High spatial resolution profiling in tree species

Until recently, the majority of genomics assays have been performed on bulk tissue samples containing multiple cell types. Tissues such as the wood formation zone in trees contain a complex mix of cell types organised in three-dimensional space. Moreover, cells within the wood formation zone represent a continual developmental progression from meristematic cambial initials through to cell death. This spatiotemporal developmental gradient and cell type information are not assayed by bulk samples. New and improved sampling methods coupled to next-generation sequencing assays are enabling the generation of high spatial resolution and single-cell transcriptomics data, offering unprecedented insight into the biology of unique cell types and cell developmental programs.We overview the application of these approaches to the study of wood development, in particular, and highlight challenges associated with the analysis of such data.
Export Date: 8 September 2021; Article; Funding details: FR-2017/0009; Funding details: VINNOVA; Funding details: Knut och Alice Wallenbergs Stiftelse; Funding text 1: S.G. is supported by Formas Research Council grant FR-2017/0009. N.R.S. is supported by the Trees and Crop for the Future (TC4F) project. T.N. is supported by the Bio4Energy project. H.T., N.R.S., T.N. and N.D. acknowledge funding support from Vinnova (the Swedish Governmental Agency for Innovation Systems) and KAW (The Knut and Alice Wallenberg Foundation). We thank Juan Inda (Chalmers) and Dr Saeed Omidi (Sophia Genetics) for insightful discussion regarding single-cell computational challenges.; Funding text 2: S.G. is supported by Formas Research Council grant FR-2017/0009. N.R.S. is supported by the Trees and Crop for the Future (TC4F) project. T.N. is supported by the Bio4Energy project. H.T., N.R.S., T.N. and N.D. acknowledge funding support from Vinnova (the Swedish Governmental Agency for Innovation Systems) and KAW(The Knut and AliceWallenberg Foundation). We thank Juan Inda (Chalmers) and Dr Saeed Omidi (Sophia Genetics) for insightful discussion regarding single-cell computational challenges. QC 20210915