B.S. Istanbul University (1982)
M.S. Istanbul University (1986)
Ph.D. Akdeniz University (1998)
Quantitative genetics; genetic basis of disease resistance of forest trees; application of molecular markers in tree breeding; genomic selection; tree breeding strategies, conservation of forest genetic resources.
FOR 726 – Advanced Topics In Quantitative Genetics and Breeding (in Autumn, even years)
FOR 728 – Quantitative Forest Genetics (in Spring, odd years)
Area(s) of Expertise
Quantitative Genetics, Genomic Selection, Forest Tree Breeding, QTL Mapping
- Genetic Parameter Estimates from a Polymix Breeding Population of Pinus taeda L. , Forest Science (2023)
- Low-density AgriSeq targeted genotyping-by-sequencing markers are efficient for pedigree quality control in Pinus taeda L. breeding , TREE GENETICS & GENOMES (2023)
- Performance Based on Measurements from Individual-Tree Progeny Tests Strongly Predicts Early Stand Yield in Loblolly Pine , FOREST SCIENCE (2023)
- AgMate: An Optimal Mating Software for Monoecious Species. A LongTerm Breeding Example for Pinus taeda L. , agriRxiv (2022)
- Current status and trends in forest genomics , Forestry Research (2022)
- Genetic linkage between the training and selection sets impacts the predictive ability of SNP markers in a cloned population of Pinus taeda L. , TREE GENETICS & GENOMES (2022)
- Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees , Methods in Molecular Biology (2022)
- Long-term evaluation of intra- and inter-provenance hybrids of loblolly pine in the Piedmont region of the southeastern United States , FOREST ECOLOGY AND MANAGEMENT (2022)
- Optimal mating of Pinus taeda L. under different scenarios using differential evolution algorithm , (2022)
- Pollination Bag Type Affects Ovule Development and Seed Yields in Pinus taeda L. , FOREST SCIENCE (2022)
We seek to understand the genetic basis of non-race-specific resistance to fusiform rust disease caused by Cronartium quercuum f. sp. fusiforme (Cqf) in Pinus taeda, an economically critical pine species. In previous research, our group mapped two major resistance QTL with high genetic resolution in the genome of a P. taeda resistance donor. In a parallel bulked-segregant RNAseq experiment, we identified candidate resistance genes with SNP highly associated with resistance to Cqf. These genes were part of the nucleotide-binding leucine-rich repeat. Here, we will leverage our newly gained knowledge of the genetics of host resistance to generate a pine population segregating for the same two resistance QTL. To understand the genetics of avirulence in the pathogen, the pine population will then be challenged with a diverse basidiospore mixture of Cqf in an artificial inoculation experiment. Following symptom development, fungal strains capable of growing on each of four host resistance genotypes will be sampled directly from diseased tissue and sequenced. Following SNP discovery, the fungal genome will be scanned for the presence of selective sweeps that would indicate proximity to genes selected for virulence against one or the other QTL, such as effectors.
Loblolly pine is the most abundant commercially grown tree species in North Carolina with over 100,000 acres of pine plantations established each year in the state. In addition to the conventional forest products industry, loblolly pine serves as a promising source for renewable energy in the form of woody biomass. Large genetic differences exist for growth, disease resistance, and stem form. By planting genetically superior trees with desirable traits, it may be possible to substantially increase the amount and quality of biomass produced at a given site. The goal of this project is to evaluate different planting stock (families) in combination with different thinning regimes in order to inform forest landowners how best to maximize their returns when supplying both the bioenergy and sawtimber markets. This project was initiated in 2012, with the planting of a high spacing density (1037 trees/acre) long-term field trial in the NC Piedmont. The trial includes 10 of the best Coastal and 10 of the best Piedmont families with varying degrees of adaptation, growth, and wood characteristics. Different thinning regimes will be explored using eight year measurements, and the predicted financial returns from the thinnings as well as projected sawtimber production will be evaluated.
Intensively managed pine plantations in the South are the major source of wood and fiber in the world. The farmgate value of timber and fiber production ranks only behind corn in the USA. Our group (Cooperative Tree Improvement Program) has over 60 years of history in working with stakeholders to support the sector by genetic improvement of pines. The objectives of this research are i) test the utility of genomic selection in loblolly pine, ii) discover alleles conferring fusiform rust disease resistance and iii) train professionals for routine applications of genomics in tree breeding. A specific population of loblolly pine has been developed over two generations to test the genomic selection concept. An Affymetrix 50K SNP array, currently under development, will be used for large scale genotyping. Bulked-segregant analysis and next-generation high-throughput RNA sequencing will be used to discover fusiform rust resistance genes. Resistance genes will be mapped using artificial inoculations on segregating pine seedling families. Disease symptoms will be associated with variants discovered from RNAseq analysis. Large sample sizes will allow for high-resolution mapping of genes conferring resistance to fusiform rust. If successful, sequence variants diagnostic for rust resistance can be converted to Affymetrix probes and included on the 50K SNP array. The results from genomic selection may have a profound effect in loblolly pine breeding. Genomic selection could replace time-consuming field experiments, reducing the tree improvement cycles from 15 years to 7 and doubling genetic gain in wood and fiber production from pine plantations in the southern US.
We will develop two tools for the selection and deployment of loblolly pine genotypes resistant to fusiform rust: 1) a tree level portable spectral sensing device for rapid resistance selection, and 2) a landscape level risk prediction model using machine learning to forecast susceptible areas to the disease in the Southeast in response to soil, climatic conditions, management regime and genetics
PepsiCo wishes to have a short-course on AS-REML taught to a few employees (5-7).
Loblolly pine (Pinus taeda L.) is the primary woody bioenergy feedstock for North Carolina. There are over 2.6 million acres of pine plantations in NC, and almost all have been established with loblolly pine genotypes from the NCSU Cooperative Tree Improvement Program. The 5-year-old Loblolly Pine Biomass Genetics/Cropping Study at the NCDA&CS Umstead Farm at Butner, NC is a unique field laboratory where we are evaluating the genetic differences in traits that impact biomass/bioenergy traits. In this field trial, we planted 10 of the best Coastal and 10 of the best Piedmont loblolly pine varieties with varying degrees of adaptation, growth, and wood characteristics. At age 3 years, Coastal families grew faster but suffered more cold damage and stem malformations than the better adapted Piedmont families. Funding is sought to continue this critical experiment and to better understand the genetic basis of variation in biomass/biofuel traits and improve pine varieties for biomass production. Trees will be at the ideal age to collect wood samples and measure density, strength, and moisture content to project dry weight yields and biomass/bioenergy value.
Timber is one of the most economically important crops in the US in farm gate value, ranking only behind corn. The goal of the project is to bring genomics to forest tree breeding to sustainably increase timber, fiber, and biofuel feedstock production. Publicly funded research projects have produced vast genomic resources for loblolly pine. We aim to discover informative SNPs from sequence databases using bioinformatics and organize in a publicaly accessible database. Leveraging the pine SNP database, we will establish PineSNPchip consortium to bring the tree breeding/forest genetics community together to design SNP arrays (see 20 letters of support). The consortium will then negotiate with genotyping centers to genotype large volumes of samples (>12K) in order to lower genotyping costs. The Cooperative Tree Improvement Program at NC State University has developed a loblolly pine population for implementation of genomic selection since 2006. Cooperative funds will be used to genotype ~6000 trees using PinSNPchip. The predicted ability of markers for growth and disease resistance will be estimated using Bayesian statistical models. Two workshops will be developed to train professionals with skills sets to use genomic tools in tree breeding. The workshops will be open to all plant/animal breeders. If successful, genomic selection will be a paradigm shift in pine breeding. We expect the research results will have a broader impact. Pine genome is large (~24Gb) and complex. The methods develop in this project could be extended to crops and horticultural species with complex genomes.
The goal for this partnership is to plant, develop and document the information and tools needed to demonstrate the sustainable production of biomass for bioenergy across the Southern US. Specifically, this program will develop and demonstrate sustainable, flexible, integrated biomass production solutions that create innovative deployment scenarios to reliably produce and supply biomass feedstocks that are optimized for performance in leading conversion technologies. Research and development activities will target specific barriers in each step of the supply chain that are identified as critical to regional economic and/or environmental sustainability. Education, extension and outreach activities will be integrated so that the results of this work will reach target audiences with appropriate real-world examples.
Plant cell walls are the essential components of feedstocks for biomass based liquid fuel alternatives to petroleum. The secondary cell walls of woody plants contribute greatly to biomass and are targets for improving potential feedstocks. In the application of systems biology to development of new biofuels, as in any complex biological process, predictive modeling is the central goal. We propose to use a systems approach with genome based information and mathematical modeling to advance the understanding of the biosynthesis of the plant secondary cell wall. To do this, we will use multiple transgenic perturbations and measure effects on plants using advanced quantitative methods of genomics, proteomics, and structural chemistry. The combination of quantitative analysis, transgenesis, statistical inference and systems modeling provide a novel and comprehensive strategy to investigate the regulation, biosynthesis and properties of the secondary cell wall.
Pine plantation forestry in the southeastern US is an important part of the regional economy, as well as the regional carbon budget. Climate changes over the coming decades have the potential to affect the productivity and carbon-cycling functions of these plantations. This research proposal is a combined effort by forestry researchers from several disciplines to conduct trans-disciplinary research, integrate analysis of data, provide an information base and generate a set of tools that will be useful to land owners and managers in the region. The project will also educate the next generation of forest scientists to address the challenges facing the southeastern US forestry sector, and transfer technology to the private sector to assist with rural economic development.