TIME Magazine, May 27, 2013
By David Harry, TerViva
Angelina Jolie’s personal decision to undergo a preventative double mastectomy became a very public discussion topic after she published an op-ed piece in the May 14, 2013, New York Times (http://www.nytimes.com/2013/05/14/opinion/my-medical-choice.html?_r=0). TIME magazine (May 27, 2013) followed suit by featuring the story on its cover. Ms. Jolie’s story is valuable because it provides an instructive example to help others begin to understand how genetic testing can help assess risk. But it also provides a learning opportunity for better understanding how genetic testing can be applied in agriculture.
Ms. Jolie sought out genetic testing because her family history presented strong evidence of an inherited predisposition for hereditary breast and ovarian cancer (HBOC, http://www.cancer.net/cancer-types/hereditary-breast-and-ovarian-cancer): her mother died of breast cancer at age 56; her maternal grandmother died of ovarian cancer at age 45; and within weeks after Ms. Jolie’s announcement, her maternal aunt died of breast cancer at age 61 (http://en.wikipedia.org/wiki/Angelina_Jolie#Cancer_prevention_treatment). Ms. Jolie’s genetic test revealed that she carries the defective (cancer causing) version of the BRCA1 gene associated with HBOC. Ms. Jolie subsequently opted to undergo a double mastectomy dramatically reducing her overall risk of developing breast cancer. The overwhelming public reaction has been an outpouring of support, coupled with praise for Ms. Jolie’s decision to go public in order to help others.
Extrapolating from medical genetics to other applications such as agriculture requires some explanation. First, it’s important to realize that the same rules of inheritance apply equally to plants, animals, and humans. Likewise, the process of interpreting these rules, and coupling family history with genetics, follows incredibly similar rationales and offer similar predictive opportunities in both medicine and in agriculture.
Ms. Jolie’s journey illustrates how, in light of her family history and genetic testing results, her medical advisors estimated she had an 87% chance of developing breast cancer. Such predictions are not always as straight forward. Over the past two decades, the roles of certain genes in breast cancer have been increasingly understood. BRCA1 and BRCA2 play particularly significant roles in cancer because they affect DNA repair, but the involvement of other genes (http://www.cancer.gov/cancertopics/factsheet/Risk/BRCA) means that completing a battery of genetic tests does not ensure accurately predicting the likelihood of developing cancer. Genetic counseling is typically recommended since a large number of factors must be considered, including the interaction of an individual’s personal history in conjunction with complex environmental influences. Needless to say, amassing the resources to evaluate overall risk is no trivial matter, and deciding how to act on this information involves balancing many factors.
All medical decisions, with or without genetic testing, are made from the perspective of an individual. In light of all pertinent medical information, and after balancing all other factors, what course of action is best for an individual patient? Each decision, whatever its outcome, is highly individual, being made by a patient in consultation with his/her medical advisor and family.
In contrast to human medicine, agriculture decisions are typically neither individual nor personal. In agriculture, decisions typically involve evaluating alternatives affecting groups of plants or animals (e.g. populations, herds, fields, orchards, etc) to select the most economical means to achieve a given commercial or environmental outcome. For example, the typical mission of breeders and geneticists is to somehow shape the genetic trajectory of a population so that it best conforms to a targeted goal—commercial or otherwise. Genetic predictions can be influenced by family history (e.g. field performance of siblings), and increasingly, augmented using results from DNA-based genetic testing.
Two young pongamia trees with contrasting phenotypes. Which might perform better in the long-run?
Genetic screening, using methods akin to human medical genetics, is being widely used in diverse agricultural applications. Some of these involve assessing the role of one or a few genes, combining perhaps dozens of markers. Other applications are being developed that simultaneously evaluate hundreds to thousands of DNA-based differences, and then combine this information with massive datasets on plant or animal performance.
For pongamia, we are constantly on the look-out for cost effective ways to evaluate which trees to select, propagate, and distribute, using genetic markers as one of many inter-related approaches. Genetic testing will rarely supply unambiguous predictions, so our goal is to stack the odds (i.e. like a winning hand in a card game) to provide the most likely collection of pongamia varieties for a given set of circumstances.
David Harry, Ph.D., is Director of Research and Development for TerViva. His background encompasses research and management positions in the public, private, and academic sectors, working primarily to integrate novel genetic applications with applied breeding in plants and animals. David has a B.S. and M.S. in forestry, and a Ph.D. in Genetics from UC Berkeley.
