Tom van der Valk

DDLS Fellow, Swedish Museum of Natural History

Key publications

Von Seth J, Dussex N, Díez-del-Molino D, van der Valk T, Kutschera V, Kierczak M, Steiner C, Liu S, Gilbert T, Sinding M, Prost S, Guschanski K, Nathan S, Brace S, Chan Y, Wheat C, Skoglund P, Ryder O, Goossens B, Götherström A, Dalén L. Genomic insights into the conservation status of the world’s last remaining Sumatran rhinoceros populations. (2021) Nature communications

van der Valk T, Pečnerová P, Díez-del-Molino D, Bergström A, Oppenheimer J, Hartmann S, Xenikoudakis G, Thomas J, Dehasque M, Sağlıcan E, Rabia Fidan F, Barnes I, Liu S, Somel M, Heintzman P, Nikolskiy P, Shapiro B, Skoglund P, Hofreiter M, Lister A, Götherström A, Dalén L. Million-year-old DNA sheds light on the genomic history of mammoths. (2021) Nature

Brealey J, Leitão H, van der Valk T, Xu W, Bougiouri K, Dalén L, Guschanski K. Dental calculus as a tool to study the evolution of the mammalian oral microbiome. (2020) Molecular biology and evolution

van der Valk T, Gonda C, Detwiler K, Guschanski K. The genome of the critically endangered dryas (Cercopithecus dryas) monkey provides new insights into the evolutionary history of the vervets (Chlorocebus). (2019) Molecular biology and evolution

van der Valk T, Díez-del-Molino D, Margues-Bonet T, Guschanski K, Dalén L. Historical genomes reveal the genomic consequences of recent population decline in eastern gorillas. (2018) Current biology

Hooper R, Brealey J, van der Valk T, Alberi A, Durban J, Fearnback H, Robertson K, Baird R, Hanson B, Wade P, Gilbert T, Morin P, Wolf J, Foote A, Guschanski K. (2018). Host-derived population genomics data provides insights into bacterial and diatom composition of the killer whale skin. (2018) Molecular Ecology

Tom van der Valk

Research interests

Just a few grams of a of lake water, sediments or soil can harbour the genetic information of thousands of organisms. The wealth of data contained in these samples can theoretically be utilised for a wide range of applications, including large-scale biodiversity monitoring, species detection or individual tracking through space and time. The research community has traditionally focused on analysing such samples by looking at very small stretches of DNA that are unique for a focal set of species (metabarcoding). Such methods analyse a minute fraction of the total DNA in the sample and thus the accuracy and sensitivity of metabarcoding methods are far below the theoretical possibilities.

Within the last decade, sequencing costs, high performance computer clusters and genome reference databases have improved by orders of magnitude. It is now financially feasible to sequence nearly all of the DNA within a sample. Together with the rapidly expanding databases, my research aims to leverage most of the information contained within such samples by developing algorithms that can efficiently classify DNA to their species origin and use these algorithms to analyse different sample types, including ancient sediments to look at the presence and distribution of animals and plants over time.


Last updated: 2023-01-31

Content Responsible: David Gotthold(