Molecular Identification of Plants

Project Information

Plant.ID

Grant agreement ID: 765000

DOI

10.3030/765000

Project closed

EC signature date 3 August 2017

Start date 1 January 2018

End date 31 December 2021

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 4 062 035,52

EU contribution

€ 4 062 035,52

Coordinated by

UNIVERSITETET I OSLO
Norway

Periodic Reporting for period 2 - Plant.ID (Molecular Identification of Plants)

Reporting period: 2020-01-01 to 2021-12-31

Summary of the context and overall objectives of the project

Plants provide food, feed, medicines, and construction materials. But they also affect us negatively through pollen allergies, poisonous species, invasive species, and as adulterants in herbal medicines. Nevertheless, plants are the most promising biological resource for our future. Current extinction risks and the decline in taxonomic expertise demand accurate and rapid identification approaches to understand and valorise botanical biodiversity. Advances in genomic data and DNA sequencing are revolutionizing plant systematics, and modern molecular identification methods make it possible to accurately determine plants in ways that were technically impossible only a decade ago. Recently, it has become possible to detect substitution in herbal pharmaceuticals, monitor invasive alien species, trace fragments such as pollen and spores, uncover illegal trade in endangered species, make rapid and accurate molecular biodiversity assessments, and study historical plant diversity through DNA in museum specimens. However, to efficiently harvest the potential of the opportunities provided by the new genomic techniques, society today is in urgent need of trained biosystematists experienced in both taxonomy and in handling enormous amounts of genomic data. Plant.ID addressed these challenges by bringing together academic and non-academic partners including regulatory agencies, industry, SMEs, and NGO stakeholders, to develop molecular identification of plants through tailored approaches including species delimitation, metabarcoding, gene capture, and genomic barcoding, in order to empower stakeholders with simplified molecular identification of plants. By bridging classical taxonomic expertise with cutting-edge genomic approaches, Plant.ID brought together a network of biodiversity researchers and institutions to address pressing impediments to describing and assessing plant biodiversity under threat; trained a new generation of 15 researchers with immediate relevance to harnessing the central role of plants in the modern world; and built a network for future collaboration within and beyond Plant.ID.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Mass DNA sequencing data provide novel insights to biodiversity at several different scales. At shallow phylogenetic levels, it gives us the possibility to discover population-level lineages, and therefore further develop a phylogenetic model in which population-level phenomena are taken into account, as well as migration of alleles between populations. In WP1, theoretical and experimental developments in this field have been reviewed and further developed and tested by ESR 1 using Arctic Silene species. Herbarium specimens provide scientists with plant material for phylogenetic studies. ESR3 used this type of data to assess species delimitation as well as deeper phylogenetic patterns in the hemiparasitic genus Euphrasia. At another level, mass sequencing of DNA collected from soil samples enables scientists to identify taxonomic diversity to accurately assess ecological turnovers and gradients at both spatial and temporal scales, which ESR 2contributed towards using plant DNA harvested from soil samples.

DNA metabarcoding is a research method developed for biodiversity assessment from DNA containing substrates. For plant identification it holds great promise, but more markers need to be developed for accurate species identification. ESRs in WP2 have worked on developing and testing new approaches in molecular plant diversity assessment that move beyond amplicon-based sequencing and instead use shotgun sequencing, metagenomics, artificial intelligence and machine-learning. Such methods enable accurate identification as well as relative quantification of plant species in substrates, and enhance the ability to screen, authenticate and monitor such substrates, including herbal supplements, food stuffs, pollen traps, soil sediments, water and wood samples.

Genome sequencing data in metabarcoding as this avoids amplification biases and enables constituent quantification. WP3 therefore aimed to develop novel genetic and molecular approaches for plant identification. Each project has continued to follow on the work that was completed during the first reporting period, and have followed through on these envisioned objectives in the second reporting period. To this end, chemical and molecular methods have been developed for the historically important medicinal plant, the Cinchona tree. Customised target capture bait panels were developed for the commercially valuable Aloe, which lead to the largest-to-date produced dataset on carbon isotope values of aloes. Target capture and metagenomic sequencing of commercial samples of salep powder from online vendors and markets have been developed to test their composition and provenance. A range of bioinformatic tools have been tested against a Begonia population with a known genetic makeup in order to establish workflows for testing Begonia from different species radiations.

An increasing number of organisations routinely apply DNA-based techniques for monitoring purposes and quality assessments. For plant identification, tailor-made applications for societal end-users is still in its infancy. The ESR projects in WP4 thus all aimed to develop solutions to present research results that are easy for end users to interpret. Thus, African hardwood samples important in trade were analyzed by ESR12, resulting in new markers to discriminate between those that can be legally traded from those that are protected. ESR13 developed new bioinformatic pipelines to analyze the level of adulteration in herbal medicines and foods. ESR14 developed methods to understand the historical geography and lineage of medicinally important plants in Africa. ESR15 developed AI methods to analyze traded ebony and identify species that are protected from those that are protected.

This work has been disseminated through 42 oral and poster presentations, 11 peer-reviewed journal articles, with 6800 members of the scientific community reached. Outreach efforts using various forms of dissemination have resulted in 470000 members of the general public also being reached.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Mobilising our team of beneficiaries and partners, Plant.ID has been working to translate cutting-edge empirical innovations to applied research and development, from key-players in species delimitation, DNA barcoding and molecular identification. This is enabling us to address questions in biosystematics that could not be addressed before. The proposal laid the foundation for a project that would progress beyond the state-of-the-art, but importantly also envisioned that the consortium would initiate new synergistic collaborations through the ESR projects. This openness to innovation is key to projects that seek to capitalize on scientific developments that happen after proposal submission or during project initiation and early execution. Midterm we can clearly see that all projects are specific, measurable, attainable, relevant, and time-bound, and our ESRs are working on specific outputs relevant to the project and their PhDs. Additionally, many ESRs have embraced and incorporated cutting-edge developments into their projects to increase the scientific and societal relevance of Plant.ID. Furthermore, a number of inter-ESR, as well as cross-project, collaborations are on their way to help Plant.ID achieve its vision beyond the cutting-edge synergies.

Overview of Plant.ID