Identification of crop cultivars with consistently high lignocellulosic sugar release requires the use of appropriate statistical design and modelling

Natural variation in HvAT10 underlies grain cell wall-esterified phenolic acid content in cultivated barley

The phenolic acids, ferulic acid and p-coumaric acid, are components of plant cell walls in grasses, including many of our major food crops. They have important health-promoting properties in grain, and influence the digestibility of biomass for industrial processing and livestock feed. Both phenolic acids are assumed to be critical to cell wall integrity and ferulic acid, at least, is important for cross-linking cell wall components, but the role of p-coumaric acid is unclear. Here we identify alleles of a BAHD p-coumaroyl arabinoxylan transferase, HvAT10, as responsible for the natural variation in cell wall-esterified phenolic acids in whole grain within a cultivated two-row spring barley panel. We show that HvAT10 is rendered non-functional by a premature stop codon mutation in half of the genotypes in our mapping panel. This results in a dramatic reduction in grain cell wall-esterifed p-coumaric acid, a moderate rise in ferulic acid, and a clear increase in the ferulic acid to p-coumaric acid ratio. The mutation is virtually absent in wild and landrace germplasm suggesting an important function for grain arabinoxylan p-coumaroylation pre-domestication that is dispensable in modern agriculture. Intriguingly, we detected detrimental impacts of the mutated locus on grain quality traits where it was associated with smaller grain and poorer malting properties. HvAT10 could be a focus for improving grain quality for malting or phenolic acid content in wholegrain foods.

Downregulation of barley ferulate 5-hydroxylase dramatically alters straw lignin structure without impact on mechanical properties

Barley is a major cereal crop for temperate climates, and a diploid genetic model for polyploid wheat. Cereal straw biomass is an attractive source of feedstock for green technologies but lignin, a key determinant of feedstock recalcitrance, complicates bio-conversion processes. However, manipulating lignin content to improve the conversion process could negatively affect agronomic traits. An alternative approach is to manipulate lignin composition which influences the physical and chemical properties of straw. This study validates the function of a barley ferulate 5-hydroxylase gene and demonstrates that its downregulation using the RNA-interference approach substantially impacts lignin composition. We identified five barley genes having putative ferulate 5-hydroxylase activity. Downregulation of HvF5H1 substantially reduced the lignin syringyl/guaiacyl (S/G) ratio in straw while the lignin content, straw mechanical properties, plant growth habit, and grain characteristics all remained unaffected. Metabolic profiling revealed significant changes in the abundance of 173 features in the HvF5H1-RNAi lines. The drastic changes in the lignin polymer of transgenic lines highlight the plasticity of barley lignification processes and the associated potential for manipulating and improving lignocellulosic biomass as a feedstock for green technologies. On the other hand, our results highlight some differences between the lignin biosynthetic pathway in barley, a temperate climate grass, and the warm climate grass, rice, and underscore potential diversity in the lignin biosynthetic pathways in grasses.

Association mapping identifies quantitative trait loci (QTL) for digestibility in rice straw

BACKGROUND

The conversion of lignocellulosic biomass from agricultural waste into biofuels and chemicals is considered a promising way to provide sustainable low carbon products without compromising food security. However, the use of lignocellulosic biomass for biofuel and chemical production is limited by the cost-effectiveness of the production process due to its recalcitrance to enzymatic hydrolysis and fermentable sugar release (i.e., saccharification). Rice straw is a particularly attractive feedstock because millions of tons are currently burned in the field each year for disposal. The aim of this study was to explore the underlying natural genetic variation that impacts the recalcitrance of rice (Oryza sativa) straw to enzymatic saccharification. Ultimately, we wanted to investigate whether we could identify genetic markers that could be used in rice breeding to improve commercial cultivars for this trait. Here, we describe the development and characterization of a Vietnamese rice genome-wide association panel, high-throughput analysis of rice straw saccharification and lignin content, and the results from preliminary genome-wide association studies (GWAS) of the combined data sets. We identify both QTL and plausible candidate genes that may have an impact on the saccharification of rice straw.

RESULTS

We assembled a diversity panel comprising 151 rice genotypes (Indica and Japonica types) from commercial, historical elite cultivars, and traditional landraces grown in Vietnam. The diversity panel was genotyped using genotype by sequencing (GBS) methods yielding a total of 328,915 single nucleotide polymorphisms (SNPs). We collected phenotypic data from stems of these 151 genotypes for biomass saccharification and lignin content. Using GWAS on the indica genotypes over 2 years we identified ten significant QTL for saccharification (digestibility) and seven significant QTL for lignin. One QTL on chromosome 11 occurred in both GWAS for digestibility and for lignin. Seven QTL for digestibility, on CH2, CH6, CH7, CH8, and CH11, were observed in both years of the study. The QTL regions for saccharification include three potential candidate genes that have been previously reported to influence digestibility: OsAT10; OsIRX9; and OsMYB58/63-L.

CONCLUSIONS

Despite the difficulties associated with multi-phasic analysis of complex traits in novel germplasm, a moderate resolution GWAS successfully identified genetic associations encompassing both known and/or novel genes involved in determining the saccharification potential and lignin content of rice straw. Plausible candidates within QTL regions, in particular those with roles in cell wall biosynthesis, were identified but will require validation to confirm their value for application in rice breeding.

Breeding for dual-purpose wheat varieties using marker-trait associations for biomass yield and quality traits

This study demonstrates that an active breeding nursery with rotation can be used to identify marker-trait associations for biomass yield and quality parameters that are important for biorefinery purposes. Wheat straw is a valuable feedstock for bioethanol production, but due to the recalcitrant nature of lignocellulose, its efficient use in biorefineries is limited by its low digestibility and difficult conversion of structural carbohydrates into free sugars. A genome-wide association study (GWAS) was conducted to search for significant SNP markers that could be used in a breeding programme to improve the value of wheat straw in a biorefinery setting. As part of a 3-year breeding programme (2013-2016), 190 winter wheat lines were phenotyped for traits that affect the yield and quality of the harvested biomass. These traits included straw yield, plant height, lodging at three growth stages and Septoria tritici blotch (STB) susceptibility. Release of glucose, xylose and arabinose was determined after hydrothermal pretreatment and enzymatic hydrolysis of the straw. The lines were genotyped using 15 K SNP markers and 5552 SNP markers could be used after filtering. Heritability for all traits ranged from 0.02 to 0.74. GWASs were conducted using CMLM, SUPER and FarmCPU algorithms, to analyse which algorithm could detect the highest number of marker-trait associations (MTAs). Comparable tendencies were obtained from CMLM and FarmCPU, but FarmCPU produced the most significant results. MTAs were obtained for lodging, harvest index, plant height, STB, glucose, xylose and arabinose at a significance level of p < 9.01 × 10^-6. MTAs in chromosome 6A were observed for glucose, xylose and arabinose, and could be of importance for increasing sugar release for bioethanol production.

Genetic variation of biomass recalcitrance in a natural Salix viminalis (L.) population

BACKGROUND

Salix spp. are high-productivity crops potentially used for lignocellulosic biofuels such as bioethanol. In general, pretreatment is needed to facilitate the enzymatic depolymerization process. Biomass resistance to degradation, i.e., biomass recalcitrance, is a trait which can be assessed by measuring the sugar released after combined pretreatment and enzymatic hydrolysis. We have examined genetic parameters of enzymatic sugar release and other traits related to biorefinery use in a population of 286 natural Salix viminalis clones. Furthermore, we have evaluated phenotypic and genetic correlations between these traits and performed a genomewide association mapping analysis using a set of 19,411 markers.

RESULTS

Sugar release (glucose and xylose) after pretreatment and enzymatic saccharification proved highly variable with large genetic and phenotypic variations, and chip heritability estimates (h 2) of 0.23-0.29. Lignin syringyl/guaiacyl (S/G) ratio and wood density were the most heritable traits (h 2 = 0.42 and 0.59, respectively). Sugar release traits were positively correlated, phenotypically and genetically, with biomass yield and lignin S/G ratio. Association mapping revealed seven marker-trait associations below a suggestive significance threshold, including one marker associated with glucose release.

CONCLUSIONS

We identified lignin S/G ratio and shoot diameter as heritable traits that could be relatively easily evaluated by breeders, making them suitable proxy traits for developing low-recalcitrance varieties. One marker below the suggestive threshold for marker associations was identified for sugar release, meriting further investigation while also highlighting the difficulties in employing genomewide association mapping for complex traits.

Biomass recalcitrance in barley, wheat and triticale straw: Correlation of biomass quality with classic agronomical traits

The global production of cereal straw as an agricultural by-product presents a significant source of biomass, which could be used as feedstock for the production of second generation biofuels by fermentation. The production of sugars for fermentation is an important measure of straw quality and in its suitability for biofuel production. In this paper, we present a characterization of straw digestibility from a wide range of cereal. Our main objective is to evaluate the variability of fermentable sugars released from different species including wheat (Triticum durum L., Triticum aestivum L.), barley (Hordeum vulgare L.) and triticale (X Triticosecale Wittmack). To this end, we adapted a saccharification method (IAS Method) capable of detecting significant differences of released sugars between cultivars and species, while using separately another method that would serve as a control and with which we could contrast our results (CNAP method). ANOVA analyses revealed that barley has a higher saccharification potential than wheat and triticale and shows more variation between genotypes. Thus, populations derived from crosses among them such as Steptoe × Morex and OWB Dominant × OWB Recessive hold potential for the identification of genetic basis for saccharification-related traits. The correlation of glucose released between the two methods was moderate (R2 = 0.57). An evaluation of the inter- and intra- specific correlation between a number of chemical and agronomical parameters and saccharification suggests that the cell wall thickness and lignin content in straw could be used in breeding programs for the improvement of the saccharification potential. Finally, the lack of correlation between grain yield and saccharification suggests that it would be possible to make a selection of genotypes for dual purpose, low recalcitrance and grain yield.

Genomic Selection in Multi-environment Crop Trials

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers.

Genomic Selection in Multi-environment Crop Trials

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers.

Association Mapping in Scandinavian Winter Wheat for Yield, Plant Height, and Traits Important for Second-Generation Bioethanol Production

A collection of 100 wheat varieties representing more than 100 years of wheat-breeding history in Scandinavia was established in order to identify marker-trait associations for plant height (PH), grain yield (GY), and biomass potential for bioethanol production. The field-grown material showed variations in PH from 54 to 122 cm and in GY from 2 to 6.61 t ha(-1). The release of monomeric sugars was determined by high-throughput enzymatic treatment of ligno-cellulosic material and varied between 0.169 and 0.312 g/g dm for glucose (GLU) and 0.146 and 0.283 g/g dm for xylose (XYL). As expected, PH and GY showed to be highly influenced by genetic factors with repeatability (R) equal to 0.75 and 0.53, respectively, while this was reduced for GLU and XYL (R = 0.09 for both). The study of trait correlations showed how old, low-yielding, tall varieties released higher amounts of monomeric sugars after straw enzymatic hydrolysis, showing reduced recalcitrance to bioconversion compared to modern varieties. Ninety-three lines from the collection were genotyped with the DArTseq(®) genotypic platform and 5525 markers were used for genome-wide association mapping. Six quantitative trait loci (QTLs) for GY, PH, and GLU released from straw were mapped. One QTL for PH was previously reported, while the remaining QTLs constituted new genomic regions linked to trait variation. This paper is one of the first studies in wheat to identify QTLs that are important for bioethanol production based on a genome-wide association approach.

Cell-wall properties contributing to improved deconstruction by alkaline pre-treatment and enzymatic hydrolysis in diverse maize (Zea mays L.) lines

A maize (Zea mays L. subsp. mays) diversity panel consisting of 26 maize lines exhibiting a wide range of cell-wall properties and responses to hydrolysis by cellulolytic enzymes was employed to investigate the relationship between cell-wall properties, cell-wall responses to mild NaOH pre-treatment, and enzymatic hydrolysis yields. Enzymatic hydrolysis of the cellulose in the untreated maize was found to be positively correlated with the water retention value, which is a measure of cell-wall susceptibility to swelling. It was also positively correlated with the lignin syringyl/guaiacyl ratio and negatively correlated with the initial cell-wall lignin, xylan, acetate, and p-coumaric acid (pCA) content, as well as pCA released from the cell wall by pre-treatment. The hydrolysis yield following pre-treatment exhibited statistically significant negative correlations to the lignin content after pre-treatment and positive correlations to the solubilized ferulic acid and pCA. Several unanticipated results were observed, including a positive correlation between initial lignin and acetate content, lack of correlation between acetate content and initial xylan content, and negative correlation between each of these three variables to the hydrolysis yields for untreated maize. Another surprising result was that pCA release was negatively correlated with hydrolysis yields for untreated maize and, along with ferulic acid release, was positively correlated with the pre-treated maize hydrolysis yields. This indicates that these properties that may negatively contribute to the recalcitrance in untreated cell walls may positively contribute to their deconstruction by alkaline pre-treatment.

Methodology for enabling high-throughput simultaneous saccharification and fermentation screening of yeast using solid biomass as a substrate

BACKGROUND

High-throughput (HTP) screening is becoming an increasingly useful tool for collating biological data which would otherwise require the employment of excessive resources. Second generation biofuel production is one such process. HTP screening allows the investigation of large sample sets to be undertaken with increased speed and cost effectiveness. This paper outlines a methodology that will enable solid lignocellulosic substrates to be hydrolyzed and fermented at a 96-well plate scale, facilitating HTP screening of ethanol production, whilst maintaining repeatability similar to that achieved at a larger scale.

RESULTS

The results showed that utilizing sheets of biomass of consistent density (handbills), for paper, and slurries of pretreated biomass that could be pipetted allowed standardized and accurate transfers to 96-well plates to be achieved (±3.1 and 1.7%, respectively). Processing these substrates by simultaneous saccharification and fermentation (SSF) at various volumes showed no significant difference on final ethanol yields, either at standard shake flask (200 mL), universal bottle (10 mL) or 96-well plate (1 mL) scales. Substrate concentrations of up to 10% (w/v) were trialed successfully for SSFs at 1 mL volume. The methodology was successfully tested by showing the effects of steam explosion pretreatment on both oilseed rape and wheat straws.

CONCLUSIONS

This methodology could be used to replace large shake flask reactions with comparatively fast 96-well plate SSF assays allowing for HTP experimentation. Additionally this method is compatible with a number of standardized assay techniques such as simple colorimetric, High-performance liquid chromatography (HPLC) and Nuclear magnetic resonance (NMR) spectroscopy. Furthermore this research has practical uses in the biorefining of biomass substrates for second generation biofuels and novel biobased chemicals by allowing HTP SSF screening, which should allow selected samples to be scaled up or studied in more detail.