Accurate Determination of Genotypic Variance of Cell Wall Characteristics of a Populus trichocarpa Pedigree Using High-Throughput Pyrolysis-Molecular Beam Mass Spectrometry

Abstract

Background Pyrolysis-molecular beam mass spectrometry (py-MBMS) analysis of a pedigree of Populus trichocarpa was performed to study the phenotypic plasticity and heritability of lignin content and lignin monomer composition. Instrumental and microspatial environmental variability were observed in the spectral features and corrected to reveal underlying genetic variance of biomass composition. Results Lignin-derived ions were highly impacted by microspatial environmental variation which demonstrates phenotypic plasticity of lignin composition in Populus trichocarpa biomass. Broad-sense heritability of lignin composition after correcting for microspatial and instrumental variation was determined to be H2 = 0.56 based on py-MBMS based on ions known to derive from lignin. Heritability of lignin monomeric syringyl/guaiacyl ratio (S/G) was H2 = 0.81. Broad-sense heritability was also high (up to H2 = 0.79) for ions derived from other components of the biomass including phenolics (e.g., salicylates) and C5 sugars (e.g., xylose). Lignin and phenolic ion abundances were primarily driven by maternal effects, and paternal effects were either similar or stronger for the most heritable carbohydrate-derived ions. Conclusions We have shown that many biopolymer-derived ions from py-MBMS show substantial phenotypic plasticity in response to microenvironmental variation in plantations. Nevertheless, broad-sense heritability for biomass composition can be quite high after correcting for spatial environmental variation. This work outlines the importance in accounting for instrumental and microspatial environmental variation in biomass composition data for applications in heritability measurements and genomic selection for breeding poplar for renewable fuels and materials.

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

“…As shown in the PCA scores plot in Figure 1 and similarly to that reported previously [ 1 , 2 , 7 , 9 , 28 ], samples cluster according to primary biomass type (family, being hardwood, softwood, or grasses) based on their spectra prior to RUV correction (instrument drift correction) from m / z 30–450 and to a lesser degree, secondary biomass type (species) and Sample ID. The first principal component (x-axis), as outlined before, generally separates the biomass types according to relative lignin and sugar abundance.…”

“…The underlying assumptions of normalizing large datasets across different instruments for RNAseq are applicable to py-MBMS analysis: (1) data are complex and contain replicates; (2) there are differences in sample loadings; (3) occurrence of operator technician variation. Normalization strategies for py-MBMS have traditionally included reference standards from NIST and internal controls, but they typically fail to account for instrument drift across time or space and thus can only be comparable within runs, although we have previously reported one different type of correction or normalization strategy [ 28 ]. Similar limitations occur across RNA sequencing runs, which vary in library depth, preparation, and reagent quality.…”

Sequencing and Analysis of the Sex Determination Region of Populus trichocarpa

“…Three half-sib families of male parents from a half-diallel designed cross (7 × 7) were used to generate three genetic maps [ 32 ]. A similar protocol as described above was used to call variants.…”

Comparison of Methodologies used to Determine Aromatic Lignin Unit Ratios in Lignocellulosic Biomass

“…Pyrolysis or thermal degradative methods coupled with chromatographic and/or mass spectrometry techniques can be performed on minimally processed biomass, yield highly reproducible results, and can be used in high-throughput platforms to analyze lignin content and composition in biomass [3,[29][30][31][32][33].…”