COLLECTOMICS AND THE DFG PRIORITY PROGRAM 1991 „TAXON-OMICS“
Motivation and Results
Four Senckenberg projects with a financial volume of nearly 1M € explore new methods to better understand speciation processes and facilitate biodiversity assessment.
• PalearcticHylesmoths show conflict between wing patterns and genetic clusters (Fig. 1).
• Proteomic fingerprinting facilitates long-term monitoring of zooplankton (Fig. 2).
• Hyperspectral imaging and DNA barcoding accelerates species detection in caddisflies (Fig. 3).
• Integration of citizen science and molecular species assignment works well for lichens (Fig. 4).
Outlook
Explore the joint application of novel methods for species detection and identification aids using:• automated image detection (Hyles),
• integrated proteomic, genetic, and morphological datasets (zooplankton),
• hyperspectral imaging (African caddisflies), and
• probabilistic species assignment based on multiple data sources (Lecanomics).
References
Bungartz F, Elix JA,Printzen C. 2020. Phytotaxa 431: 1 - 85. - - Hjalmarsson AE, Graf W, Jähnig SC, Vitecek S,Pauls SU. 2018. ZooKeys 773: 79-108. -- Pippel M, Jebb D,Patzold F, Winkler S, Vogel H, Myers G, ...Hundsdoerfer AK. 2020. GigaScience, 9(1), giaa001. -- Wilke T,Renz J, Hauffe T, Delicado D, Peters J. 2020.. Malacologia 63:1 (in press).
Acknowledgements
We thank DFG SPP 1991 for funding, as well as Prof. Susanne Renner (LMU München) and the steering committee for organizing workshops and facilitating cooperations within the SPP.
Contribution to SGN Program Portfolio
• The four projects contribute to Senckenberg‘sCORE MISSIONby describing, analyzing and documenting biodiversity in an earth-system context.
• The COLLECTION-BASED development of novel approaches and integration of a broad spectrum of methods is a key element of ourCOLLECTOMICSapproach.
• The development of practical assessment tools helps to monitor ANTHROPOCENE BIODIVERSITY LOSS.
• The integration of citizen scientists into research enables direct and bi-directional transfer of knowledge between SCIENCE AND SOCIETY.
#1
RA 1.1 Taxonomy and
Systematics
Christian Printzen
1, Anna Hundsdörfer
2, Steffen Pauls
1, Jasmin Renz-Gehnke
31Senckenberg Forschungsinstitut und Naturmuseum Frankfurt/M., 2Senckenberg Naturhistorische Sammlungen Dresden, 3Senckenberg am Meer, Hamburg
1
Hybridization is frequent in Hylesmoths.Mitochondrial DNA from historical museum collections sheds light on how many genomes mix to produce hybrid species helps to clarify the enigmatic taxonomy.
3
The diversity ofAfrican caddisfliesis severely under-explored.Combining hyperspectral imaging with a DNA barcoding approach and a transcriptome-based phylogenetic backbone allows us to rapidly detect , describe and illustrate undescribed species.
4
A major bottleneck for lichen taxonomy is the lack of proficient collectors with access to molecular data. Lecanomicsjoins citizen science with molecular species detection. Geographic coverage of inconspicuous and rarely collected taxa is massively improved by this approach.2
Proteome fingerprinting of zooplankton:Sustainable management of marine ecosystems under human pressure requires detailed biodiversity monitoring.
Zooplankton responds rapidly to changing environmental conditions and is an ideal biomonitor, but identification is difficult and time-consuming. Proteome fingerprinting by MALDI-TOF MS can greatly facilitate species identification.
„Whole genome capturing“ fragmented DNA ofmuseum samples
Museum (aDNA) Fresh
Reference genome
Wavelength (nm)
400 5006007008009001000
Relative reflectance
0.0 0.1 0.2 0.3 0.4
0.5 Female
Male
Sorting to morphospecies
Species Descriptions Species Delimitation
COI + 28S sequencing Combined Data
Phylogeny Transcriptome / Genome Sequencing
Sampling
Hyperspectral Imaging
Morphological / phylogenetic characterisation of Afrotropical caddisfly fauna
Fast species identification in zooplankton?
species specific spectra MALDI-TOF MS
Matrix-Assisted Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry
monitoring biodiversity assessment
machine learning reference
data base cytoplasmic proteins
<15 kDa
