Publications by authors named "Marina Oliva"

Germination involves highly dynamic transcriptional programs as the cells of seeds reactivate and express the functions necessary for establishment in the environment. Individual cell types have distinct roles within the embryo, so must therefore have cell type-specific gene expression and gene regulatory networks. We can better understand how the functions of different cell types are established and contribute to the embryo by determining how cell type-specific transcription begins and changes through germination.

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The construction of synthetic gene circuits in plants has been limited by a lack of orthogonal and modular parts. Here, we implement a CRISPR (clustered regularly interspaced short palindromic repeats) interference (CRISPRi)-based reversible gene circuit platform in plants. We create a toolkit of engineered repressible promoters of different strengths and construct NOT and NOR gates in Arabidopsis thaliana protoplasts.

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In recent years, single-cell genomics, coupled to imaging techniques, have become the state-of-the-art approach for characterising biological systems. In plant sciences, a variety of tissues and species have been profiled, providing an enormous quantity of data on cell identity at an unprecedented resolution, but what biological insights can be gained from such data sets? Using recently published studies in plant sciences, we will highlight how single-cell technologies have enabled a better comprehension of tissue organisation, cell fate dynamics in development or in response to various stimuli, as well as identifying key transcriptional regulators of cell identity. We discuss the limitations and technical hurdles to overcome, as well as future directions, and the promising use of single-cell omics to understand, predict, and manipulate plant development and physiology.

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Retrieving the complex responses of individual cells in the native three-dimensional tissue context is crucial for a complete understanding of tissue functions. Here, we present PHYTOMap (plant hybridization-based targeted observation of gene expression map), a multiplexed fluorescence in situ hybridization method that enables single-cell and spatial analysis of gene expression in whole-mount plant tissue in a transgene-free manner and at low cost. We applied PHYTOMap to simultaneously analyse 28 cell-type marker genes in Arabidopsis roots and successfully identified major cell types, demonstrating that our method can substantially accelerate the spatial mapping of marker genes defined in single-cell RNA-sequencing datasets in complex plant tissue.

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Recent years have seen an impressive increase in our knowledge of the topology of plant hormone signaling networks. The complexity of these topologies has motivated the development of models for several hormones to aid understanding of how signaling networks process hormonal inputs. Such work has generated essential insights into the mechanisms of hormone perception and of regulation of cellular responses such as transcription in response to hormones.

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Gravity profoundly influences plant growth and development. Plants respond to changes in orientation by using gravitropic responses to modify their growth. Cholodny and Went hypothesized over 80 years ago that plants bend in response to a gravity stimulus by generating a lateral gradient of a growth regulator at an organ's apex, later found to be auxin.

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Auxin is a key plant morphogenetic signal but tools to analyse dynamically its distribution and signalling during development are still limited. Auxin perception directly triggers the degradation of Aux/IAA repressor proteins. Here we describe a novel Aux/IAA-based auxin signalling sensor termed DII-VENUS that was engineered in the model plant Arabidopsis thaliana.

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The plant hormone auxin is thought to provide positional information for patterning during development. It is still unclear, however, precisely how auxin is distributed across tissues and how the hormone is sensed in space and time. The control of gene expression in response to auxin involves a complex network of over 50 potentially interacting transcriptional activators and repressors, the auxin response factors (ARFs) and Aux/IAAs.

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