Two HudsonAlpha scientists awarded USDA-NIFA Fellowships
Lee and Robinson will use genomics to improve economically important crops in the US
By: Sarah Sharman, PhD
Genetic technologies are a game changer for the agricultural industry, allowing farmers and breeders to create better crops more quickly for a more productive and sustainable agricultural system. To fuel such immense growth and discovery in the genetics field, we need a constant flow of young scientists ready to tackle the problems of tomorrow.
At HudsonAlpha Institute for Biotechnology, training the next generation of scientists is integral to the mission of using genomics to improve life. In addition to the nationally recognized educational programming through the Educational Outreach team, faculty investigators train high school students, undergraduate and graduate students, and postdoctoral associates in their labs.
Two postdoctoral associates at HudsonAlpha were recently awarded prestigious $225,000 postdoctoral fellowships from the US Department of Agriculture’s (USDA) National Institute of Food and Agriculture (NIFA). Kendall Lee, PhD, is a postdoctoral associate in the lab of Faculty Investigator Josh Clevenger, PhD, and Julie Robinson, PhD, is a postdoctoral associate in the lab of Faculty Investigator Alex Harkess, PhD. Both projects aim to use genomics to improve economically important crops in the US.
Pangenomics to improve blueberry breeding programs
Kendall Lee is a two-time graduate of the University of Georgia (UGA), earning both bachelor’s and doctoral degrees there. Growing up on her family’s farm, plants and agriculture have long been a passion for Lee.
“After getting a bachelor’s degree in Animal Science, I decided to learn about forage breeding,” says Lee. “This took me down the path of plant breeding and genetics, and I quickly realized that I loved working on plants.”
Lee’s life goal is to live on her family farm while still being a leader in plant genomics research. She plans to meet this goal thanks to the flexibility of computational biology.
“Computational biology is seeing such rapid growth right now,” says Lee. “Because there are no in-lab requirements for computational biologists, this career will allow me to conduct impactful research remotely from my family’s farm.”
Lee’s USDA-NIFA-funded project will help her refine her technical and interpersonal skills, making her a more effective computational biologist. In collaboration with the blueberry breeding program at UGA, Lee’s project aims to apply cutting-edge genomic tools developed at HudsonAlpha to discover genetic markers associated with agronomically important traits in blueberries.
Blueberries have polyploid genomes, meaning they have more than two sets of chromosomes in their cells. Polyploid genomes contain extensive large DNA rearrangements called structural variants, often associated with agronomically important traits in crop plants. Traditional genome analysis can often miss these important structural variants. Lee plans to use a newer form of genomic analysis to look at structural variants in blueberries: pangenomes.
“Pangenomes are powerful tools that represent the entire collection of genetic information within a species, not just a single individual like traditional reference genomes,” says Lee. “My project will create pangenomic resources for the blueberry breeding community to help improve important traits like yield, fruit quality, and stress tolerance.”
The UGA blueberry breeding program has over a thousand blueberry selections established at their research farm in Alapaha, GA. Lee will use DNA from several blueberry varieties to create a pangenome reference. She’ll then use the pangenome reference and phenotyping data (observable traits) from UGA to pinpoint underlying genes for late flowering time, fruit development time, and berry size.
“The Southeast growing region provides specific challenges to blueberry breeding, namely the lack of reliable timing for the first frost and the frequent high heat and humidity,” says Lee. “Using genomic-informed breeding to shorten the time between full bloom and fruit maturation in blueberries will hopefully help farmers avoid losses due to weather conditions.”
Once Lee identifies genes associated with important traits, she’ll develop genetic markers that breeders can use for genomic selection in their breeding programs.
Engineering sex chromosomes in soybean to improve hybrid breeding
While Lee is developing a new computational tool to improve blueberry breeding, Julie Robinson will use genomic and molecular technologies to give soybeans a leg up. Robinson, a University of Tennessee, Knoxville graduate, does not have an abundant plant background like Lee. Instead, she used fission yeast to study critical cellular processes in graduate school. However, working in a plant genetics lab for her postdoctoral training was not a random choice.
“My favorite part of being a scientist is communicating my findings,” says Robinson. “Working in a plant lab and developing novel molecular systems to improve crop breeding will help expand my knowledge base, giving me broader depth of experience to draw from in my future career as a professional science communicator.”
“My favorite part of being a scientist is communicating my findings. Working in a plant lab and developing novel molecular systems to improve crop breeding will help expand my knowledge base, giving me broader depth of experience to draw from in my future career as a professional science communicator.
Julie Robinson
Throughout her USDA-NIFA-funded project, Robinson will collaborate with individuals across academia, industry, and government, helping her develop meaningful skills as a science communicator. Scientifically, Robinson’s project proposes to use genomics and molecular biology to improve hybrid soybean breeding.
The US is the primary producer of soybeans worldwide, but that doesn’t mean soybean breeding and farming are easy. Soybeans have both male and female reproductive organs in one flower, allowing them to make both pollen and seeds. They’re also cleistogamous, which means their flowers don’t open. These traits create the perfect storm for self-pollination, which limits genetic diversity in soybean offspring.
“To create better soybean lines, breeders need to cross genetically unique individuals,” says Robinson. “However, making hybrid crosses in soybean is difficult since it is able to self-pollinate. Dioecy, a system in which individual plants have only either male or female reproductive organs, promotes genetic diversity because plants are forced to cross-pollinate and create more genetically unique offspring.”
Many genes influence an organism’s sex-specific development. Sometimes, such as in humans, these genes are clustered on sex chromosomes that are inherited by offspring in different combinations, leading to the development of different sexes. However, most flowering plants, like soybeans, don’t have sex chromosomes and develop as self-pollinating hermaphrodites.
Robinson will introduce dioecy to soybeans by engineering sex chromosomes. To accomplish this, she’ll use genetic engineering and molecular biology techniques to insert genes into soybeans that influence the development of male and female sex characteristics so that individual plants do not have both anthers and carpels, thus preventing self-pollination.
Concurrently, Robinson will design and implement an inducible gene expression platform in soybeans that uses light to turn gene expression on and off. In this type of system, called optogenetics, gene expression is controlled by shining a specific wavelength of light on plants in a greenhouse. This method could produce soybean plants that are male, female, or hermaphroditic, depending on what wavelength of light is shone on a plant, giving growers and seed producers newfound control over the production of hybrid soybeans.
This work will not only significantly improve hybrid soybean production but also show that optogenetics can be implemented in and benefit other crop plants.
Julie Robinson
Boosting Retention, Interest, and Diversity through Guided Experiences in STEM (BRIDGES) is supported by the National Science Foundation under Grant Number 2225832.