The application of fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes

Brown CW1, Grof CPL1 and Martin AP2

  1. Centre for Plant Science, School of Environmental and Life Sciences, University of Newcastle, University Drive, Callaghan, NSW 2308, Australia.
  2. Rapid Phenotyping, 9 Gipps St, Carrington, NSW, 2294, Australia.

Cell wall composition in monocotyledonous grasses has been identified as a key area of research for developing better feedstocks for forage and biofuel production. Setaria viridis and its close domesticated relative Setaria italica, have been chosen as suitable monocotyledonous models for more economically significant plants possessing the C4 pathway of photosynthesis including sorghum, maize, sugarcane, switchgrass and Miscanthus x giganteus. Accurate Partial Least Squares Regression (PLSR) models to predict S. italica cell wall composition in stem tissue have been generated, based upon Fourier transform mid-Infrared (FTIR) spectra and calibrated with wet chemistry determinations of ground S. italica stem material measured using a modified version of the US National Renewable Energy Laboratory (NREL) two stage acid hydrolysis protocol. The models facilitated a high-throughput screening analysis for glucan, xylan, Klason lignin and acid soluble lignin in a collection of 183 natural S. italicavariants and clustered them into classes, some possessing unique cell wall chemotypes. Genes encoding key catalytic enzymes of the lignin biosynthesis pathway were compared from different developmental regions within an elongating stem internode in selected S. italica variants. A high level of conservation with matching expression profiles between selected variants was evident. Expression in S. italica was determined by quantitative reverse transcription polymerase chain reaction (RT-qPCR), and closely mirrored expression profiles of homologous genes in equivalent developmental regions of elongating internodes of S. viridis by RNASeq.