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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one-carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. Here, by ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

GeneLab Analysis Working Group Kick-Off Meeting

Goals to achieve for GeneLab AWG - GL vision - Review of GeneLab AWG charter Timeline and milestones for 2018 Logistics - Monthly Meeting - Workshop - Internship - ASGSR Introduction of team leads and goals of each group Introduction of all members Q/A Three-tier Client Strategy to Democratize Data Physiological changes, pathway enrichment, differential expression, normalization, processing metadata, reproducibility, Data federation/integration with heterogeneous bioinformatics external databases The GLDS currently serves over 100 omics investigations to the biomedical community via open access. In order to expand the scope of metadata record searches via the GLDS, we designed a metadata warehouse that collects and updates metadata records from external systems housing similar data. To demonstrate the capabilities of federated search and retrieval of these data, we imported metadata records from three open-access data systems into the GLDS metadata warehouse: NCBI's Gene Expression Omnibus (GEO), EBI's PRoteomics IDEntifications (PRIDE) repository, and the Metagenomics Analysis server (MG-RAST). Each of these systems defines metadata for omics data sets differently. One solution to bridge such differences is to employ a common object model (COM) to which each systems' representation of metadata can be mapped. Warehoused metadata records are then transformed at ETL to this single, common representation. Queries generated via the GLDS are then executed against the warehouse, and matching records are shown in the COM representation (Fig. 1). While this approach is relatively straightforward to implement, the volume of the data in the omics domain presents challenges in dealing with latency and currency of records. Furthermore, the lack of a coordinated has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

GeneLab↗
DOE OSTI2017

Evolution of AF6-RAS association and its implications in mixed-lineage leukemia

Elucidation of activation mechanisms governing protein fusions is essential for therapeutic development. MLL undergoes rearrangement with numerous partners, including a recurrent translocation fusing the epigenetic regulator to a cytoplasmic RAS effector, AF6/afadin. We show here that AF6 employs a non-canonical, evolutionarily conserved α-helix to bind RAS, unique to AF6 and the classical RASSF effectors. Further, all patients with MLL-AF6 translocations express fusion proteins missing only this helix from AF6, resulting in exposure of hydrophobic residues that induce dimerization. We provide evidence that oligomerization is the dominant mechanism driving oncogenesis from rare MLL translocation partners and employ our mechanistic understanding of MLL-AF6 to examine how dimers induce leukemia. Proteomic data resolve association of dimerized MLL with gene expression modulators, and inhibiting dimerization disrupts formation of these complexes while completely abrogating leukemogenesis in mice. Oncogenic gene translocations are thus selected under pressure from protein structure/function, underscoring the complex nature of chromosomal rearrangements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics-Lethal Human Viruses, Interferon-Stimulated Response Experiment IFNaHUH001

The purpose of this experiment was to evaluate the human host cellular response to treatment with and without interferon alpha/beta (IFNα/β) treatment. Sample time course data was obtained from human hepatoma carcinoma cells (HUH-7) expressing transcriptional activation protein VP30, stably transfected with the Ebola VP30 gene for enabling replication of VP30-deficient Ebola virus for transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset download have a direct relationship to a primary sample submission corresponding to a specific interferon response to viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Genome-Wide Identification, Classification, and Expression Analysis of the Hsf Gene Family in Carnation ( Dianthus caryophyllus )

Heat shock transcription factors (Hsfs) are a class of important transcription factors (TFs) which play crucial roles in the protection of plants from damages caused by various abiotic stresses. The present study aimed to characterize the Hsf genes in carnation (Dianthus caryophyllus), which is one of the four largest cut flowers worldwide. In this study, a total of 17 non-redundant Hsf genes were identified from the D. caryophyllus genome. Specifically, the gene structure and motifs of each DcaHsf were comprehensively analyzed. Phylogenetic analysis of the DcaHsf family distinctly separated nine class A, seven class B, and one class C Hsf genes. Additionally, promoter analysis indicated that the DcaHsf promoters included various cis-acting elements that were related to stress, hormones, as well as development processes. In addition, cis-elements, such as STRE, MYB, and ABRE binding sites, were identified in the promoters of most DcaHsf genes. According to qRT-PCR data, the expression of DcaHsfs varied in eight tissues and six flowering stages and among different DcaHsfs, even in the same class. Moreover, DcaHsf-A1, A2a, A9a, B2a, B3a revealed their putative involvement in the early flowering stages. The time-course expression profile of DcaHsf during stress responses illustrated that all the DcaHsfs were heat- and drought-responsive, and almost all DcaHsfs were down-regulated by cold, salt, and abscisic acid (ABA) stress. Meanwhile, DcaHsf-A3, A7, A9a, A9b, B3a were primarily up-regulated at an early stage in response to salicylic acid (SA). This study provides an overview of the Hsf gene family in D. caryophyllus and a basis for the breeding of stress-resistant carnation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A transcriptome software comparison for the analyses of treatments expected to give subtle gene expression responses

Background: In this comparative study we evaluate the performance of four software tools: DNAstar-D (DESeq2), DNAstar-E (edgeR), CLC Genomics and Partek Flow for identification of differentially expressed genes (DEGs) using a transcriptome of E. coli. The RNA-seq data are from the effect of below-background radiation 5.5 nGy total dose (0.2nGy/hr) on E. coli grown shielded from natural radiation 655 m below ground in a pre-World War II steel vault. The gene expression response to three supplemented sources of radiation designed to mimic natural background, 1952 – 5720 nGy in total dose (71–208 nGy/hr), are compared to this “radiation-deprived” treatment. In addition, RNA-seq data of Caenorhabditis elegans nematode from similar radiation treatments was analyzed by three of the software packages. Results: In E. coli, the four software programs identified one of the supplementary sources of radiation (KCl) to evoke about 5 times more transcribed genes than the minus-radiation treatment (69–114 differentially expressed genes, DEGs), and so the rest of the analyses used this KCl vs “Minus” comparison. After imposing a 30-read minimum cutoff, one of the DNAStar options shared two of the three steps (mapping, normalization, and statistic) with Partek Flow (they both used median of ratios to normalize and the DESeq2 statistical package), and these two programs identified the highest number of DEGs in common with each other (53). In contrast, when the programs used different approaches in each of the three steps, between 31 and 40 DEGs were found in common. Regarding the extent of expression differences, three of the four programs gave high fold-change results (15–178 fold), but one (DNAstar’s DESeq2) resulted in more conservative fold-changes (1.5–3.5). In a parallel study comparing three qPCR commercial validation software programs, these programs also gave variable results as to which genes were significantly regulated. Similarly, the C. elegans analysis showed exaggerated fold-changes in CLC and DNAstar’s edgeR while DNAstar-D was more conservative. Conclusions: Regarding the extent of expression (fold-change), and considering the subtlety of the very low level radiation treatments, in E. coli three of the four programs gave what we consider exaggerated fold-change results (15 – 178 fold), but one (DNAstar’s DESeq2) gave more realistic fold-changes (1.5–3.5). When RT-qPCR validation comparisons to transcriptome results were carried out, they supported the more conservative DNAstar-D’s expression results. When another model organism’s (nematode) response to these radiation differences was similarly analyzed, DNAstar-D also resulted in the most conservative expression patterns. Therefore, we would propose DESeq2 (“DNAstar-D”) as an appropriate software tool for differential gene expression studies for treatments expected to give subtle transcriptome responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Discovery of FoTO1 and Taxol genes enables biosynthesis of baccatin III

Abstract Plants make complex and potent therapeutic molecules 1,2 , but sourcing these molecules from natural producers or through chemical synthesis is difficult, which limits their use in the clinic. A prominent example is the anti-cancer therapeutic paclitaxel (sold under the brand name Taxol), which is derived from yew trees (Taxusspecies) 3 . Identifying the full paclitaxel biosynthetic pathway would enable heterologous production of the drug, but this has yet to be achieved despite half a century of research 4 . WithinTaxus’ large, enzyme-rich genome 5 , we suspected that the paclitaxel pathway would be difficult to resolve using conventional RNA-sequencing and co-expression analyses. Here, to improve the resolution of transcriptional analysis for pathway identification, we developed a strategy we term multiplexed perturbation × single nuclei (mpXsn) to transcriptionally profile cell states spanning tissues, cell types, developmental stages and elicitation conditions. Our data show that paclitaxel biosynthetic genes segregate into distinct expression modules that suggest consecutive subpathways. These modules resolved seven new genes, allowing a de novo 17-gene biosynthesis and isolation of baccatin III, the industrial precursor to Taxol, inNicotiana benthamianaleaves, at levels comparable with the natural abundance inTaxusneedles. Notably, we found that a nuclear transport factor 2 (NTF2)-like protein, FoTO1, is crucial for promoting the formation of the desired product during the first oxidation, resolving a long-standing bottleneck in paclitaxel pathway reconstitution. Together with a new β-phenylalanine-CoA ligase, the eight genes discovered here enable the de novo biosynthesis of 3’-N-debenzoyl-2’-deoxypaclitaxel. More broadly, we establish a generalizable approach to efficiently scale the power of co-expression analysis to match the complexity of large, uncharacterized genomes, facilitating the discovery of high-value gene sets.

Science & Technology - Other Topics↗
DOE OSTI2015

miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5

MicroRNAs (miRNAs) are short, non-coding RNAs (∼22 nt) that play important roles in the pathogenesis of human diseases by negatively regulating numerous target genes at posttranscriptional level. However, the role of microRNAs in lung cancer, particularly non-small-cell lung cancer (NSCLC), has remained elusive. In this study, two microRNAs, miR-1271 and miR-628, and their predicted target genes were identified differentially expressed in NSCLC by analyzing the miRNA and mRNA expression data from NSCLC tissues and their matching normal controls. miR-1271 and its target gene HOXA5 were selected for further investigation. CCK-8 proliferation assay showed that the cell proliferation was promoted by miR-1271 in NSCLC cells, while miR-1271 inhibitor could significantly inhibited the proliferation of NSCLC cells. Interestingly, migration and invasion assay indicated that overexpression of miR-1271 could significantly promoted the migration and invasion of NSCLC cells, whereas miR-1271 inhibitor could inhibited both cell migration and invasion of NSCLC cells. Western blot showed that miR-1271 suppressed the protein level of HOXA5, and luciferase assays confirmed that miR-1271 directly bound to the 3'untranslated region of HOXA5. This study indicated indicate that miR-1271 regulates NSCLC cell proliferation and invasion, via the down-regulation of HOXA5. Thus, miR-1271 may represent a potential therapeutic target for NSCLC intervention. - Highlights: • Overexpression of miR-1271 promoted proliferation and invasion of NSCLC cells. • miR-1271 inhibitor inhibited the proliferation and invasion of NSCLC cells. • miR-1271 targets 3′ UTR of HOXA5 in NSCLC cells. • miR-1271 negatively regulates HOXA5 in NSCLC cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Multiple Maize Reference Genomes Impact the Identification of Variants by Genome-Wide Association Study in a Diverse Inbred Panel

Use of a single reference genome for genome-wide association studies (GWAS) limits the gene space represented to that of a single accession. This limitation can complicate identification and characterization of genes located within presence–absence variations (PAVs). In this study, we present the draft de novo genome assembly of ‘PHJ89’, an ‘Oh43’-type inbred line of maize (Zea mays L.). From three separate reference genome assemblies (‘B73’, ‘PH207’, and PHJ89) that represent the predominant germplasm groups of maize, we generated three separate whole-seedling gene expression profiles and single nucleotide polymorphism (SNP) matrices from a panel of 942 diverse inbred lines. We identified 34,447 (B73), 39,672 (PH207), and 37,436 (PHJ89) transcripts that are not present in the respective reference genome assemblies. Genome-wide association studies were conducted in the 942 inbred panel with both the SNP and expression data values to map Sugarcane mosaic virus (SCMV) resistance. Highlighting the impact of alternative reference genomes in gene discovery, the GWAS results for SCMV resistance with expression values as a surrogate measure of PAV resulted in robust detection of the physical location of a known resistance gene when the B73 reference that contains the gene was used, but not the PH207 reference. This study provides the valuable resource of the Oh43-type PHJ89 genome assembly as well as SNP and expression data for 942 individuals generated from three different reference genomes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

The NASA Twins Study: The Effect of One Year in Space on Long-Chain Fatty Acid Desaturases and Elongases

Background: To date, there is no clear understanding of the effect of long-duration spaceflight on the major enzymes that govern the metabolism of omega-6 and omega-3 fatty acids. To address this gap in knowledge, we used data from the NASA Twins Study, which includes a multi-scale omic investigation of the changes that occurred during a year-long (340 days) human spaceflight. Embedded within the NASA Twins data are specific analytes associated with fatty acid metabolism. Objectives: To examine the long-chain fatty acid desaturases and elongases in a single human during one year in space. Method: One male twin was on board the International Space Station (ISS) for one year, while his monozygotic twin served as a genetically matched ground control. Longitudinal assessments included the genome, epigenome, transcriptome, proteome, metabolome, microbiome, and immunome during the mission, as well as six months before and after. The gene-specific fatty acid desaturase and elongase transcriptome data (FADS1, FADS2, ELOVL2 and ELOVL5) were extracted from untargeted RNA-seq measurements derived from white blood cell fractions. Results: Most data from the elongases and desaturases exhibited relatively similar expression profiles (R2>0.6) over time for the CD8, CD19, and LD cell fractions, indicating overall conservation of function within and between the subjects. Both cell-type and temporal specificity was observed in some cases, and some differences were also apparent between the poly-adenylated fraction (polyA) of processed RNAs vs. the ribo-depleted (ribo-) fraction. The flight subject showed a stronger enrichment of the Fatty Acid Metabolic processes pathway across almost all cell types (columns, CD4, CD8, CPT, LD), most especially in the ribodepleted fraction of RNA, but also with the polyA+ fraction of RNA. GSEA enrichment measures across three related Fatty Acid Metabolism pathways showed a differential between the ground and flight subject. Conclusions: There appears to be no persistent alteration of desaturase and elongase gene expression associated with one year in space. However, these data provide evidence that cellular lipid metabolism can be responsive and dynamic to spaceflight, even though it appears cell-type- and context-specific, most notably in terms of the fraction of RNA measured and the collection protocols. These results also provide new evidence of mid-flight spikes in expression of selected genes, which may indicate transient responses to specific insults during spaceflight.

Elongase↗
DOE OSTI2017

Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models

Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. - Highlights: • Hypertrophy (H) and hypertrophic carcinogenesis (C) were studied by toxicogenomics. • Important genes for H and C were selected by logistic ridge regression analysis. • Amino acid biosynthesis and oxidative responses may be involved in C. • Predictive models for H and C provided 94.8% and 82.7% accuracy, respectively. • The identified genes could be useful for assessment of liver hypertrophy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

PRELP (proline/arginine-rich end leucine-rich repeat protein) promotes osteoblastic differentiation of preosteoblastic MC3T3-E1 cells by regulating the β-catenin pathway

Proline/arginine-rich end leucine-rich repeat protein (PRELP) is a collagen-binding proteoglycan highly expressed in the developing bones. Recent studies indicated that PRELP could inhibit osteoclastogenesis as a NF-κB inhibitor. However, its role during osteoblast differentiation is still unclear. In this study, we confirmed that the expression of PRELP increased with the osteogenesis induction of preosteoblastic MC3T3-E1 cells. Down-regulation of PRELP expression by shRNA reduced ALP activity, mineralization and expression of osteogenic marker gene Runx2. Our microarray analysis data suggested that β-catenin may act as a hub gene in the PRELP-mediated gene network. We validated furtherly that PRELP knockdown could inhibit the level of connexin43, a key regulator of osteoblast differentiation by affecting β-catenin protein expression, and its nuclear translocation in MC3T3-E1 preosteoblasts. Therefore, this study established a new role of PRELP in modulating β-catenin/connexin43 pathway and osteoblast differentiation.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Molecular Basis of the Increase in Invertase Activity Elicited by Gravistimulation of Oat-Shoot Pulvini

An asymmetric (top vs. bottom) increase in invertase activity is elicited by gravistimulation in oatshoot pulvini starting within 3h after treatment. In order to analyze the regulation of invertase gene expression in this system, we examined the effect of gravistimulation on invertase mRNA induction. Total RNA and poly(A)(+)RNA, isolated from oat pulvini, and two oligonucleotide primers, corresponding to two conserved amino-acid sequences (NDPNG and WECPD) found in invertase from other species, were used for the Polymerase Chain Reaction (PCR). A partial-length cDNA (550 base pairs) was obtained and characterized. There was a 52 % deduced amino-acid sequence homology to that of carrot beta-fructosi- dase and a 48 % homology to that of tomato invertase. Northern blot analysis showed that there was an obvious transient accumulation of invertase mRNA elicited by gravistimulation of oat pulvini. The mRNA was rapidly induced to a maximum level at 1h following gravistimulation treatment and gradually decreased afterwards. The mRNA level in the bottom half of the oat pulvinus was significantly higher (five-fold) than that in the top half of the pulvinus tissue. The induction of invertase mRNA was consistent with the transient enhancement of invertase activity during the graviresponse of the pulvinus. These data indicate that the expression of the invertase gene(s) could be regulated by gravistimulation at the transcriptional and/or translational levels. Southern blot analysis showed that there were four genomic DNA fragments hybridized to the invertase cDNA. This suggests that an invertase gene family may exist in oat plants.

Wu, Liu-Lai↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection

Plant defense responses to pathogens involve massive transcriptional reprogramming. Recently, differential coexpression analysis has been developed to study the rewiring of gene networks through microarray data, which is becoming an important complement to traditional differential expression analysis. Using time-series microarray data of Arabidopsis thaliana infected with Pseudomonas syringae, we analyzed Arabidopsis defense responses to P. syringae through differential coexpression analysis. Overall, we found that differential coexpression was a common phenomenon of plant immunity. Genes that were frequently involved in differential coexpression tend to be related to plant immune responses. Importantly, many of those genes have similar average expression levels between normal plant growth and pathogen infection but have different coexpression partners. By integrating the Arabidopsis regulatory network into our analysis, we identified several transcription factors that may be regulators of differential coexpression during plant immune responses. We also observed extensive differential coexpression between genes within the same metabolic pathways. Several metabolic pathways, such as photosynthesis light reactions, exhibited significant changes in expression correlation between normal growth and pathogen infection. Taken together, differential coexpression analysis provides a new strategy for analyzing transcriptional data related to plant defense responses and new insights into the understanding of plant-pathogen interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Genome-Wide Analysis of Nitrate Transporter (NRT/NPF) Family in Sugarcane Saccharum spontaneum L.

Nitrate is the predominant nitrogen source for plant growth and development. However, sugarcane, globally used as the primary sugar crop and biofuel feedstock, displays a low nitrate use efficiency due to a low capacity in storing nitrate in shoots. It is well studied that the nitrate transporter (NRT/NPF) family functions as the gatekeeper in governing nitrogen uptake and distribution, and optimizing nitrogen utilization in plants. This makes it a promising target for improving nitrogen use efficiency in sugarcane. Here, we carried out a comprehensive analysis of NRT/NPF genes at a genome-wide scale in Saccharum spontaneum. A BLAST search of NRT/NPF genes was initially performed against recently released sugarcane genome, followed by phylogenetic, gene structure and protein motif analysis. Additionally, NRT/NPF gene expression profile from various tissues was obtained from RNA-seq data analysis. As a result, we identified 178 NPF, 20 NRT2, and 6 NRT3 genes which spread across all 8 monoploid chromosomes. NPF and NRT3 exhibit high levels of genetic diversities as opposed to NRT2 which is more evolutionarily conserved. Interestingly, several SsNPF genes are products of gene fusions of several tandem duplications, which provide valuable structural resources for functional characterization of nitrate transporters. Moreover, several genes are tissue-specific expressed, indicating roles in tissue-specific nitrate translocations. A substantial number of NRT/NPF genes are heterogeneous in terms of their gene structures and mRNA abundance. Taken together, our work provides a genetic foundation for future investigations of molecular and physiological functions of sugarcane nitrate transporters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Identification of potential target genes of ROR-alpha in THP1 and HUVEC cell lines

ROR-alpha is a nuclear receptor, activity of which can be modulated by natural or synthetic ligands. Due to its possible involvement in, and potential therapeutic target for atherosclerosis, we aimed to identify ROR-alpha target genes in monocytic and endothelial cell lines. We performed chromatin immunoprecipitation (ChIP) followed by tiling array (ChIP-on-chip) for ROR-alpha in monocytic cell line THP1 and endothelial cell line HUVEC. Following bioinformatic analysis of the array data, we tested four candidate genes in terms of dependence of their expression level on ligand-mediated ROR-alpha activity, and two of them in terms of promoter occupancy by ROR-alpha. Bioinformatic analyses of ChIP-on-chip data suggested that ROR-alpha binds to genomic regions near the transcription start site (TSS) of more than 3000 genes in THP1 and HUVEC. Potential ROR-alpha target genes in both cell types seem to be involved mainly in membrane receptor activity, signal transduction and ion transport. While SPP1 and IKBKA were shown to be direct target genes of ROR-alpha in THP1 monocytes, inflammation related gene HMOX1 and heat shock protein gene HSPA8 were shown to be potential target genes of ROR-alpha. Our results suggest that ROR-alpha may regulate signaling receptor activity, and transmembrane transport activity through its potential target genes. ROR-alpha seems also to play role in cellular sensitivity to environmental substances like arsenite and chloroprene. Although, the expression analyses have shown that synthetic ROR-alpha ligands can modulate some of potential ROR-alpha target genes, functional significance of ligand-dependent modulation of gene expression needs to be confirmed with further analyses.

60 APPLIED LIFE SCIENCES↗