QTL Mapping of Wood FT-IR Chemotypes Shows Promise for Improving Biofuel Potential in Short Rotation Coppice Willow (Salix spp.)

• Published in: Bioenergy research 2018-06, Vol.11 (2), p.351-363
• Main Authors: Pawar, Prashant Mohan-Anupama, Schnürer, Anna, Mellerowicz, Ewa J., Rönnberg-Wästljung, Ann Christin
• Format: Article
• Language: English
• Subjects: Analysis; Biodiesel fuels; Bioenergi; Bioenergy; Biofuels; Biogas; Biomass; Biomass energy; Biomedical and Life Sciences; Breeding; Cellulose; Content analysis; Coppicing; Fuels; G ratio; Gene loci; Gene mapping; Genes; Genetic diversity; Genomics; Genotype & phenotype; Hemicellulose; Infrared analysis; Infrared spectroscopy; Life Sciences; Lignin; Lignocellulose; Mapping; Moisture content; Phenotypic variations; Phenotyping; Plant Breeding/Biotechnology; Plant Ecology; Plant Genetics and Genomics; Plant Sciences; Quantitative genetics; Quantitative trait loci; Salix viminalis; Spectrometry; Water content; Willow; Wood Science & Technology
• ISSN: 1939-1234; 1939-1242; 1939-1242
• DOI: 10.1007/s12155-018-9901-8

An increasing interest to convert lignocellulosic biomass into biofuels has highlighted the potential of using willows for this purpose, due to its fast growth in short rotation coppice systems. Here, we use a mapping population of 463 individuals of a cross between Salix viminalis and S. viminalis × S. schwerinii to investigate the genetic background of different wood chemical traits, information of importance for breeding towards different uses of wood. Furthermore, using a subset of the mapping population, the correlation between biogas production and chemical traits was investigated. The phenotyping of wood was carried by Furrier-transformed-Infrared spectrometry (FT-IR) and water content analysis. Quantitative trait loci (QTLs) analysis was used to identify regions in the genome of importance for the phenotypic variation of these chemical traits. We found 27 QTLs for various traits. On linkage group (LG) VI-1, QTLs for signals assigned to G-lignin, lignin, and the S/G ratio were collocated and on LG XIV we found a cluster of QTLs representing signals assigned to lignin, cellulose, hemicellulose, and water. The QTLs explained from 3.4 to 6.9% of the phenotypic variation indicating a quantitative genetic background where many genes influence the traits. For the biogas production, a positive and negative correlation was seen with the signals assigned to acetyl and lignin, respectively. This study represents a first step in the understanding of the genetic background of wood chemical traits for willows, information needed for complementary studies, mapping of important genes, and for breeding of varieties for biofuel production purposes.