The Origins of Coca: Museum Genomics Reveals Multiple Independent Domestications from Progenitor Erythroxylum gracilipes

Morphometrics and Phylogenomics of Coca (Erythroxylum spp.) Illuminate Its Reticulate Evolution, With Implications for Taxonomy

South American coca (Erythroxylum coca and E. novogranatense) has been a keystone crop for many Andean and Amazonian communities for at least 8,000 years. However, over the last half-century, global demand for its alkaloid cocaine has driven intensive agriculture of this plant and placed it in the center of armed conflict and deforestation. To monitor the changing landscape of coca plantations, the United Nations Office on Drugs and Crime collects annual data on their areas of cultivation. However, attempts to delineate areas in which different varieties are grown have failed due to limitations around identification. In the absence of flowers, identification relies on leaf morphology, yet the extent to which this is reflected in taxonomy is uncertain. Here, we analyze the consistency of the current naming system of coca and its four closest wild relatives (the "coca clade"), using morphometrics, phylogenomics, molecular clocks, and population genomics. We include name-bearing type specimens of coca's closest wild relatives E. gracilipes and E. cataractarum. Morphometrics of 342 digitized herbarium specimens show that leaf shape and size fail to reliably discriminate between species and varieties. However, the statistical analyses illuminate that rounder and more obovate leaves of certain varieties could be associated with the subtle domestication syndrome of coca. Our phylogenomic data indicate extensive gene flow involving E. gracilipes which, combined with morphometrics, supports E. gracilipes being retained as a single species. Establishing a robust evolutionary-taxonomic framework for the coca clade will facilitate the development of cost-effective genotyping methods to support reliable identification.

Medicinal plants meet modern biodiversity science

Plants have been an essential source of human medicine for millennia. In this review, we argue that a holistic, interdisciplinary approach to the study of medicinal plants that combines methods and insights from three key disciplines - evolutionary ecology, molecular biology/biochemistry, and ethnopharmacology - is poised to facilitate new breakthroughs in science, including pharmacological discoveries and rapid advancements in human health and well-being. Such interdisciplinary research leverages data and methods spanning space, time, and species associated with medicinal plant species evolution, ecology, genomics, and metabolomic trait diversity, all of which build heavily on traditional Indigenous knowledge. Such an interdisciplinary approach contrasts sharply with most well-funded and successful medicinal plant research during the last half-century, which, despite notable advancements, has greatly oversimplified the dynamic relationships between plants and humans, kept hidden the larger human narratives about these relationships, and overlooked potentially important research and discoveries into life-saving medicines. We suggest that medicinal plants and people should be viewed as partners whose relationship involves a complicated and poorly explored set of (socio-)ecological interactions including not only domestication but also commensalisms and mutualisms. In short, medicinal plant species are not just chemical factories for extraction and exploitation. Rather, they may be symbiotic partners that have shaped modern societies, improved human health, and extended human lifespans.

Target capture and genome skimming for plant diversity studies

Recent technological advances in long-read high-throughput sequencing and assembly methods have facilitated the generation of annotated chromosome-scale whole-genome sequence data for evolutionary studies; however, generating such data can still be difficult for many plant species. For example, obtaining high-molecular-weight DNA is typically impossible for samples in historical herbarium collections, which often have degraded DNA. The need to fast-freeze newly collected living samples to conserve high-quality DNA can be complicated when plants are only found in remote areas. Therefore, short-read reduced-genome representations, such as target capture and genome skimming, remain important for evolutionary studies. Here, we review the pros and cons of each technique for non-model plant taxa. We provide guidance related to logistics, budget, the genomic resources previously available for the target clade, and the nature of the study. Furthermore, we assess the available bioinformatic analyses, detailing best practices and pitfalls, and suggest pathways to combine newly generated data with legacy data. Finally, we explore the possible downstream analyses allowed by the type of data generated using each technique. We provide a practical guide to help researchers make the best-informed choice regarding reduced genome representation for evolutionary studies of non-model plants in cases where whole-genome sequencing remains impractical.

The herbarium of the future

The ~400 million specimens deposited across ~3000 herbaria are essential for: (i) understanding where plants have lived in the past, (ii) forecasting where they may live in the future, and (iii) delineating their conservation status. An open access 'global metaherbarium' is emerging as these specimens are digitized, mobilized, and interlinked online. This virtual biodiversity resource is attracting new users who are accelerating traditional applications of herbaria and generating basic and applied scientific innovations, including e-monographs and floras produced by diverse, interdisciplinary, and inclusive teams; robust machine-learning algorithms for species identification and phenotyping; collection and synthesis of ecological trait data at large spatiotemporal and phylogenetic scales; and exhibitions and installations that convey the beauty of plants and the value of herbaria in addressing broader societal issues.

The complete genome sequences of Erythroxylum coca and Erythroxylum novogranatense

The flowering plant genus Erythroxylum contains approximately 300 species, including the economically and socially consequential crops called coca. We present the genome sequences of Erythroxylum coca and E. novogranatense, two cultigens produced for medicinal and quotidian use in the Andes and Amazon regions of South America, as well as the international cocaine industry. Sequencing was performed on an Illumina X-Ten platform, and reads were assembled by a de novo method followed by finishing via comparison with several species from the same genus. The BioProject, raw and assembled data can be accessed in GenBank for E. coca (PRJNA676123; JAJMLV000000000) and E. novogranatense (PRJNA675212; JAJKBF000000000).

The complete genome sequences of 56 Erythroxylum species

We present the whole genome sequences of 56 wild Erythroxylum species from Africa, China, and the American tropics. Deep Illumina sequencing was performed on a single leaf of each voucher. We de novo assembled sequence reads and then identified and used conserved regions across all preassemblies join contigs in a finishing step. The raw and assembled data is publicly available via Genbank.

Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models

To ensure optimal utilization and bioavailability, iron uptake, transport, subcellular localization, and assimilation are tightly regulated in plants. Herein, we examine recent advances in our understanding of cellular responses to Fe deficiency. We then use intracellular mechanisms of Fe homeostasis to discuss how formalizing cell biology knowledge via a mathematical model can advance discovery even when quantitative data is limited. Using simulation-based inference to identify plausible systems mechanisms that conform to known emergent phenotypes can yield novel, testable hypotheses to guide targeted experiments. However, this approach relies on the accurate encoding of domain-expert knowledge in exploratory mathematical models. We argue that this would be facilitated by fostering more "systems thinking" life scientists and that diversifying your research team may be a practical path to achieve that goal.

Mining museums for historical DNA: advances and challenges in museomics

Historical DNA (hDNA), obtained from museum and herbarium specimens, has yielded spectacular new insights into the history of organisms. This includes documenting historical genetic erosion and extinction, discovering species new to science, resolving evolutionary relationships, investigating epigenetic effects, and determining origins of infectious diseases. However, the development of best-practices in isolating, processing, and analyzing hDNA remain under-explored, due to the substantial diversity of specimen preparation types, tissue sources, archival ages, and collecting histories. Thus, for hDNA to reach its full potential, and justify the destructive sampling of the rarest specimens, more experimental work using time-series collections, and the development of improved methods to correct for data asymmetries and biases due to DNA degradation are required.