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1.  Image Harvest: an open-source platform for high-throughput plant image processing and analysis 
Journal of Experimental Botany  2016;67(11):3587-3599.
Image Harvest is an open-source software for high-throughput image processing and analysis that is integrated with the Open Science Grid and provides computational resources to process large image datasets.
High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.
PMCID: PMC4892737  PMID: 27141917
High throughput computing; image analysis; image processing; large-scale biology; OpenCV; Open Science Grid; open-source software; phenomics.
2.  Genetic and Molecular Characterization of Submergence Response Identifies Subtol6 as a Major Submergence Tolerance Locus in Maize 
PLoS ONE  2015;10(3):e0120385.
Maize is highly sensitive to short term flooding and submergence. Early season flooding reduces germination, survival and growth rate of maize seedlings. We aimed to discover genetic variation for submergence tolerance in maize and elucidate the genetic basis of submergence tolerance through transcriptional profiling and linkage analysis of contrasting genotypes. A diverse set of maize nested association mapping (NAM) founder lines were screened, and two highly tolerant (Mo18W and M162W) and sensitive (B97 and B73) genotypes were identified. Tolerant lines exhibited delayed senescence and lower oxidative stress levels compared to sensitive lines. Transcriptome analysis was performed on these inbreds to provide genome level insights into the molecular responses to submergence. Tolerant lines had higher transcript abundance of several fermentation-related genes and an unannotated Pyrophosphate-Dependent Fructose-6-Phosphate 1-Phosphotransferase gene during submergence. A coexpression network enriched for CBF (C-REPEAT/DRE BINDING FACTOR: C-REPEAT/DRE BINDING FACTOR) genes, was induced by submergence in all four inbreds, but was more activated in the tolerant Mo18W. A recombinant inbred line (RIL) population derived from Mo18W and B73 was screened for submergence tolerance. A major QTL named Subtol6 was mapped to chromosome 6 that explains 22% of the phenotypic variation within the RIL population. We identified two candidate genes (HEMOGLOBIN2 and RAV1) underlying Subtol6 based on contrasting expression patterns observed in B73 and Mo18W. Sources of tolerance identified in this study (Subtol6) can be useful to increase survival rate during flooding events that are predicted to increase in frequency with climate change.
PMCID: PMC4373911  PMID: 25806518
3.  Protein abundances are more conserved than mRNA abundances across diverse taxa 
Proteomics  2010;10(23):4209-4212.
Proteins play major roles in most biological processes; as a consequence, protein expression levels are highly regulated. While extensive post-transcriptional, translational and protein degradation control clearly influence protein concentration and functionality, it is often thought that protein abundances are primarily determined by the abundances of the corresponding mRNAs. Hence surprisingly, a recent study showed that abundances of orthologous nematode and fly proteins correlate better than their corresponding mRNA abundances. We tested if this phenomenon is general by collecting and testing matching large-scale protein and mRNA expression datasets from seven different species: two bacteria, yeast, nematode, fly, human, and plant. We find that steady-state abundances of proteins show significantly higher correlation across these diverse phylogenetic taxa than the abundances of their corresponding mRNAs (p=0.0008, paired Wilcoxon). These data support the presence of strong selective pressure to maintain protein abundances during evolution, even when mRNA abundances diverge.
PMCID: PMC3113407  PMID: 21089048
4.  Towards Establishment of a Rice Stress Response Interactome 
PLoS Genetics  2011;7(4):e1002020.
Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein–protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance.
Author Summary
A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. In this paper, we used a yeast-based approach to identify rice proteins that govern the rice stress response. We validated the role of these new proteins using additional analyses to evaluate the function of these genes in rice and assessed whether they serve to positively or negatively regulate the stress response. This approach allowed us to identify ten genes that control resistance to bacterial disease and tolerance to submergence. The combination of approaches described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance.
PMCID: PMC3077385  PMID: 21533176
5.  Comparing genomic expression patterns across plant species reveals highly diverged transcriptional dynamics in response to salt stress 
BMC Genomics  2009;10:398.
Rice and barley are both members of Poaceae (grass family) but have a marked difference in salt tolerance. The molecular mechanism underlying this difference was previously unexplored. This study employs a comparative genomics approach to identify analogous and contrasting gene expression patterns between rice and barley.
A hierarchical clustering approach identified several interesting expression trajectories among rice and barley genotypes. There were no major conserved expression patterns between the two species in response to salt stress. A wheat salt-stress dataset was queried for comparison with rice and barley. Roughly one-third of the salt-stress responses of barley were conserved with wheat while overlap between wheat and rice was minimal. These results demonstrate that, at transcriptome level, rice is strikingly different compared to the more closely related barley and wheat. This apparent lack of analogous transcriptional programs in response to salt stress is further highlighted through close examination of genes associated with root growth and development.
The analysis provides support for the hypothesis that conservation of transcriptional signatures in response to environmental cues depends on the genetic similarity among the genotypes within a species, and on the phylogenetic distance between the species.
PMCID: PMC2739230  PMID: 19706179
6.  Detection and validation of single feature polymorphisms using RNA expression data from a rice genome array 
BMC Plant Biology  2009;9:65.
A large number of genetic variations have been identified in rice. Such variations must in many cases control phenotypic differences in abiotic stress tolerance and other traits. A single feature polymorphism (SFP) is an oligonucleotide array-based polymorphism which can be used for identification of SNPs or insertion/deletions (INDELs) for high throughput genotyping and high density mapping. Here we applied SFP markers to a lingering question about the source of salt tolerance in a particular rice recombinant inbred line (RIL) derived from a salt tolerant and salt sensitive parent.
Expression data obtained by hybridizing RNA to an oligonucleotide array were analyzed using a statistical method called robustified projection pursuit (RPP). By applying the RPP method, a total of 1208 SFP probes were detected between two presumed parental genotypes (Pokkali and IR29) of a RIL population segregating for salt tolerance. We focused on the Saltol region, a major salt tolerance QTL. Analysis of FL478, a salt tolerant RIL, revealed a small (< 1 Mb) region carrying alleles from the presumed salt tolerant parent, flanked by alleles matching the salt sensitive parent IR29. Sequencing of putative SFP-containing amplicons from this region and other positions in the genome yielded a validation rate more than 95%.
Recombinant inbred line FL478 contains a small (< 1 Mb) segment from the salt tolerant parent in the Saltol region. The Affymetrix rice genome array provides a satisfactory platform for high resolution mapping in rice using RNA hybridization and the RPP method of SFP analysis.
PMCID: PMC2697985  PMID: 19480680
7.  Array-based genotyping and expression analysis of barley cv. Maythorpe and Golden Promise 
BMC Genomics  2007;8:87.
Golden Promise is a salt-tolerant spring barley closely related to Maythorpe. Salt tolerance in Golden Promise has been attributed to a single mutation at the Ari-e locus (on 5H) resulting from irradiation of Maythorpe. Golden Promise accumulates lower shoot Na+ compared to Maythorpe when growing under saline conditions. This study focused on elucidating the genetic basis and mechanisms involved in this difference.
The level of polymorphism between the two genotypes was explored using the Barley1 GeneChip for single feature polymorphisms (SFPs) and an oligonucleotide pool assay for single nucleotide polymorphisms (SNPs). Polymorphism analyses revealed three haplotype blocks spanning 6.4 cM on chromosome 1H, 23.7 cM on chromosome 4H and 3.0 cM on 5H. The Barley1 GeneChip was used to examine transcript abundance in different tissues and stages during development. Several genes within the polymorphic haplotype blocks were differentially regulated. Additionally, a more global difference in the jasmonic acid pathway regulation was detected between the two genotypes.
The results confirm that Golden Promise and Maythorpe are genetically very closely related but establish that they are not isogenic, as previously reported, due to three polymorphic haplotype blocks. Transcriptome analysis indicates that the response of the two genotypes to salinity stress is quite different. Additionally, the response to salinity stress in the roots and shoot tissue is strikingly different.
PMCID: PMC1851953  PMID: 17394671
8.  Genome-wide transcriptional analysis of salinity stressed japonica and indica rice genotypes during panicle initiation stage 
Plant Molecular Biology  2006;63(5):609-623.
Rice yield is most sensitive to salinity stress imposed during the panicle initiation (PI) stage. In this study, we have focused on physiological and transcriptional responses of four rice genotypes exposed to salinity stress during PI. The genotypes selected included a pair of indicas (IR63731 and IR29) and a pair of japonica (Agami and M103) rice subspecies with contrasting salt tolerance. Physiological characterization showed that tolerant genotypes maintained a much lower shoot Na+ concentration relative to sensitive genotypes under salinity stress. Global gene expression analysis revealed a strikingly large number of genes which are induced by salinity stress in sensitive genotypes, IR29 and M103 relative to tolerant lines. We found 19 probe sets to be commonly induced in all four genotypes. We found several salinity modulated, ion homeostasis related genes from our analysis. We also studied the expression of SKC1, a cation transporter reported by others as a major source of variation in salt tolerance in rice. The transcript abundance of SKC1 did not change in response to salinity stress at PI stage in the shoot tissue of all four genotypes. However, we found the transcript abundance of SKC1 to be significantly higher in tolerant japonica Agami relative to sensitive japonica M103 under control and stressed conditions during PI stage.
Electronic supplementary material
Supplementary material is available in the online version of this article at and is accessible for authorized users.
PMCID: PMC1805040  PMID: 17160619
Rice; Salt stress; Panicle initiation; Microarray

Results 1-8 (8)