“So how does that work? How do you get a bunch of books or whatever into DNA format?” –my Dad
A recent article my Dad read in The Atlantic ("Fun with DNA") about DNA spurred an interesting conversation about the state of genetics, our knowledge of DNA, and even more so, about the depth of (mis)understanding between the scientists and the public.
The reality is even those in the field of genetics are having trouble keeping up. In particular, my Dad was having a hard time grasping the idea that DNA (and the immense amount we’ve learned about DNA) can serve as data storage. Techniques already exist to store immense amounts of data, entire books, music, video in an insanely small package. Imagine squeezing 1 million CDs into a gram of DNA (for reference a penny weighs about 3 grams). We can encode and decode these DNA sequences in ways no one ever dreamed would be possible. We can use traces of DNA that nearly all organisms leave behind (“environmental DNA or eDNA”) in water, soil, and even dust to determine what species occupied in that space without ever actually seeing that species. Increasingly, powerful methods in sequencing technology and statistical modeling provide opportunities to look back in time using genetic data to assess where a species may have come from or if major events such as massive floods or volcanic eruption coincide with bottlenecks in a population. Mendel hand counted around 400,000 seeds in 7 years to learn how genetic heredity worked, and now I can look at 400,000 sequences with millions of base pairs in a few minutes. The changes and advances are truly stunning, and this is only a smattering of the tools and methods that have evolved from our increasing refined knowledge about DNA and how to manipulate it.
So it is very understandable that we have a hard time grasping just how we can apply this knowledge, both publicly and in a conservation research realm. Given the speed at which things have moved in the research realm —Watson and Crick discovered the structure of DNA a mere 60+ years ago, and now we can edit and modify entire genes— it is unsurprising we struggle with not only the possibilities, but the responsibilities in applying this new knowledge.
Lost in Conservation
Getting back to the general conservation theme of this blog, I would suggest genetics has largely been applied to a few key questions, particularly from a management and legal (i.e., Endangered Species Act [ESA]) perspective. First, how to identifying genetic variation or diversity. Genetic diversity provides the adaptive potential for all species, the potential pool of future mutations on which natural selection operates, and ultimately the metric that we use to assess a species’ ability to persist in the future. Simply put, conservation typically encourages preservation of genetic diversity and there are legal ramifications for doing so under the ESA.
The second key question in conservation genetics is identifying population structure (which relates to genetic variation). Where are genetically unique populations? Terms such as ESU (Evolutionary Significant Unit) or DPS (Distinct Population Segments) have very specific legal definitions under the ESA, but we know nature tends to avoid strict definitions in favor of gradients which can change over time. Add layers of economic and anthropogenic evaluation and the reality of conservation management can become quite complicated and difficult. More recent application of planning tools such as Structured Decision Making or Open Standards has at least given practitioners tools to evaluate and proceed (see previous posts on this blog by Mark Schwartz). Genetics has provided some very important tools which provide important information about populations and species, but this information also sparks difficult questions with ecological and legal ramifications. For example, how will we deal with hybrids with certain percentages of a native or invasive species? How do we pick thresholds for what constitutes these subspecies/ species or population segments? How relevant are these genetic details from a long-term management (i.e., climate change) perspective vs. short-term inaction? As finer resolution data become available, the application of it is not always straightforward, although some might argue it should be.
A recent example of how our genetic technology has outstripped our conservation management frameworks is advances in actually implementing "Gene Drives". Simply put, a gene drive (for a nice overview, see here) is the increased selection on a single gene or trait, so that it quickly increases in prevalence throughout a population until all or nearly all individuals have that trait. The concept is not new, but now with the advent of a genome editing tool called CRISPR/Cas9 (yes, we love our acronyms), a gene drive is now a technology that can be applied, not just theorized. This is truly revolutionary, we have the ability to introduce genetically heritable traits in organisms, to literally edit, add, or delete genes.
Gene drives are most interesting from the context of organisms with short generation times like mosquitos, and could potentially be used to introduce traits to reduce or eliminate reproductive capacities which could potentially eliminate the spread of diseases like malaria or Zika. The National Academies of Sciences, Engineering, and Medicine just released a fairly terse report (pdf here) about the application and ethics surrounding gene drives, and the fact that our ability to oversee, regulate, and assess the risks of this novel advance is quickly falling behind the science. The report states, “If the current pace of change in general genetics is thrilling, the pace of change in gene drive research is breathtaking…The presumed efficiency of gene drive modified organisms may lead to calls for their release in perceived crisis situations, before there is adequate knowledge of their ecological effects, and before mitigation plans for unintended harmful consequences are in place.” Ultimately they suggest more research in both lab and field settings, charting human values in relation to gene drives, identify and understand ecological and environmental effects, assessment of risk, engagement with the public, and establishing governance of gene drives. It remains to be seen whether the policy and management of gene drives will have sufficient time catch up, but at minimum there is growing recognition that there is a significant gap. Perhaps another interesting blog post would be what pathways might exist for building more flexibility and eliminating the lags between policy/assessment and research processes. Building flexibility into policy or management processes is not a new concept, yet it may be one of the major reasons for difficulties in conservation efficacy (think adaptive management).
Implementation of Genetic Factors
Gene drives are certainly on the extreme cutting edge of science, but may bear very direct implications for the environment and society. But even more basic advances in genomics are still well ahead of the conservation implementation curve. A recent article by Pierson et al. (2016) analyzed data on how genetic factors (i.e., on populations, fitness, and life-history) were applied in threatened species recovery plans on three continents. They found while "genetic factors were sometimes considered, but genetic data was rarely included", and plans in the US were more likely to consider genetic issues (probably because of legislation like the ESA) versus Europe and Australia. Ultimately important parameters (which can be easily estimated from modern genetic data, like genetic effective population size [Ne] which is a fundamental parameter for assessing population fitness) were rarely included in recovery plans. Understanding or at least evaluating metrics like Ne is central to conservation of populations in both the short term and the long term. Generating these data are not difficult, and though they require specific expertise, the informational value far outweighs the costs (which continues to drop with newer and faster sequencing methods). The advent of the ability to economically generate thousands of SNP loci (Single Nucleotide Polymorphisms) should be utilized more widely. These datasets can provide information on demographics, fitness, and evolutionary processes, which may span spatial and temporal scales that could not be cannot be obtained using traditional approaches.
So where does this leave us? We (researchers, policy makers, conservation managers?) need to do a better job of bridging the gap. The people who need to or could apply these data are often not familiar with its interpretation. For those in the field of genomics/genetics, open science is increasingly touted as "the best reproducible way forward", which I fully support. However, this is generally from a researcher’s perspective, rarely is the translation component fully integrated into the science pipeline. In my opinion, there needs to be a stronger value placed on how we translate advances in genomics (or any STEM (Science-Technology-Engineering-Math) field to the relevant audience. From a conservation standpoint this is important, if managers can’t access important genetic information (actual data or simply synthesized outcomes) it is unlikely decisions will integrate them. Similarly, if the general public does not understand or value the importance of genomic information, there may be less support (votes, funding, motivation) for important conservation management action in the future. There are many amazing researchers and educators who continue to try and bridge this gap, but as the gap seems to grow, there needs to be more awareness, and emphasis on supporting frameworks that make translation and implementation a priority.
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