Research Interests
I am, a crop geneticist and genomics-assisted molecular breeder, interested in dissecting drought and heat tolerance adaptive mechanisms in crops at morphological, physiological, biochemical, and genetic levels using advanced genomics techniques. My research combines large data of high-throughput (precise) phenotyping in greenhouse & field conditions and advanced NGS-sequencing-based genotyping, and their association, in order to identify high-impact alleles/genes to understand the biological pathways in crops. My long-term research interest is to build a multidisciplinary platform with a collaborative network incorporating phenomics, genomics, transcriptomics metabolomics, and computer science to develop a machine learning (ML) and artificial intelligence (AI)-assisted crops development system.
ResearchProjects
Systems Genetics Studies on Rice Genomes for Grain Yield and Quality under Heat Stress
The japonica rice subspecies is the basis of most US varieties currently in production and have been used in US breeding efforts with other rice introductions from all over the world to select varieties that are tolerant to high night temperature. In this project, a diverse collection of rice lines critical to U.S. production will be screened in the field, including environments differing in night temperature, and replicated under controlled greenhouse conditions, to identify heat tolerant genotypes with contributing genes and novel mechanisms that are of interest to use in improvement of rice and other cereals for their resilience to high night temperatures. The genetic changes or identification of alleles ascribed to the desired phenotypes will be characterized at multi-systems levels: the transcriptome, metabolome, proteome, and the physiological response. Information from these analyses will be integrated into gene regulatory networks that can provide a biological understanding of plant adaptations to the changing environment documented in independent genotypes. Wildtype or mutant alleles identified from the population studies will be validated by transformation and CRISPR/Cas9 mediated allele engineering, followed by phenotypic validation to identify alleles associated with heat tolerance, as proof of concept for use in cultivar development. This Research Infrastructure Improvement Track-2 Focused EPSCoR Collaboration (RII Track-2 FEC) project brings together complementary expertise comprising senior and junior faculty from the University of Arkansas campuses at Fayetteville and Little Rock, Louisiana State University, and Oklahoma State University, to address this complex challenge in an interdisciplinary manner. The participants include six early career faculty from different institutions, who will be integrated into the interdisciplinary program to develop expertise in cross-disciplinary research projects. The project will include training of postdocs, graduate and undergraduate students, participation of 10-12th grade students in STEM girl's leadership events, and of High School teachers and students for training in Plant Genetics and Physiology.
Genetics Analysis of Photosynthetic Carbon Metabolism in Rice
Development and Characterization of Rice Genotypes for Water-use Efficiency and Drought Resistance
The aim of this project is to discover mutations in rice that increase photosynthesis efficiency. Plants capture the energy of sunlight through photosynthesis to produce sugars, starch, and a multitude of biologically active energy-rich molecules of life. Improving the efficiency of photosynthesis in plants, making it stable to environmental stresses, would provide us with a sustainable supply of food and nutrition as well as renewable energy to maintain the needs of the growing population. The project will use an integrated systems genetics approach to dissect the complex pathways of plant photosynthesis driving plant development and productivity. Genome wide association analysis of a diverse rice population identified single nucleotide polymorphism (SNP) markers associated with several parameters for photosynthetic efficiency. These SNPs will be used to identify the key genes determining important natural variation for photosynthesis. To understand the regulation of these interacting processes, it is essential to go beyond individual gene action or biochemical pathways. The integrated network approach employed will help place multiple genetically defined photosynthetic parameters in the context of gene regulatory pathways that underpin response to external factors, growth and development. A diverse set of computational formulations will be integrated into a consensus network using rank-based protocols, an approach proven to be robust for prediction of functional relationships. Predicted transcription factors will be tested in high throughput assays for their ability to activate photosynthesis genes in vivo, and confirmed in transgenic plants to unravel their downstream regulatory pathways. The systems genetic information from these genotypes will be used to reconstruct improved plants and crops with modular improvements in photosynthetic-based processes for diverse needs.
Rice, the second largest staple food crop, uses 30% of global fresh water to complete its life cycle worldwide. Water deficits worldwide have become a serious problem affecting rice growth and ultimately grain yield. To solve the water problem globally, improvement of water use efficiency (WUE) and other drought resistance (DR) traits in rice genotypes would be a useful strategy using advanced genomics tools. In this study, our objectives were to 1) analyze phenotypes of the USDA rice mini-core collection (URMC) for WUE and DR related traits to dissect the drought mechanisms, 2) correlate drought response phenes for physiological traits and grain yield in the URMC, 3) utilize molecular genetic dissection of WUE and DR using genome-wide association (GWA) analysis in the URMC, and 4) conduct genome-wide meta analysis of QTLs for DR traits and grain yield components under drought stress. In the results, 35 rice genotypes showing 40% reduction, were drought resistant, moderate drought resistant, and drought sensitive for WUE, photosynthesis, biomass, and other DR traits under drought stress, respectively. The results suggest from the correlation analysis that strong correlation exits between major grain yield components (number of spikelets per panicle, number of filled and unfilled grains per panicle) and major morphophysiological traits (plant biomass, photosynthesis and WUEi). In the GWA analysis, 24, 16, 26, 10, 19, 23, 7, 17, 11, 14, 17, 15, 29, 12, 18, and 19 significant SNPs were highly associated with WUEi, TR, stomatal conductance, Ci & Ci/Ca , plant biomass, NOTs, RWC, LR, chlorophyll content, and chlorophyll fluorescence (Fv’, Fm’, Fv’/Fm’, PhiPSII, ETR, and qN) and their identified candidate genes for WUEi and DR traits. In the meta-analysis, 13 genome-wide MQTLs were found useful containing higher number of QTLs, lower genetic distance with lower CI. Therefore, this information would be useful for the geneticists to dissect the genetic architecture of WUE and DR traits for developing high yielding drought resistant rice genotypes.
