Guidelines for Sample Normalization to Minimize Batch Variation for Large-Scale Metabolic Profiling of Plant Natural Genetic Variance

Methods in Molecular Biology
Saleh AlseekhAlisdair R Fernie

Abstract

Recent methodological advances in both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) have facilitated the profiling highly complex mixtures of primary and secondary metabolites in order to investigate a diverse range of biological questions. These techniques usually face a large number of potential sources of technical and biological variation. In this chapter we describe guidelines and normalization procedures to reduce the analytical variation, which are essential for the high-throughput evaluation of metabolic variance used in broad genetic populations which commonly entail the evaluation of hundreds or thousands of samples. This chapter specifically deals with handling of large-scale plant samples for metabolomics analysis of quantitative trait loci (mQTL) in order to reduce analytical error as well as batch-to-batch variation.

Citations

Apr 29, 2020·Current Protocols in Plant Biology·Taly Lapidot-CohenYariv Brotman
Nov 27, 2019·Metabolites·Ana M RodriguesCarla António
Sep 10, 2019·Mass Spectrometry Reviews·Ana Margarida RodriguesCarla António

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