Genetic diversity, essential oil's chemical constituents of aromatic plant Mesosphaerum suaveolens (L.) Kuntze Syn. Hyptis suaveolens (L.) Poit. and its uses in crop protection: a review.

This review provides evidence on the genetic diversity, chemical constituents, and ecotoxicology of Mesosphaerum suaveolens ' essential oil. It emphasizes the agricultural benefits such as crop protection effectiveness of the plant and highlights the existing knowledge gaps and research perspectives to promote its utilization in agriculture. A systematic and extensive review of the literature was done and all pertinent full-text articles and abstracts were analyzed and incorporated into the review. Mesosphaerum suaveolens is used traditionally in pharmacology to treat several diseases such as malaria, constipation, stomach problems, and renal inflammation. It also treats cramps, digestive infections, headaches, and skin infections. To date, very few studies have been conducted worldwide about its genetic diversity. These studies highlighted three morphological variants, the blue-flowering, the white-flowering, and the light-purple flowering M. suaveolens. Its wide biological actions may be attributed to the numerous groups of chemical constituents in its essential oil including monoterpenes, sesquiterpenes, and diterpenes. Biological studies highlighted evidence of M. suaveolens being used as an antifungal, bactericidal, antimicrobial, insecticidal, and repellent plant. The essential oil extracted from M. suaveolens showed significant potential for the control of agricultural pests such as Sitiophilus zeamais, Helicoverpa armigera and Helminthosporium oryzae. M. suaveolens is commonly used worldwide as a pesticidal plant in healthcare, agriculture, and food preservation. However, there is a lack of studies concerning the toxicity and effectiveness of isolated potent phytotoxic substances, the efficacy screening in the field, the genetic diversity, the essential oil yield, and productivity. Consequently, further studies are required to fill the knowledge gaps.

Drivers of the Sisrè berry plant [Synsepalum dulcificum (Schumach & Thonn.) Daniell] rhizosphere bacterial communities in Benin.

Each plant species has its own rhizobacteriome, whose activities determine both soil biological quality and plant growth. Little knowledge exists of the rhizosphere bacterial communities associated with opportunity crops with high economic potential such as Synsepalum dulcificum. Native to West Africa, this shrub is famous for its red berries representing the only natural source of miraculin, a glycoprotein, with sweetening properties, but also playing a role in the treatment of cancer and diabetes. This study aimed to characterize the structure and diversity of rhizobacterial communities associated with S. dulcificum and to identify the parameters determining this diversity. An initial sampling stage allowed the collection of rhizosphere soils from 29 S. dulcificum accessions, belonging to three distinct phenotypes, from 16 municipalities of Benin, located either on farms or in home gardens. The bacterial diversity of these rhizosphere soils was assessed by Illumina sequencing of the 16S rRNA gene after DNA extraction from these soils. Furthermore, an analysis of the physicochemical properties of these soils was carried out. All accessions combined, the most represented phylum appeared to be Actinobacteriota, with an average relative abundance of 43.5 %, followed by Proteobacteria (14.8 %), Firmicutes (14.3 %) and Chloroflexi (12.2 %), yet the relative abundance of dominant phyla varied significantly among accessions (p < 0.05). Plant phenotype, habitat, climate and soil physicochemical properties affected the bacterial communities, but our study pointed out that soil physicochemical parameters were the main driver of rhizobacterial communities' structure and diversity. Among them, the assimilable phosphorus, lead, potassium, arsenic and manganese contents, texture and cation exchange capacity of rhizosphere soils were the major determinants of the composition and diversity of rhizosphere bacterial communities. These results suggested the possibility of improving the growth conditions and productivity of S. dulcificum, by harnessing its associated bacteria of interest and better managing soil physicochemical properties.

The Gynandropsis gynandra genome provides insights into whole-genome duplications and the evolution of C4 photosynthesis in Cleomaceae.

Gynandropsis gynandra (Cleomaceae) is a cosmopolitan leafy vegetable and medicinal plant, which has also been used as a model to study C4 photosynthesis due to its evolutionary proximity to C3 Arabidopsis (Arabidopsis thaliana). Here, we present the genome sequence of G. gynandra, anchored onto 17 main pseudomolecules with a total length of 740 Mb, an N50 of 42 Mb and 30,933 well-supported gene models. The G. gynandra genome and previously released genomes of C3 relatives in the Cleomaceae and Brassicaceae make an excellent model for studying the role of genome evolution in the transition from C3 to C4 photosynthesis. Our analyses revealed that G. gynandra and its C3 relative Tarenaya hassleriana shared a whole-genome duplication event (Gg-α), then an addition of a third genome (Th-α, +1×) took place in T. hassleriana but not in G. gynandra. Analysis of syntenic copy number of C4 photosynthesis-related gene families indicates that G. gynandra generally retained more duplicated copies of these genes than C3T. hassleriana, and also that the G. gynandra C4 genes might have been under positive selection pressure. Both whole-genome and single-gene duplication were found to contribute to the expansion of the aforementioned gene families in G. gynandra. Collectively, this study enhances our understanding of the polyploidy history, gene duplication and retention, as well as their impact on the evolution of C4 photosynthesis in Cleomaceae.

Perspective for genomic-enabled prediction against black sigatoka disease and drought stress in polyploid species.

Genomic selection (GS) in plant breeding is explored as a promising tool to solve the problems related to the biotic and abiotic threats. Polyploid plants like bananas (Musa spp.) face the problem of drought and black sigatoka disease (BSD) that restrict their production. The conventional plant breeding is experiencing difficulties, particularly phenotyping costs and long generation interval. To overcome these difficulties, GS in plant breeding is explored as an alternative with a great potential for reducing costs and time in selection process. So far, GS does not have the same success in polyploid plants as with diploid plants because of the complexity of their genome. In this review, we present the main constraints to the application of GS in polyploid plants and the prospects for overcoming these constraints. Particular emphasis is placed on breeding for BSD and drought-two major threats to banana production-used in this review as a model of polyploid plant. It emerges that the difficulty in obtaining markers of good quality in polyploids is the first challenge of GS on polyploid plants, because the main tools used were developed for diploid species. In addition to that, there is a big challenge of mastering genetic interactions such as dominance and epistasis effects as well as the genotype by environment interaction, which are very common in polyploid plants. To get around these challenges, we have presented bioinformatics tools, as well as artificial intelligence approaches, including machine learning. Furthermore, a scheme for applying GS to banana for BSD and drought has been proposed. This review is of paramount impact for breeding programs that seek to reduce the selection cycle of polyploids despite the complexity of their genome.