Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field

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.

State of Shark and Ray Genomics in an Era of Extinction

“…An emerging challenge lies not only in generating genomic data but also in processing it (Dupont et al, 2007;Schweizer et al, 2021). The advances in sequencing technology and lack of computational software for bioinformatics particularly has led to a "bottleneck, " where data are being produced much faster than can be analyzed (Corlett, 2017;Hohenlohe et al, 2021;Schweizer et al, 2021). Additionally, genomics realistically requires high-performance computing to process and analyze full genomes, often gigabytes of data.…”

“…Many bioinformatics pipelines and programs require a reasonably high level of computer programming knowledge, therefore outsourcing bioinformatic and computational assistance is a common way to overcome this issue (Corlett, 2017). Whilst there are increasing resources, such as workshops, seminars, and online courses, now available for researchers to upskill on emerging techniques, these are currently underutilized (Hendricks et al, 2018;Schweizer et al, 2021). Increasing the user-friendliness of bioinformatic tools would accelerate the integration of bioinformatics and computer sciences in marine sciences, which will be essential for the efficient development of genomic resources for species conservation (Hohenlohe et al, 2021).…”

Genomic Approaches for Conservation Management in Australia under Climate Change

“…Geneticists can now sequence the entire genome, use exome capture to target specific regions, or target single nucleotide polymorphisms (hereafter, SNPs) [ 63 ]. Although the massive amounts of data produced by genomic sequencing platforms necessitate advanced and diverse bioinformatics tools [ 58 , 64 ], such programs are constantly being improved and developed to allow genomic sequencing to reach its full potential. While there are still some uncertainties surrounding interpretation and uptake of genomic data in a management context [ 56 ], population genomics studies are increasingly being applied to conservation problems and management decision-making [ 65 ].…”

A brief history of population genetic research in California and an evaluation of its utility for conservation decision-making

“…The CaliPopGen Database provides an extensive database of spatially referenced population genetic data from the peer-reviewed literature published over the last 35 yr for populations in California. This historical database encompasses the shifting baselines of population genetics research from its infancy to the present, an astonishing progression of advances in genomic technologies, statistics, and geospatial analyses, and more generally, tracks our understanding of genomic structure and function over time ( Allendorf et al 2010 ; Schweizer et al 2021 ). As a result of these changes in technology and approach, the “best available science” for one species may be based on entirely different data types and analyses than for another, although both are used to make conservation decisions.…”