Short title: GhWAK7A regulates chitin signaling and defense. One-sentence summary: GhWAK7A interacts with the GhCERK1-GhLYK5 chitin sensory complex and regulates cotton resistance against fungal diseases.

Salinity is among the major factors limiting crop production worldwide. Despite having moderate salt-tolerance, cotton (Gossypium spp.) suffers severe yield losses to salinity stresses, largely due to being grown on saline-alkali and dry lands.To identify genetic determinants conferring salinity tolerance in cotton, we deployed a functional genomic screen using a cotton cDNA library in a virus-induced gene silencing (VIGS) vector. We have revealed that silencing of GhDsPTP3a, which encodes a protein phosphatase, increases cotton tolerance to salt stress.Yeast two-hybrid screens indicated that GhDsPTP3a interacts with GhANN8b, an annexin protein, which plays a positive role in regulating cotton response to salinity stress. Salt stress induces GhANN8b phosphorylation, which is subsequently dephosphorylated by GhDsPTP3a. Ectopic expression of GhDsPTP3a and GhANN8b oppositely regulates plant salt tolerance and calcium influx. In addition, we have revealed that silencing of GhDsPTP3a or GhANN8b exerts opposing roles in regulating GhSOS1 transcript levels, and ectopic expression of GhANN8b elevates Na + efflux in Arabidopsis under salinity stress.Our study demonstrates that a cotton phosphatase GhDsPTP3a and an annexin protein GhANN8b interact and reversely modulate Ca 2+ and Na + fluxes in cotton salinity responses.

Grammitidoideae are the largest subfamily in Polypodiaceae and contain about 911 species. Progress has been made in understanding the overall phylogeny and generic boundaries in the light of recent molecular works. However, the majority of species, especially Asian species, and some critical type species of genera remain unsampled. In this study, a dataset of six plastid markers of 1003 (112 new) accessions representing ca. 412 species of Grammitidoideae including the type species of Ctenopterella, Grammitis, Moranopteris, Radiogrammitis, and Themelium, was assembled to infer a phylogeny. Our major results include: (1) the type species of Grammitis is successfully sequenced using a next‐generation sequencing technique and is resolved in Grammitis s.str. as expected; (2) Ctenopterella is found to be polyphyletic and a new clade consisting of C. khaoluangensis is resolved as sister to Tomophyllum; (3) the type species of Ctenopterella is resolved in a clade sister to the C. lasiostipes clade; (4) Oreogrammitis is found to be polyphyletic and three clades outside of the core Oreogrammitis are identified containing O. subevenosa and allies, O. orientalis, and O. beddomeana (+ O. cf. beddomeana); (5) Prosaptia is found to be paraphyletic with P. nutans being sister to a clade containing the rest of Prosaptia and Archigrammitis; (6) the intergeneric and major relationships within the Asia‐Pacific clade are well resolved and strongly supported except for a few branches; (7) extensive cryptic speciation is detected in the Asia‐Pacific clade; and (8) based on the polyphyly of Ctenopterella we describe three new genera, Boonkerdia, Oxygrammitis, and Rouhania, for species formerly in Ctenopterella; because the type species of Grammitis belongs to Grammitis s.str., we describe five new genera, Aenigmatogrammitis, Grammitastrum (stat. nov.), Howeogrammitis, Nanogrammitis, and Thalassogrammitis for species formerly in Grammitis s.l. A key to the 35 Old‐World genera is given, a taxonomic treatment is presented, and the morphology of all new genera is shown with either a color plate and/or a line drawing.

Background: Drought is a natural hazard that affects crops by inducing water stress. Water stress, induced by drought, accounts for more loss in crop yield than all the other causes combined. With the increasing frequency and intensity of droughts worldwide, it is essential to develop drought-resistant crops to ensure food security. In this paper, we model multiple drought signaling pathways in Arabidopsis using Bayesian networks to identify potential regulators of drought-responsive reporter genes. Genetically intervening at these regulators can help develop drought-resistant crops.Result: We create the Bayesian network model from the biological literature and determine its parameters from publicly available data. We conduct inference on this model using a stochastic simulation technique known as likelihood weighting to determine the best regulators of drought-responsive reporter genes. Our analysis reveals that activating MYC2 or inhibiting ATAF1 are the best single node intervention strategies to regulate the drought-responsive reporter genes. Additionally, we observe simultaneously activating MYC2 and inhibiting ATAF1 is a better strategy.Conclusion: The Bayesian network model indicated that MYC2 and ATAF1 are possible regulators of the drought response. Validation experiments showed that ATAF1 negatively regulated the drought response. Thus intervening at ATAF1 has the potential to create drought-resistant crops.

Drought is a natural hazard that affects crops by inducing water stress. Water stress, induced by drought accounts for more loss in crop yield than all the other causes combined. With the increasing frequency and intensity of droughts worldwide, it is essential to develop drought-resistant crops to ensure food security. In this paper, we model multiple drought signaling pathways in Arabidopsis using Bayesian networks to identify potential regulators of drought-responsive reporter genes. Genetically intervening at these regulators can help develop drought-resistant crops. We create the Bayesian network model from the biological literature and determine its parameters from publicly available data. We conduct inference on this model using a stochastic simulation technique known as likelihood weighting to determine the best regulators of drought-responsive reporter genes. Our analysis reveals that activating MYC2 or inhibiting ATAF1 are the best single node intervention strategies to regulate the drought-responsive reporter genes. Additionally, we observe simultaneously activating MYC2 and inhibiting ATAF1 is a better strategy. The Bayesian network model indicated that MYC2 and ATAF1 are possible regulators of the drought response. Validation experiments showed that ATAF1 negatively regulated the drought response. Thus intervening at ATAF1 has the potential to create drought-resistant crops.