hybridization based on the mechanism of the hybridization chain reaction (HCR) has addressed multi-decade challenges that impeded imaging of mRNA expression in diverse organisms, offering a unique combination of multiplexing, quantitation, sensitivity, resolution and versatility. Here, with third-generation HCR, we augment these capabilities using probes and amplifiers that combine to provide automatic background suppression throughout the protocol, ensuring that reagents will not generate amplified background even if they bind non-specifically within the sample. Automatic background suppression dramatically enhances performance and robustness, combining the benefits of a higher signal-to-background ratio with the convenience of using unoptimized probe sets for new targets and organisms. HCR v3.0 enables three multiplexed quantitative analysis modes: (1) qHCR imaging - analog mRNA relative quantitation with subcellular resolution in the anatomical context of whole-mount vertebrate embryos; (2) qHCR flow cytometry - analog mRNA relative quantitation for high-throughput expression profiling of mammalian and bacterial cells; and (3) dHCR imaging - digital mRNA absolute quantitation via single-molecule imaging in thick autofluorescent samples.

In situ hybridization based on the mechanism of hybridization chain reaction (HCR) has addressed multi-decade challenges to imaging mRNA expression in diverse organisms, offering a unique combination of multiplexing, quantitation, sensitivity, resolution, and versatility. Here, with third-generation in situ HCR, we augment these capabilities using probes and amplifiers that combine to provide automatic background suppression throughout the protocol, ensuring that even if reagents bind non-specifically within the sample they will not generate amplified background. Automatic background suppression dramatically enhances performance and robustness, combining the benefits of higher signal-to-background with the convenience of using unoptimized probe sets for new targets and organisms. In situ HCR v3.0 enables multiplexed quantitative mRNA imaging with subcellular resolution in the anatomical context of whole-mount vertebrate embryos, multiplexed quantitative mRNA flow cytometry for high-throughput single-cell expression profiling, and multiplexed quantitative single-molecule mRNA imaging in thick autofluorescent samples.KEYWORDS: in situ HCR v3.0, qHCR imaging, qHCR flow cytometry, dHCR imaging, multiplexed in situ hybridization, quantitative in situ hybridization, single-molecule mRNA imaging, mRNA flow cytometry, whole-mount vertebrate embryos, mammalian cells, bacterial cells, split-initiator probes, automatic background suppression.

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SUMMARYThe formation of cellular patterns during development requires the coordination of cell division with cell identity specification. This coordination is essential in patterning the highly elongated giant cells, which are interspersed between small cells, in the outer epidermis of the Arabidopsis thaliana sepal. Giant cells undergo endocycles, replicating their DNA without dividing, whereas small cells divide mitotically. We show that distinct enhancers are expressed in giant cells and small cells, indicating that these cell types have different identities as well as different sizes. We find that members of the epidermal specification pathway, DEFECTIVE KERNEL1 (DEK1), MERISTEM LAYER1 (ATML1), Arabidopsis CRINKLY4 (ACR4) and HOMEODOMAIN GLABROUS11 (HDG11), control the identity of giant cells. Giant cell identity is established upstream of cell cycle regulation. Conversely, endoreduplication represses small cell identity. These results show not only that cell type affects cell cycle regulation, but also that changes in the cell cycle can regulate cell type. KEY WORDS: Epidermal specification, Giant cell, EndoreduplicationCell cycle regulates cell type in the Arabidopsis sepal MATERIALS AND METHODS Enhancer trap markersOne marker from the Poethig collection of enhancer trap lines expressed in the flowers (ABRC stock number CS70134) showed the small cell expression pattern. The giant cell marker is enhancer trap line YJ158 from the Bowman collection (Eshed et al., 2004).

Stem cells are responsible for organogenesis, but it is largely unknown whether and how information from stem cells acts to direct organ patterning after organ primordia are formed. It has long been proposed that the stem cells at the plant shoot apex produce a signal, which promotes leaf adaxial-abaxial (dorsoventral) patterning. Here we show the existence of a transient low auxin zone in the adaxial domain of early leaf primordia. We also demonstrate that this adaxial low auxin domain contributes to leaf adaxial-abaxial patterning. The auxin signal is mediated by the auxin-responsive transcription factor MONOPTEROS (MP), whose constitutive activation in the adaxial domain promotes abaxial cell fate. Furthermore, we show that auxin flow from emerging leaf primordia to the shoot apical meristem establishes the low auxin zone, and that this auxin flow contributes to leaf polarity. Our results provide an explanation for the hypothetical meristem-derived leaf polarity signal. Opposite to the original proposal, instead of a signal derived from the meristem, we show that a signaling molecule is departing from the primordium to the meristem to promote robustness in leaf patterning. Extensive molecular genetic studies of more than a decade have identified a transcriptional regulatory network containing several adaxially or abaxially expressed leaf abaxial-and adaxialpromoting genes (1-6). These genes encode transcription factors and small RNAs, and their domain-specific expression patterns are required for adaxial-abaxial asymmetric cell differentiation and lamina expansion. Regulatory genes expressed in the abaxial domain suppress those expressed in the adaxial domain and vice versa. MicroRNAs 165 and 166 (MiR165/166) and transcription factor-encoding KANADI (KAN) genes are expressed in the abaxial domain and restrict the expression of class III homeo-

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Abstract:The aim of the present work was to investigate the wetting behaviour of biomedical grade Ti-6Al-4V alloy surfaces textured by a femtosecond laser treatment. The material was treated in ambient atmosphere using an Yb: KYW chirped-pulse-regenerative amplification laser with a wavelength of 1030 nm and a pulse duration of 500 fs. Four main types of surface textures were obtained depending on the processing parameters and laser treatment method. These textures consist of: (1) nanoscale laser-induced periodic surface structures (LIPSS); (2) nanopillars; (3) a bimodal roughness distribution texture formed of LIPSS overlapping microcolumns; (4) a complex texture formed of LIPSS overlapping microcolumns with a periodic variation of the columns size in the laser scanning direction. The wettability of the surfaces was evaluated by the sessile drop method using distilled-deionized (DD) water and Hank's balanced salt solution (HBSS) as testing liquids. The laser treated surfaces present a hydrophilic behaviour as well as a high affinity for the saline solution, with equilibrium contact angles in the ranges 24.1-76.2. for DD water and 8.4-61.8. for HBSS. The wetting behaviour is anisotropic, reflecting the anisotropy of the surface textures.

Computational morphodynamics utilizes computer modeling to understand the development of living organisms over space and time. Results from biological experiments are used to construct accurate and predictive models of growth. These models are then used to make novel predictions providing further insight into the processes in question, which can be tested experimentally to either confirm or rule out the validity of the computational models. This review highlights two fundamental issues: (1.) models should span and integrate single cell behavior with tissue development and (2.) the necessity to understand the feedback between mechanics of growth and chemical or molecular signaling. We review different approaches to model plant growth and discuss a variety of model types that can be implemented, with the aim of demonstrating how this methodology can be used, to explore the morphodynamics of plant development.