Exploring the phenotypic expression of a regulatory proteome-altering geneby spectroscopy and chemometrics

Evaluating gene effects on proteomes and the resulting indirect pleiotropic effects through the cell machinery on the chemical phenotype constitutes a formidable challenge to the analytical chemist. This paper demonstrates th at near-infrared (NIR) spectroscopy and chemometrics on the level of the ba rley seed phenotype is able to differentiate between genetic and environmen tal effects in a PCA model involving normal barley lines and the gene regul ator lys3a in different genetic backgrounds. The gene drastically changes t he proteome quantitatively and qualitatively, as displayed in two-dimension al electrophoresis, resulting in a radically changed amino acid and chemica l composition. A synergy interval partial least squares regression model (s i-PLSR) is tested to select combinations of spectral segments which have a high correlation to defined chemical components indicative of the lys3a gen e, such as direct effects of the changed proteome, for example, the amide c ontent, or indirect effects due to changes in carbohydrate and fat composit ion. It is concluded that the redundancy of biological information on the D NA sequence level is also represented at the phenotypic level in the datase t read by the NIR spectroscopic sensor from the chemical physical fingerpri nt. The PLS algorithm chooses spectral intervals: which combine both direct and indirect proteome effects. This explains the robustness of NIR spectra l predictions by PLSR for a wide range of chemical components. The new opti on of using spectroscopy, analytical chemistry and chemometrics in modeling the genetically based covariance of physical/chemical fingerprints of the intact phenotype in plant breeding and biotechnology is discussed. (C) 2001 Elsevier Science B.V. All rights reserved.