Tillers are vegetative branches that develop from axillary buds located in the leaf axils at the base of many grasses. Genetic manipulation of tillering is a major objective in breeding for improved cereal yields and competition with weeds. Despite this, very little is known about the molecular genetic bases of tiller development in important Triticeae crops such as barley (Hordeum vulgare) and wheat (Triticum aestivum). Recessive mutations at the barley Uniculme4 (Cul4) locus cause reduced tillering, deregulation of the number of axillary buds in an axil, and alterations in leaf proximal-distal patterning. We isolated the Cul4 gene by positional cloning and showed that it encodes a BROAD-COMPLEX, TRAMTRACK, BRIC-À-BRAC-ankyrin protein closely related to Arabidopsis (Arabidopsis thaliana) BLADE-ON-PETIOLE1 (BOP1) and BOP2. Morphological, histological, and in situ RNA expression analyses indicate that Cul4 acts at axil and leaf boundary regions to control axillary bud differentiation as well as the development of the ligule, which separates the distal blade and proximal sheath of the leaf. As, to our knowledge, the first functionally characterized BOP gene in monocots, Cul4 suggests the partial conservation of BOP gene function between dicots and monocots, while phylogenetic analyses highlight distinct evolutionary patterns in the two lineages.

In this study, we provide a comparative genomic analysis of Pantoea agglomerans strain P5 and 10 closely related strains based on phylogenetic analyses. A next-generation shotgun strategy was implemented using the Illumina HiSeq 2500 technology followed by core- and pan-genome analysis. The genome of P. agglomerans strain P5 contains an assembly size of 5082485 bp with 55.4% G + C content. P. agglomerans consists of 2981 core and 3159 accessory genes for Coding DNA Sequences (CDSs) based on the pan-genome analysis. Strain P5 can be grouped closely with strains PG734 and 299 R using pan and core genes, respectively. All the predicted and annotated gene sequences were allocated to KEGG pathways. Accordingly,  genes involved in plant growth-promoting (PGP) ability, including phosphate solubilization, IAA and siderophore production, acetoin and 2,3-butanediol synthesis and bacterial secretion, were assigned. This study provides an in-depth view of the PGP characteristics of strain P5, highlighting its potential use in agriculture as a biofertilizer.

It is commonly accepted that bacteria actively interact with plant host and have beneficial effects on growth and adaptation and grant tolerance to various biotic and abiotic stresses. However, the mechanisms of plant growth promoting bacteria to communicate and adapt to the plant environment are not well characterized. Among the examined bacteria isolates from different saline soils, Arthrobacter nitroguajacolicus was selected as the best plant growth-promoting bacteria under salt stress. To study the effect of bacteria on wheat tolerance to salinity stress, bread wheat seeds were inoculated with A. nitroguajacolicus and grown under salt stress condition. Comparative transcriptome analysis of inoculated and un-inoculated wheat roots under salt stress showed up-regulation of 152 genes whereas 5 genes were significantly down-regulated. Many genes from phenylpropanoid, flavonoid and terpenoid porphyrin and chlorophyll metabolism, stilbenoid, diarylheptanoid metabolism pathways were differentially expressed within inoculated roots under salt stress. Also, a considerable number of genes encoding secondary metabolites such as phenylpropanoids was detected. They are known to take part in lignin biosynthesis of the cell wall as well as antioxidants.

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Successful spermatogenesis and oogenesis are the two genetically independent processes preceding embryo development. To date, several fertility-related proteins have been described in mammalian species. Nevertheless, further studies are required to discover more proteins associated with the development of germ cells and embryogenesis in order to shed more light on the processes. This work builds on our previous software (OOgenesis_Pred), mainly focusing on algorithms beyond what was previously done, in particular new fertility-related proteins and their classes (embryogenesis, spermatogenesis and oogenesis) based on the support vector machine according to the concept of Chou’s pseudo-amino acid composition features. The results of five-fold cross validation, as well as the independent test demonstrated that this method is capable of predicting the fertility-related proteins and their classes with accuracy of more than 80%. Moreover, by using feature selection methods, important properties of fertility-related proteins were identified that allowed for their accurate classification. Based on the proposed method, a two-layer classifier software, named as “PrESOgenesis” (https://github.com/mrb20045/PrESOgenesis) was developed. The tool identified a query sequence (protein or transcript) as fertility or non-fertility-related protein at the first layer and then classified the predicted fertility-related protein into different classes of embryogenesis, spermatogenesis or oogenesis at the second layer.