Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field. (15th April 2021)

• Record Type: Journal Article
• Authors: Schweizer, Rena M; Saarman, Norah; Ramstad, Kristina M; Forester, Brenna R; Kelley, Joanna L; Hand, Brian K; Malison, Rachel L; Ackiss, Amanda S; Watsa, Mrinalini; Nelson, Thomas C; Beja-Pereira, Albano; Waples, Robin S; Funk, W Chris; Luikart, Gordon
• Editors: Koepfli, Klaus-Peter
• Is Part Of: Journal of heredity. Volume 112:Number 4(2021)
• Page Start: 313
• Page End: 327
• Publication Date: 2021-04-15
• Subjects: population genetics theory -- ecological genomics -- biodiversity conservation -- experimental design -- big data filtering -- metabarcoding -- bioinformatics -- training workshops -- career planning; Breeding -- Periodicals; Plant breeding -- Periodicals; Heredity -- Periodicals; 576.5
• DOI: 10.1093/jhered/esab019
• Languages: English
• ISSNs: 0022-1503

Abstract

Abstract: A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors—and beyond—to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis.