for lignin and energy estimations in large data sets. Our study revealed that the intra-specific variations in lignin and energy contents were unrelated to each other and that the lignin content, therefore, was no predictor of the energy content. Employing principle component analyses we showed that factor loadings for the energy content were mainly associated with carbohydrate ring vibrations, whereas those for lignin were mainly related to aromatic compounds. Therefore, our analysis suggests that it may be possible to optimize the energy content of trees without concomitant increase in lignin.

Background: This work explores the potential contribution of bioenergy technologies to 60% and 80% carbon reductions in the UK energy system by 2050, by outlining the potential for accelerated technological development of bioenergy chains. The investigation was based on insights from MARKAL modelling, detailed literature reviews and expert consultations. Due to the number and complexity of bioenergy pathways and technologies in the model, three chains and two underpinning technologies were selected for detailed investigation: (1) lignocellulosic hydrolysis for the production of bioethanol, (2) gasification technologies for heat and power, (3) fast pyrolysis of biomass for bio-oil production, (4) biotechnological advances for second generation bioenergy crops, and (5) the development of agro-machinery for growing and harvesting bioenergy crops. Detailed literature searches and expert consultations (looking inter alia at research and development needs and economic projections) led to the development of an 'accelerated' dataset of modelling parameters for each of the selected bioenergy pathways, which were included in five different scenario runs with UK-MARKAL (MED). The results of the 'accelerated runs' were compared with a low-carbon (LC-Core) scenario, which assesses the cheapest way to decarbonise the energy sector., Results: Bioenergy was deployed in larger quantities in the bioenergy accelerated technological development scenario compared with the LC-Core scenario. In the electricity sector, solid biomass was highly utilised for energy crop gasification, displacing some deployment of wind power, and nuclear and marine to a lesser extent. Solid biomass was also deployed for heat in the residential sector from 2040 in much higher quantities in the bioenergy accelerated technological development scenario compared with LC-Core. Although lignocellulosic ethanol increased, overall ethanol decreased in the transport sector in the bioenergy accelerated technological development scenario due to a reduction in ethanol produced from wheat., Conclusion: There is much potential for future deployment of bioenergy technologies to decarbonise the energy sector. However, future deployment is dependent on many different factors including investment and efforts towards research and development needs, carbon reduction targets and the ability to compete with other low carbon technologies as they become deployed. All bioenergy technologies should become increasingly more economically competitive with fossil-based technologies as feedstock costs and flexibility are reduced in line with technological advances.