Genomics of natural history collections for understanding evolution in the wild

Lua Lopez, Kathryn G. Turner, Emily S. Bellis, Jesse R. Lasky

Research output: Contribution to journalEditorialpeer-review

18 Scopus citations


A long-standing question in biology is how organisms change through time and space in response to their environment. This knowledge is of particular relevance to predicting how organisms might respond to future environmental changes caused by human-induced global change. Usually researchers make inferences about past events based on an understanding of current static genetic patterns, but these are limited in their capacity to inform on underlying past processes. Natural history collections (NHCs) represent a unique and critical source of information to provide temporally deep and spatially broad time-series of samples. By using NHC samples, researchers can directly observe genetic changes over time and space and link those changes with specific ecological/evolutionary events. Until recently, such genetic studies were hindered by the intrinsic challenges of NHC samples (i.e. low yield of highly fragmented DNA). However, recent methodological and technological developments have revolutionized the possibilities in the novel field of NHC genomics. In this Special Feature, we compile a range of studies spanning from methodological aspects to particular case studies which demonstrate the enormous potential of NHC samples for accessing large genomic data sets from the past to advance our knowledge on how populations and species respond to global change at multiple spatial–temporal scales. We also highlight possible limitations, recommendations and a few opportunities for future researchers aiming to study NHC genomics.

Original languageEnglish (US)
Pages (from-to)1153-1160
Number of pages8
JournalMolecular Ecology Resources
Issue number5
StatePublished - Sep 1 2020

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Ecology, Evolution, Behavior and Systematics
  • Genetics


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