Feature Story

Developing Tools for Modern Breeding in Genetically Complex Crops

David R. Huff, Professor of Turfgrass Breeding and Genetics, Penn State

Matthew Sheltra, Ph.D. Graduate Student in Plant Biology, Penn State

Christopher Benson, Ph.D. Graduate Student in Plant Biology, Penn State

Turfgrass management is a lot like plant breeding in that, to be successful in either requires a mixture of both art and science. The art portion comes from the tending of the plants and providing a watchful eye for their care and growth; while the science portion empowers us with an ability to separate fact from folklore and provides us with a pathway towards progressive advancement rather than aimless wandering and stagnation.

In order to advance the science of plant breeding in genetically complex crops, the Penn State turfgrass breeding program has recently been awarded a grant from the USDA-NIFA Specialty Crops Research Initiative to collaborate with an international group of plant breeders, bioinformaticists, and computer systems analysists to develop and test new computational tools. This work will utilize our ability to sequence vast amounts of DNA and apply the resulting information towards crop improvement through the breeding process, as well as providing the opportunity to train other breeders in the use of these new tools.

The fundamental science of plant breeding is genetics, which is a field of science that began in the early 1900’s after the rediscovery of Gregor Mendel’s earlier pioneering work. At the heart of genetics lies the DNA sequence which encodes all of the instructions for life on earth, including humans, turfgrass, and microscopic disease-causing organisms. The technological developments in sequencing DNA have been astounding, such that the price of sequencing a human genome has dropped from $2.7 billion to just $300 in the last twenty years. However, as the human genome (note: the “genome” of an organism is the name we use for ALL of an organism’s DNA within a single cell) contains 6.4 billion letters, that is a lot of DNA information to be able to even store on a computer let alone to mathematically process and statistically analyze, which requires substantial amounts of computer programming, power and memory.

Compared to humans, plants can be even more genetically complex because plants may possess multiple copies of each gene, a genetic feature we call “polyploidy”. As such, polyploid crop plants are more difficult to genetically analyze and breed than non-polyploid crop plants. Our USDA grant is focused on developing the necessary computational tools to utilize vast amounts of DNA sequence information and to validate the use of these tools in several such polyploid crops including potatoes, blackberries, kiwi fruit, sweet potatoes, roses and turfgrass.

In the past, USDA funded research in turfgrass and other ornamental crops was non-existent because the uses of turfgrass did not include food, fiber, or feed. However, through the diligent efforts of the turfgrass industry including the National Turfgrass Evaluation Program (NTEP), United States Golf Association (USGA), Golf Course Superintendents Association of America (GCSAA), Professional Lawn Care Association of America (PLCAA), Turfgrass Producers International (TPI),

Oregon Seed Council (OSC), Sports Turf Managers Association (STMA), the Irrigation Association (IA) and others, turfgrass is now recognized as a crop deserving of federal research dollars through the Specialty Crops Research Initiative program. As justification for our specific grant we were able to document that polyploid species used as ornamentals (rose, chrysanthemum, lily, orchids, lantana) and as turfgrass (ryegrass, bentgrass, Kentucky bluegrass, tall fescue, bermudagrass, zoysia) deliver 1/3 the value of all specialty crop production and 15% of agricultural production in the USA. This $16.7 billion ornamental industry employs about two million people and delivers an economic impact of at least $136 billion. The turfgrass and ornamentals used in home, private and public landscapes significantly impact human health and urban ecology by enhancing air and water quality, sequestering carbon, reducing runoff and erosion, providing energy savings in heating and cooling, facilitating rain capture and storm water management, reducing noise and dust pollution, promoting wildlife habitat, increasing property values and benefitting psychological wellbeing.

For the turfgrass portion of the project, the most economically important cool season turfgrass species for the golf course industry, which is creeping bentgrass (Agrostis stolonifera L.) was selected for study. Creeping bentgrass is a polyploid with 28 chromosomes and 4 copies of each gene resulting in a large genome size of 3.4 billion letters (roughly half the size of a human genome). Genomic resources in creeping bentgrass are limited, so increasing our genetic knowledge of creeping bentgrass will provide valuable information for its agronomic improvement. The Penn State turfgrass breeding program was selected to participate in this research because it has actively bred creeping bentgrass varieties for nearly 70 years and has a large germplasm resource available for genomic analysis.

••••••

FIGURE 1: Evaluation sites for the genetic assessment of the 244 creeping bentgrass plants comprising the diversity panel includes a space-plant nursery planted on 3' centers (A & B) and a Poa annua putting green planted on 1' centers (C & D). (Photo credit: DR Huff; PJ Landschoot)

FIGURE 1A

FIGURE 1B

FIGURE 1C

FIGURE 1D

••••••

For our part in the genome-wide association study, a creeping bentgrass diversity panel of 244 genotypes has been grown and clonally propagated. The 244 genotypes are composed of the three parents of Penncross, 13 genotypes from each of nine F1 seed lots of Penncross (sampled from three production fields for each of 3 years), multiple genotypes from 22 commercially available cultivars and from 5 plant introduction collections. These 244 creeping bentgrass plants will be genotyped using the genomic complexity reduction method known as “genotyping by sequencing”. The same Illumina NextSeq DNA sequencing platform will also generate a reference genome of creeping bentgrass to allow alignment of the reads obtained from the diversity panel. Three clonal replicates of each creeping bentgrass genotype will be grown at the Landscape Management Research Center, University Park, PA for phenotypic evaluation in spaced plant nurseries. An additional three replicates will be maintained at the Joseph E. Valentine Turfgrass Research Center under putting green conditions mowed between 2.5 – 3.2 mm. The spaced plant nurseries will be evaluated for: plant spread, plant height, heading date, inflorescence number, and floret fertility, while the putting green will be evaluated for genetic color, winter color, spring greenup, clonal spread, tiller density, leaf texture, shoot density, dollar spot disease resistance, and competitive ability against Poa annua. Once all the data has been collected, we will then associate the performance of each creeping bentgrass genotype with their unique DNA characteristics through the use of the new computational programs developed by the bioinformaticists and computer systems analysts.

Our long term goals of this project will be to (1) enable routine use of genomic tools to accelerate the rate of genetic gains in polyploid crop breeding programs, (2) produce cultivars of polyploid crops that have better quality, greater productivity, and more resilience, and (3) train a new generation of plant breeders to efficiently employ genomic tools to accelerate the plant breeding process. While this advancement in science will certainly improve our ability to breed new varieties of turfgrass with higher turf quality and improved adaptation to stressful environments, it nevertheless won’t replace the art portion of plant breeding.