METHODS: We sequenced Trebouxia nuclear ribosomal ITS and rbcL of 139 lichen thalli from diverse biomes in South Africa and Namibia. Global Trebouxia phylogenies incorporating these new data were inferred with a maximum likelihood approach. Trebouxia biodiversity, biogeography, and mycobiont-photobiont associations were assessed in phylogenetic and ecological network frameworks.
RESULTS: An estimated 43 putative Trebouxia species were found across the region, including seven potentially endemic species. Only five clades represent formally described species: T. arboricola s.l. (A13), T. cf. cretacea (A01), T. incrustata (A06), T. lynniae (A39), and T. maresiae (A46). Potential endemic species were not significantly associated with the Greater Cape Floristic Region or desert. Trebouxia species occurred frequently across multiple biomes. Annual precipitation, but not precipitation seasonality, was significant in explaining variation in Trebouxia communities. Consistent with other studies of lichen photobionts, the Trebouxia-mycobiont network had an anti-nested structure.
CONCLUSIONS: Depending on the metric used, ca. 20-30% of global Trebouxia biodiversity occurs in southern Africa, including many species yet to be described. With a classification scheme for Trebouxia now well established, tree-based approaches are preferable over "barcode gap" methods for delimiting new species.
RESULTS: Here, we present draft genome information for five agriculturally, biologically, medicinally, and economically important underutilized plants native to Africa: Vigna subterranea, Lablab purpureus, Faidherbia albida, Sclerocarya birrea, and Moringa oleifera. Assembled genomes range in size from 217 to 654 Mb. In V. subterranea, L. purpureus, F. albida, S. birrea, and M. oleifera, we have predicted 31,707, 20,946, 28,979, 18,937, and 18,451 protein-coding genes, respectively. By further analyzing the expansion and contraction of selected gene families, we have characterized root nodule symbiosis genes, transcription factors, and starch biosynthesis-related genes in these genomes.
CONCLUSIONS: These genome data will be useful to identify and characterize agronomically important genes and understand their modes of action, enabling genomics-based, evolutionary studies, and breeding strategies to design faster, more focused, and predictable crop improvement programs.