JOSH CLEVENGER
Clevenger and his team use genomics alongside new computational tools and breeding methods to identify quantitative trait loci (QTL) controlling drought tolerance and rapidly introduce the QTL into valuable peanut lines. Larger DNA segments close to the QTL can be used as markers to determine if a plant inherited the desired trait. The team identified several QTL and introduced them into agronomically elite peanut lines using marker-assisted speed breeding. Peanuts carrying the drought-tolerance genes were planted under drought conditions in 200 plots in Georgia. Successful lines that survive drought conditions, have little to no aflatoxin contamination, and carry other beneficial traits, such as high yield, will be deployed for commercial use. These new lines will be released publicly and de- posited in the USDA germplasm collection for free seed dispersal upon request to any country worldwide. Peanut lines that are less susceptible to aflatoxin will benefit both the economy and human health, contributing to less crop loss due to aflatoxin contamination and fewer toxic human exposures.
The Mars ® project is just one of many that Clevenger is working on using his new computational pipeline, Khufu ™ . Clevenger and Khufu co-creator Walid Korani, PhD, have been working together off and on since their time together at the University of Georgia’s Institute for Plant Breeding, Genetics, and Genomics. Throughout their time in the peanut field, the two researchers realized a weakness in sequencing technology — it is hard for current software to map short DNA reads to a reference genome and then ac- curately identify molecular markers like single-nucleotide polymorphisms (SNPs) that correlate with an observed trait. Khufu is their answer to the problem. Khufu allows researchers to perform highly accu- rate, low-coverage whole genome sequencing of com- plex genomes for a fraction of the traditional cost. Khufu uses bulk sequence analysis to accurately map traits to genes. Using peanuts as an example, this means that a bulk group of peanuts having a trait such as disease resistance is sequenced and compared to a bulk group of peanuts that do not have the trait. When the sequences are presented on a bell curve, a peak occurs at the genetic location of the SNP that is correlated to the trait. By re-analyzing data from previous studies, Clevenger and Korani show their software is 99.9 percent accurate at calling SNPs correlated to a given trait. As of late 2022, the Khufu platform sequenced more than 10,000 samples, rep- resenting 15 different species. The group has worked with more than 30 companies, organizations, or individual labs. The Khufu team works with several international groups to support small commodity crop breeding programs, like coffee, cacao, and beans. Clevenger and Korani hope that by offering other researchers the ability to use their low-cost, highly accurate computational software, they can help to advance genomic research in many different fields. The bulk of the projects for which Clevenger and Korani provide their Khufu service are focused on crop improvement and sustainability. Khufu leverages whole genome sequencing to improve crops, a feat that is impossible at such low coverage without the computational pipeline. ■
Josh Clevenger, PhD and Walid Korani, PhD, inspect the peanut plants in the HudsonAlpha greenhouse
(See pgs 48-51)
RESEARCH REPORT
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