Arjun Krishnan

Molecular and Physiological Analysis of Drought Stress in Arabidopsis Reveals Early Responses Leading to Acclimation in Plant Growth

Plant drought stress response and resistance are complex biological processes that need to be analyzed at a systems level using genomics and physiological approaches to dissect experimental models that address drought stresses encountered by crops in the field. Toward this goal, a controlled, sublethal, moderate drought (mDr) treatment system was developed in Arabidopsis (Arabidopsis thaliana) as a reproducible assay for the dissection of plant responses to drought. The drought assay was validated using Arabidopsis mutants in abscisic acid (ABA) biosynthesis and signaling displaying drought sensitivity and in jasmonate response mutants showing drought resistance, indicating the crucial role of ABA and jasmonate signaling in drought response and acclimation. A comparative transcriptome analysis of soil water deficit drought stress treatments revealed the similarity of early-stage mDr to progressive drought, identifying common and specific stress-responsive genes and their promoter cis-regulatory elements. The dissection of mDr stress responses using a time-course analysis of biochemical, physiological, and molecular processes revealed early accumulation of ABA and induction of associated signaling genes, coinciding with a decrease in stomatal conductance as an early avoidance response to drought stress. This is accompanied by a peak in the expression of expansin genes involved in cell wall expansion, as a preparatory step toward drought acclimation by the adjustment of the cell wall. The time-course analysis of mDr provides a model with three stages of plant responses: an early priming and preconditioning stage, followed by an intermediate stage preparatory for acclimation, and a late stage of new homeostasis with reduced growth.

Improvement of water use efficiency in rice by expression of HARDY, an Arabidopsis drought and salt tolerance gene

Freshwater is a limited and dwindling global resource; therefore, efficient water use is required for food crops that have high water demands, such as rice, or for the production of sustainable energy biomass. We show here that expression of the Arabidopsis HARDY (HRD) gene in rice improves water use efficiency, the ratio of biomass produced to the water used, by enhancing photosynthetic assimilation and reducing transpiration. These drought-tolerant, low-water-consuming rice plants exhibit increased shoot biomass under well irrigated conditions and an adaptive increase in root biomass under drought stress. The HRD gene, an AP2/ERF-like transcription factor, identified by a gain-of-function Arabidopsis mutant hrd-D having roots with enhanced strength, branching, and cortical cells, exhibits drought resistance and salt tolerance, accompanied by an enhancement in the expression of abiotic stress associated genes. HRD overexpression in Arabidopsis produces thicker leaves with more chloroplast-bearing mesophyll cells, and in rice, there is an increase in leaf biomass and bundle sheath cells that probably contributes to the enhanced photosynthesis assimilation and efficiency. The results exemplify application of a gene identified from the model plant Arabidopsis for the improvement of water use efficiency coincident with drought resistance in the crop plant rice.

Understanding multicellular function and disease with human tissue-specific networks

Tissue and cell-type identity lie at the core of human physiology and disease. Understanding the genetic underpinnings of complex tissues and individual cell lineages is crucial for developing improved diagnostics and therapeutics. We present genome-wide functional interaction networks for 144 human tissues and cell types developed using a data-driven Bayesian methodology that integrates thousands of diverse experiments spanning tissue and disease states. Tissue-specific networks predict lineage-specific responses to perturbation, identify the changing functional roles of genes across tissues and illuminate relationships among diseases. We introduce NetWAS, which combines genes with nominally significant genome-wide association study (GWAS) P values and tissue-specific networks to identify disease-gene associations more accurately than GWAS alone. Our webserver, GIANT, provides an interface to human tissue networks through multi-gene queries, network visualization, analysis tools including NetWAS and downloadable networks. GIANT enables systematic exploration of the landscape of interacting genes that shape specialized cellular functions across more than a hundred human tissues and cell types.

Effects of Drought on Gene Expression in Maize Reproductive and Leaf Meristem Tissue Revealed by RNA-Seq

Drought stress affects cereals especially during the reproductive stage. The maize (Zea mays) drought transcriptome was studied using RNA-Seq analysis to compare drought-treated and well-watered fertilized ovary and basal leaf meristem tissue. More drought-responsive genes responded in the ovary compared with the leaf meristem. Gene Ontology enrichment analysis revealed a massive decrease in transcript abundance of cell division and cell cycle genes in the drought-stressed ovary only. Among Gene Ontology categories related to carbohydrate metabolism, changes in starch and Suc metabolism-related genes occurred in the ovary, consistent with a decrease in starch levels, and in Suc transporter function, with no comparable changes occurring in the leaf meristem. Abscisic acid (ABA)-related processes responded positively, but only in the ovaries. Related responses suggested the operation of low glucose sensing in drought-stressed ovaries. The data are discussed in the context of the susceptibility of maize kernel to drought stress leading to embryo abortion and the relative robustness of dividing vegetative tissue taken at the same time from the same plant subjected to the same conditions. Our working hypothesis involves signaling events associated with increased ABA levels, decreased glucose levels, disruption of ABA/sugar signaling, activation of programmed cell death/senescence through repression of a phospholipase C-mediated signaling pathway, and arrest of the cell cycle in the stressed ovary at 1 d after pollination. Increased invertase levels in the stressed leaf meristem, on the other hand, resulted in that tissue maintaining hexose levels at an “unstressed” level, and at lower ABA levels, which was correlated with successful resistance to drought stress.

Mutant resources in rice for functional genomics of the grasses.

Rice ( Oryza sativa ) is the reference genome for the grasses, including cereals. The complete genome sequence lays the foundation for comparative genomics to the other grasses based on genome structure and individual gene function ([Devos, 2005][1]; [International Rice Genome Sequencing Project,

Coordinated Activation of Cellulose and Repression of Lignin Biosynthesis Pathways in Rice

Cellulose from plant biomass is the largest renewable energy resource of carbon fixed from the atmosphere, which can be converted into fermentable sugars for production into ethanol. However, the cellulose present as lignocellulosic biomass is embedded in a hemicellulose and lignin matrix from which it needs to be extracted for efficient processing. Here, we show that expression of an Arabidopsis (Arabidopsis thaliana) transcription factor, SHINE (SHN), in rice (Oryza sativa), a model for the grasses, causes a 34% increase in cellulose and a 45% reduction in lignin content. The rice AtSHN lines also exhibit an altered lignin composition correlated with improved digestibility, with no compromise in plant strength and performance. Using a detailed systems-level analysis of global gene expression in rice, we reveal the SHN regulatory network coordinating down-regulation of lignin biosynthesis and up-regulation of cellulose and other cell wall biosynthesis pathway genes. The results thus support the development of nonfood crops and crop wastes with increased cellulose and low lignin with good agronomic performance that could improve the economic viability of lignocellulosic crop utilization for biofuels.

Coordinated regulation of photosynthesis in rice increases yield and tolerance to environmental stress

Plants capture solar energy and atmospheric carbon dioxide (CO2) through photosynthesis, which is the primary component of crop yield, and needs to be increased considerably to meet the growing global demand for food. Environmental stresses, which are increasing with climate change, adversely affect photosynthetic carbon metabolism (PCM) and limit yield of cereals such as rice (Oryza sativa) that feeds half the world. To study the regulation of photosynthesis, we developed a rice gene regulatory network and identified a transcription factor HYR (HIGHER YIELD RICE) associated with PCM, which on expression in rice enhances photosynthesis under multiple environmental conditions, determining a morpho-physiological programme leading to higher grain yield under normal, drought and high-temperature stress conditions. We show HYR is a master regulator, directly activating photosynthesis genes, cascades of transcription factors and other downstream genes involved in PCM and yield stability under drought and high-temperature environmental stress conditions.

Mechanisms of Action and Medicinal Applications of Abscisic Acid

Since its discovery in the early 1960s, abscisic acid (ABA) has received considerable attention as an important phytohormone, and more recently, as a candidate medicinal in humans. In plants it has been shown to regulate important physiological processes such as response to drought stress, and dormancy. The discovery of ABA synthesis in animal cells has generated interest in the possible parallels between its role in plant and animal systems. The importance of this molecule has prompted the development of several methods for the chemical synthesis of ABA, which differ significantly from the biosynthesis of ABA in plants through the mevalonic acid pathway. ABA recognition in plants has been shown to occur at both the intra- and extracellularly but little is known about the perception of ABA by animal cells. A few ABA molecular targets have been identified in vitro (e.g., calcium signaling, G protein-coupled receptors) in both plant and animal systems. A unique finding in mammalian systems, however, is that the peroxisome proliferator-activated receptor, PPAR gamma, is upregulated by ABA in both in vitro and in vivo studies. Comparison of the human PPAR gamma gene network with Arabidopsis ABA-related genes reveal important orthologs between these groups. Also, ABA can ameliorate the symptoms of type II diabetes, targeting PPAR gamma in a similar manner as the thiazolidinediones class of anti-diabetic drugs. The use of ABA in the treatment of type II diabetes, offers encouragement for further studies concerning the biomedical applications of ABA.

Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic basis. Yet, only a small fraction of potentially causal genes—about 65 genes out of an estimated several hundred—are known with strong genetic evidence from sequencing studies. We developed a complementary machine-learning approach based on a human brain-specific gene network to present a genome-wide prediction of autism risk genes, including hundreds of candidates for which there is minimal or no prior genetic evidence. Our approach was validated in a large independent case–control sequencing study. Leveraging these genome-wide predictions and the brain-specific network, we demonstrated that the large set of ASD genes converges on a smaller number of key pathways and developmental stages of the brain. Finally, we identified likely pathogenic genes within frequent autism-associated copy-number variants and proposed genes and pathways that are likely mediators of ASD across multiple copy-number variants. All predictions and functional insights are available at http://asd.princeton.edu.

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

We present SEEK (search-based exploration of expression compendia; http://seek.princeton.edu/), a query-based search engine for very large transcriptomic data collections, including thousands of human data sets from many different microarray and high-throughput sequencing platforms. SEEK uses a query-level cross-validation–based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify genes, pathways and processes co-regulated with the query. SEEK provides multigene query searching with iterative metadata-based search refinement and extensive visualization-based analysis options.