The plant hormone abscisic acid (ABA) plays a crucial role in regulating plant responses to environmental stresses. Interplay of several different proteins including the PYR/PYL/RCAR receptors, A-group PP2C protein phosphatases, SnRK2 protein kinases, and downstream transcription factors regulates ABA signalling. We report here the identification of a family of ABA-induced transcription repressors (AITRs) that act as feedback regulators in ABA signalling. We found that the expression of all the 6 Arabidopsis AITR genes was induced by exogenously ABA, and their expression levels were decreased in ABA biosynthesis mutant aba1-5. BLAST searches showed that AITRs are exclusively present in angiosperms. When recruited to the promoter region of a reporter gene by a fused DNA binding domain, all AITRs inhibited reporter gene expression in transfected protoplasts. In Arabidopsis, aitr mutants showed reduced sensitivity to ABA and to stresses such as salt and drought. Quantitative RT-PCR analysis demonstrated that the ABA-induced response of PP2C and some PYR/PYL/RCAR genes was reduced in AITR5 transgenic plants but increased in an aitr2 aitr5 aitr6 triple mutant. These results provide important new insights into the regulation of ABA signalling in plants, and such information may lead to the production of plants with enhanced resistance to environmental stresses.

Aux/IAA proteins are transcriptional repressors that control auxin signaling by interacting with auxin response factors (ARFs). So far all of the identified Aux/IAA mutants with auxin-related phenotypes in Arabidopsis and rice (Oryza sativa) are dominant gain-of-function mutants, with mutations in Domain II that affected stability of the corresponding Aux/IAA proteins. On the other hand, morphological changes were observed in knock-down mutants of Aux/IAA genes in tomato (Solanum lycopersicum), suggesting that functions of Aux/IAA proteins may be specific for certain plant species. We report here the characterization of PtrIAA14.1, a poplar (Populus trichocarpa) homolog of IAA7. Bioinformatics analysis showed that PtrIAA14.1 is a classic Aux/IAA protein. It contains four conserved domains with the repressor motif in Domain I, the degron in Domain II, and the conserved amino acid signatures for protein–protein interactions in Domain III and Domain IV. Protoplast transfection assays showed that PtrIAA14.1 is localized in nucleus. It is unable in the presence of auxin, and it represses auxin response reporter gene expression. Expression of wild-type PtrIAA14.1 in Arabidopsis resulted in auxin-related phenotypes including down-curling leaves, semi-draft with increased number of branches, and greatly reduced fertility, but expression of the Arabidopsis Aux/IAA genes tested remain largely unchanged in the transgenic plants. Protein–protein interaction assays in yeast and protoplasts showed that PtrIAA14.1 interacted with ARF5, but not other ARFs. Consistent with this observation, vascular patterning was altered in the transgenic plants, and the expression of AtHB8 (Arabidopsis thaliana homeobox gene 8) was reduced in transgenic plants.

Ethylene regulates many aspects of plant growth and development including seed germination, leaf senescence, and fruit ripening, and of plant responses to environmental stimuli including both biotic and abiotic stresses. Ethylene response factors (ERFs) are plant-specific transcription factors and are a subfamily of the AP2 (APETALA2)/ERF transcription factor family. The function of many members in this large gene family remains largely unknown. ERF96, a member of the Group IX ERF family transcription factors, has recently been shown to be a transcriptional activator that is involved in plant defense response in Arabidopsis. Here we provide evidence that ERF96 is a positive regulator of abscisic acid (ABA) responses. Bioinformatics analysis indicated that there are a total four small ERFs in Arabidopsis including ERF95, ERF96, ERF97, and ERF98, and that ERF96 forms a cluster with ERF95 and ERF97. By using quantitative RT-PCR, we found that ERF96 is expressed in all tissues and organs examined except roots, with relatively high expression in flowers and seeds. Results from the protoplast transfection assay indicated that the EDLL motif-containing C-terminal domain is responsible for ERF96’s transcriptional activity. Although loss-of-function mutant of ERF96 was morphologically similar to wild type plants, transgenic plants overexpressing ERF96 had smaller rosette size and were delayed in flowering time. In ABA sensitivity assays, we found that ERF96 overexpression plants were hypersensitive to ABA in terms of ABA inhibition of seed germination, early seedling development and root elongation. Consistent with these observations, elevated transcript levels of some ABA-responsive genes including RD29A, ABI5, ABF3, ABF4, P5CS, and COR15A were observed in the transgenic plants in the presence of ABA. However, in the absence of ABA treatment, the transcript levels of these ABA-responsive genes remained largely unchanged. Our experiments also showed that water loss in ERF96 overexpression plants was slower than that in Col wild type plants. Stomatal closure assays indicated that ERF96 overexpression plants had reduced stomatal aperture in the presence of ABA. Taken together, our results suggest that ERF96 positively regulates ABA responses in Arabidopsis.

Epithelia are dynamic tissues that self-remodel during their development. During morphogenesis, the tissue-scale organization of epithelia is obtained through a sum of individual contributions of the cells constituting the tissue. Therefore, understanding any morphogenetic event first requires a thorough segmentation of its constituent cells. This task, however, usually implies extensive manual correction, even with semi-automated tools. Here we present EPySeg, an open-source, coding-free software that uses deep learning to segment membrane-stained epithelial tissues automatically and very efficiently. EPySeg, which comes with a straightforward graphical user interface, can be used as a python package on a local computer, or on the cloud via Google Colab for users not equipped with deep-learning compatible hardware. By substantially reducing human input in image segmentation, EPySeg accelerates and improves the characterization of epithelial tissues for all developmental biologists.

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