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1.  ‘MicroRNA Targets’, a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana 
BioData Mining  2012;5:7.
The AthaMap database generates a genome-wide map for putative transcription factor binding sites for A. thaliana. When analyzing transcriptional regulation using AthaMap it may be important to learn which genes are also post-transcriptionally regulated by inhibitory RNAs. Therefore, a unified database for transcriptional and post-transcriptional regulation will be highly useful for the analysis of gene expression regulation.
To identify putative microRNA target sites in the genome of A. thaliana, processed mature miRNAs from 243 annotated miRNA genes were used for screening with the psRNATarget web server. Positional information, target genes and the psRNATarget score for each target site were annotated to the AthaMap database. Furthermore, putative target sites for small RNAs from seven small RNA transcriptome datasets were used to determine small RNA target sites within the A. thaliana genome.
Putative 41,965 genome wide miRNA target sites and 10,442 miRNA target genes were identified in the A. thaliana genome. Taken together with genes targeted by small RNAs from small RNA transcriptome datasets, a total of 16,600 A. thaliana genes are putatively regulated by inhibitory RNAs. A novel web-tool, ‘MicroRNA Targets’, was integrated into AthaMap which permits the identification of genes predicted to be regulated by selected miRNAs. The predicted target genes are displayed with positional information and the psRNATarget score of the target site. Furthermore, putative target sites of small RNAs from selected tissue datasets can be identified with the new ‘Small RNA Targets’ web-tool.
The integration of predicted miRNA and small RNA target sites with transcription factor binding sites will be useful for AthaMap-assisted gene expression analysis. URL:
PMCID: PMC3410767  PMID: 22800758
Arabidopsis thaliana; AthaMap; MicroRNAs; Small RNAs; Post-transcriptional regulation
2.  AthaMap web tools for the analysis and identification of co-regulated genes 
Nucleic Acids Research  2006;35(Database issue):D857-D862.
The AthaMap database generates a map of cis-regulatory elements for the whole Arabidopsis thaliana genome. This database has been extended by new tools to identify common cis-regulatory elements in specific regions of user-provided gene sets. A resulting table displays all cis-regulatory elements annotated in AthaMap including positional information relative to the respective gene. Further tables show overviews with the number of individual transcription factor binding sites (TFBS) present and TFBS common to the whole set of genes. Over represented cis-elements are easily identified. These features were used to detect specific enrichment of drought-responsive elements in cold-induced genes. For identification of co-regulated genes, the output table of the colocalization function was extended to show the closest genes and their relative distances to the colocalizing TFBS. Gene sets determined by this function can be used for a co-regulation analysis in microarray gene expression databases such as Genevestigator or PathoPlant. Additional improvements of AthaMap include display of the gene structure in the sequence window and a significant data increase. AthaMap is freely available at .
PMCID: PMC1761422  PMID: 17148485
3.  AthaMap-assisted transcription factor target gene identification in Arabidopsis thaliana 
The AthaMap database generates a map of potential transcription factor binding sites (TFBS) and small RNA target sites in the Arabidopsis thaliana genome. The database contains sites for 115 different transcription factors (TFs). TFBS were identified with positional weight matrices (PWMs) or with single binding sites. With the new web tool ‘Gene Identification’, it is possible to identify potential target genes for selected TFs. For these analyses, the user can define a region of interest of up to 6000 bp in all annotated genes. For TFBS determined with PWMs, the search can be restricted to high-quality TFBS. The results are displayed in tables that identify the gene, position of the TFBS and, if applicable, individual score of the TFBS. In addition, data files can be downloaded that harbour positional information of TFBS of all TFs in a region between −2000 and +2000 bp relative to the transcription or translation start site. Also, data content of AthaMap was increased and the database was updated to the TAIR8 genome release.
Database URL:
PMCID: PMC3011983  PMID: 21177332
4.  AthaMap web tools for database-assisted identification of combinatorial cis-regulatory elements and the display of highly conserved transcription factor binding sites in Arabidopsis thaliana 
Nucleic Acids Research  2005;33(Web Server issue):W397-W402.
The AthaMap database generates a map of cis-regulatory elements for the Arabidopsis thaliana genome. AthaMap contains more than 7.4 × 106 putative binding sites for 36 transcription factors (TFs) from 16 different TF families. A newly implemented functionality allows the display of subsets of higher conserved transcription factor binding sites (TFBSs). Furthermore, a web tool was developed that permits a user-defined search for co-localizing cis-regulatory elements. The user can specify individually the level of conservation for each TFBS and a spacer range between them. This web tool was employed for the identification of co-localizing sites of known interacting TFs and TFs containing two DNA-binding domains. More than 1.8 × 105 combinatorial elements were annotated in the AthaMap database. These elements can also be used to identify more complex co-localizing elements consisting of up to four TFBSs. The AthaMap database and the connected web tools are a valuable resource for the analysis and the prediction of gene expression regulation at .
PMCID: PMC1160156  PMID: 15980498
5.  AthaMap: an online resource for in silico transcription factor binding sites in the Arabidopsis thaliana genome 
Nucleic Acids Research  2004;32(Database issue):D368-D372.
Gene expression is controlled mainly by the binding of transcription factors to regulatory sequences. To generate a genomic map for regulatory sequences, the Arabidopsis thaliana genome was screened for putative transcription factor binding sites. Using publicly available data from the TRANSFAC database and from publications, alignment matrices for 23 transcription factors of 13 different factor families were used with the pattern search program Patser to determine the genomic positions of more than 2.4 × 106 putative binding sites. Due to the dense clustering of genes and the observation that regulatory sequences are not restricted to upstream regions, the prediction of binding sites was performed for the whole genome. The genomic positions and the underlying data were imported into the newly developed AthaMap database. This data can be accessed by positional information or the Arabidopsis Genome Initiative identification number. Putative binding sites are displayed in the defined region. Data on the matrices used and on the thresholds applied in these screens are given in the database. Considering the high density of sites it will be a valuable resource for generating models on gene expression regulation. The data are available at
PMCID: PMC308752  PMID: 14681436
6.  PathoPlant®: a platform for microarray expression data to analyze co-regulated genes involved in plant defense responses 
Nucleic Acids Research  2006;35(Database issue):D841-D845.
Plants react to pathogen attack by expressing specific proteins directed toward the infecting pathogens. This involves the transcriptional activation of specific gene sets. PathoPlant®, a database on plant–pathogen interactions and signal transduction reactions, has now been complemented by microarray gene expression data from Arabidopsis thaliana subjected to pathogen infection and elicitor treatment. New web tools enable identification of plant genes regulated by specific stimuli. Sets of genes co-regulated by multiple stimuli can be displayed as well. A user-friendly web interface was created for the submission of gene sets to be analyzed. This results in a table, listing the stimuli that act either inducing or repressing on the respective genes. The search can be restricted to certain induction factors to identify, e.g. strongly up- or down-regulated genes. Up to three stimuli can be combined with the option of induction factor restriction to determine similarly regulated genes. To identify common cis-regulatory elements in co-regulated genes, a resulting gene list can directly be exported to the AthaMap database for analysis. PathoPlant is freely accessible at .
PMCID: PMC1669748  PMID: 17099232
7.  Internet Resources for Gene Expression Analysis in Arabidopsis thaliana 
Current Genomics  2008;9(6):375-380.
The number of online databases and web-tools for gene expression analysis in Arabidopsis thaliana has increased tremendously during the last years. These resources permit the database-assisted identification of putative cis-regulatory DNA sequences, their binding proteins, and the determination of common cis-regulatory motifs in coregulated genes. DNA binding proteins may be predicted by the type of cis-regulatory motif. Further questions of combinatorial control based on the interaction of DNA binding proteins and the colocalization of cis-regulatory motifs can be addressed. The database-assisted spatial and temporal expression analysis of DNA binding proteins and their target genes may help to further refine experimental approaches. Signal transduction pathways upstream of regulated genes are not yet fully accessible in databases mainly because they need to be manually annotated. This review focuses on the use of the AthaMap and PathoPlant® databases for gene expression regulation analysis and discusses similar and complementary online databases and web-tools. Online databases are helpful for the development of working hypothesis and for designing subsequent experiments.
PMCID: PMC2691667  PMID: 19506727
Bioinformatics; databases; gene expression; plants; transcription; web-server.
8.  Niche adaptation by expansion and reprogramming of general transcription factors 
Experimental analysis of TFB family proteins in a halophilic archaeon reveals complex environment-dependent fitness contributions. Gene conversion events among these proteins can generate novel niche adaptation capabilities, a process that may have contributed to archaeal adaptation to extreme environments.
Evolution of archaeal lineages correlate with duplication events in the TFB family.Each TFB is required for adaptation to multiple environments.The relative fitness contributions of TFBs change with environmental context.Changes in the regulation of duplicated TFBs can generate new adaptation capabilities.
The evolutionary success of an organism depends on its ability to continually adapt to changes in the patterns of constant, periodic, and transient challenges within its environment. This process of ‘niche adaptation' requires reprogramming of the organism's environmental response networks by reorganizing interactions among diverse parts including environmental sensors, signal transducers, and transcriptional and post-transcriptional regulators. Gene duplications have been discovered to be one of the principal strategies in this process, especially for reprogramming of gene regulatory networks (GRNs). Whereas eukaryotes require dozens of factors for recruitment of RNA polymerase, archaea require just two general transcription factors (GTFs) that are orthologous to eukaryotic TFIIB (TFB in archaea) and TATA-binding protein (TBP) (Bell et al, 1998). Both of these GTFs have expanded extensively in nearly 50% of all archaea whose genomes have been fully sequenced. The phylogenetic analysis presented in this study reveal lineage-specific expansions of TFBs, suggesting that they might encode functionally specialized gene regulatory programs for the unique environments to which these organisms have adapted. This hypothesis is particularly appealing when we consider that the greatest expansion is observed within the group of halophilic archaea whose habitats are associated with routine and dynamic changes in a number of environmental factors including light, temperature, oxygen, salinity, and ionic composition (Rodriguez-Valera, 1993; Litchfield, 1998).
We have previously demonstrated that variations in the expanded set of TFBs (a through e) in Halobacterium salinarum NRC-1 manifests at the level of physical interactions within and across the two families, their DNA-binding specificity, their differential regulation in varying environments, and, ultimately, on the large-scale segregation of transcription of all genes into overlapping yet distinct sets of functionally related groups (Facciotti et al, 2007). We have extended findings from this earlier study with a systematic survey of the fitness consequences of perturbing the TFB network of H. salinarum NRC-1 across 17 environments. Notably, each TFB conferred fitness in two or more environmental conditions tested, and the relative fitness contributions (see Table I) of the five TFBs varied significantly by environment. From an evolutionary perspective, the relationships among these fitness landscapes reveal that two classes of TFBs (c/g- and f-type) appear to have played an important role in the evolution of halophilic archaea by overseeing regulation of core physiological capabilities in these organisms. TFBs of the other clades (b/d and a/e) seem to have emerged much more recently through gene duplications or horizontal gene transfers (HGTs) and are being utilized for adaptation to specialized environmental conditions.
We also investigated higher-order functional interactions and relationships among the duplicated TFBs by performing competition experiments and by mapping genetic interactions in different environments. This demonstrated that depending on environmental context, the TFBs have strikingly different functional hierarchies and genetic interactions with one another. This is remarkable as it makes each TFB essential albeit at different times in a dynamically changing environment.
In order to understand the process by which such gene family expansions shape architecture and functioning of a GRN, we performed integrated analysis of phylogeny, physical interactions, regulation, and fitness landscapes of the seven TFBs in H. salinarum NRC-1. This revealed that evolution of both their protein-coding sequence and their promoter has been instrumental in the encoding of environment-specific regulatory programs. Importantly, the convergent and divergent evolution of regulation and binding properties of TFBs suggested that, aside from HGT and random mutations, a third plausible (and perhaps most interesting) mechanism for acquiring a novel TFB variant is through gene conversion. To test this hypothesis, we synthesized a novel TFBx by transferring TFBa/e clade-specific residues to a TFBd backbone, transformed this variant under the control of either the TFBd or the TFBe promoter (PtfbD or PtfbE) into three different host genetic backgrounds (Δura3 (parent), ΔtfbD, and ΔtfbE), and analyzed fitness and gene expression patterns during growth at 25 and 37°C. This showed that gene conversion events spanning the coding sequence and the promoter, environmental context, and genetic background of the host are all extremely influential in the functional integration of a TFB into the GRN. Importantly, this analysis suggested that altering the regulation of an existing set of expanded TFBs might be an efficient mechanism to reprogram the GRN to rapidly generate novel niche adaptation capability. We have confirmed this experimentally by increasing fitness merely by moving tfbE to PtfbD control, and by generating a completely novel phenotype (biofilm-like appearance) by overexpression of tfbE.
Altogether this study clearly demonstrates that archaea can rapidly generate novel niche adaptation programs by simply altering regulation of duplicated TFBs. This is significant because expansions in the TFB family is widespread in archaea, a class of organisms that not only represent 20% of biomass on earth but are also known to have colonized some of the most extreme environments (DeLong and Pace, 2001). This strategy for niche adaptation is further expanded through interactions of the multiple TFBs with members of other expanded TF families such as TBPs (Facciotti et al, 2007) and sequence-specific regulators (e.g. Lrp family (Peeters and Charlier, 2010)). This is analogous to combinatorial solutions for other complex biological problems such as recognition of pathogens by Toll-like receptors (Roach et al, 2005), generation of antibody diversity by V(D)J recombination (Early et al, 1980), and recognition and processing of odors (Malnic et al, 1999).
Numerous lineage-specific expansions of the transcription factor B (TFB) family in archaea suggests an important role for expanded TFBs in encoding environment-specific gene regulatory programs. Given the characteristics of hypersaline lakes, the unusually large numbers of TFBs in halophilic archaea further suggests that they might be especially important in rapid adaptation to the challenges of a dynamically changing environment. Motivated by these observations, we have investigated the implications of TFB expansions by correlating sequence variations, regulation, and physical interactions of all seven TFBs in Halobacterium salinarum NRC-1 to their fitness landscapes, functional hierarchies, and genetic interactions across 2488 experiments covering combinatorial variations in salt, pH, temperature, and Cu stress. This systems analysis has revealed an elegant scheme in which completely novel fitness landscapes are generated by gene conversion events that introduce subtle changes to the regulation or physical interactions of duplicated TFBs. Based on these insights, we have introduced a synthetically redesigned TFB and altered the regulation of existing TFBs to illustrate how archaea can rapidly generate novel phenotypes by simply reprogramming their TFB regulatory network.
PMCID: PMC3261711  PMID: 22108796
evolution by gene family expansion; fitness; niche adaptation; reprogramming of gene regulatory network; transcription factor B
9.  CATMA, a comprehensive genome-scale resource for silencing and transcript profiling of Arabidopsis genes 
BMC Bioinformatics  2007;8:400.
The Complete Arabidopsis Transcript MicroArray (CATMA) initiative combines the efforts of laboratories in eight European countries [1] to deliver gene-specific sequence tags (GSTs) for the Arabidopsis research community. The CATMA initiative offers the power and flexibility to regularly update the GST collection according to evolving knowledge about the gene repertoire. These GST amplicons can easily be reamplified and shared, subsets can be picked at will to print dedicated arrays, and the GSTs can be cloned and used for other functional studies. This ongoing initiative has already produced approximately 24,000 GSTs that have been made publicly available for spotted microarray printing and RNA interference.
GSTs from the CATMA version 2 repertoire (CATMAv2, created in 2002) were mapped onto the gene models from two independent Arabidopsis nuclear genome annotation efforts, TIGR5 and PSB-EuGène, to consolidate a list of genes that were targeted by previously designed CATMA tags. A total of 9,027 gene models were not tagged by any amplified CATMAv2 GST, and 2,533 amplified GSTs were no longer predicted to tag an updated gene model. To validate the efficacy of GST mapping criteria and design rules, the predicted and experimentally observed hybridization characteristics associated to GST features were correlated in transcript profiling datasets obtained with the CATMAv2 microarray, confirming the reliability of this platform. To complete the CATMA repertoire, all 9,027 gene models for which no GST had yet been designed were processed with an adjusted version of the Specific Primer and Amplicon Design Software (SPADS). A total of 5,756 novel GSTs were designed and amplified by PCR from genomic DNA. Together with the pre-existing GST collection, this new addition constitutes the CATMAv3 repertoire. It comprises 30,343 unique amplified sequences that tag 24,202 and 23,009 protein-encoding nuclear gene models in the TAIR6 and EuGène genome annotations, respectively. To cover the remaining untagged genes, we identified 543 additional GSTs using less stringent design criteria and designed 990 sequence tags matching multiple members of gene families (Gene Family Tags or GFTs) to cover any remaining untagged genes. These latter 1,533 features constitute the CATMAv4 addition.
To update the CATMA GST repertoire, we designed 7,289 additional sequence tags, bringing the total number of tagged TAIR6-annotated Arabidopsis nuclear protein-coding genes to 26,173. This resource is used both for the production of spotted microarrays and the large-scale cloning of hairpin RNA silencing vectors. All information about the resulting updated CATMA repertoire is available through the CATMA database
PMCID: PMC2147040  PMID: 17945016
10.  The study of Nickel Resistant Bacteria (NiRB) isolated from wastewaters polluted with different industrial sources 
Pollution due to the heavy metals is a problem that may have negative consequences on the hydrosphere. One of the best procedures in removing the toxic metals from the environment is using metal resistant bacteria.
In the present study eight nickel resistant bacteria were isolated from industrial wastewaters. Three of them were selected as the most resistant based on their Maximum tolerable concentration (8, 16 and 24 mM Ni2+). Their identification was done according to morphological, biochemical characteristics and 16SrDNA gene sequencing and they were identified as Cupriavidus sp ATHA3, Klebsiella oxytoca ATHA6 and Methylobacterium sp ATHA7. The accession numbers assigned to ATHA3, ATHA6 and ATHA7 strains are JX120152, JX196648 and JX457333 respectively. The Growth rate of the most resistant isolate, Klebsiella oxytoca strain ATHA6, in the presence of Ni2+ and the reduction in Ni2+ concentration was revealed that K oxytoca ATHA6 could decrease 83 mg/mL of nickel from the medium after 3 days.
It can be concluded that the identified Ni resistant bacteria could be valuable for the bioremediation of Ni polluted waste water and sewage.
PMCID: PMC3931474  PMID: 24475932
Nickel resistant bacteria (NiRB); Maximum tolerance concentration; Multiple metal resistance determination; 16SrDNA; Wastewater
11.  Evolutionary rates and patterns for human transcription factor binding sites derived from repetitive DNA 
BMC Genomics  2008;9:226.
The majority of human non-protein-coding DNA is made up of repetitive sequences, mainly transposable elements (TEs). It is becoming increasingly apparent that many of these repetitive DNA sequence elements encode gene regulatory functions. This fact has important evolutionary implications, since repetitive DNA is the most dynamic part of the genome. We set out to assess the evolutionary rate and pattern of experimentally characterized human transcription factor binding sites (TFBS) that are derived from repetitive versus non-repetitive DNA to test whether repeat-derived TFBS are in fact rapidly evolving. We also evaluated the position-specific patterns of variation among TFBS to look for signs of functional constraint on TFBS derived from repetitive and non-repetitive DNA.
We found numerous experimentally characterized TFBS in the human genome, 7–10% of all mapped sites, which are derived from repetitive DNA sequences including simple sequence repeats (SSRs) and TEs. TE-derived TFBS sequences are far less conserved between species than TFBS derived from SSRs and non-repetitive DNA. Despite their rapid evolution, several lines of evidence indicate that TE-derived TFBS are functionally constrained. First of all, ancient TE families, such as MIR and L2, are enriched for TFBS relative to younger families like Alu and L1. Secondly, functionally important positions in TE-derived TFBS, specifically those residues thought to physically interact with their cognate protein binding factors (TF), are more evolutionarily conserved than adjacent TFBS positions. Finally, TE-derived TFBS show position-specific patterns of sequence variation that are highly distinct from random patterns and similar to the variation seen for non-repeat derived sequences of the same TFBS.
The abundance of experimentally characterized human TFBS that are derived from repetitive DNA speaks to the substantial regulatory effects that this class of sequence has on the human genome. The unique evolutionary properties of repeat-derived TFBS are perhaps even more intriguing. TE-derived TFBS in particular, while clearly functionally constrained, evolve extremely rapidly relative to non-repeat derived sites. Such rapidly evolving TFBS are likely to confer species-specific regulatory phenotypes, i.e. divergent expression patterns, on the human evolutionary lineage. This result has practical implications with respect to the widespread use of evolutionary conservation as a surrogate for functionally relevant non-coding DNA. Most TE-derived TFBS would be missed using the kinds of sequence conservation-based screens, such as phylogenetic footprinting, that are used to help characterize non-coding DNA. Thus, the very TFBS that are most likely to yield human-specific characteristics will be neglected by the comparative genomic techniques that are currently de rigeur for the identification of novel regulatory sites.
PMCID: PMC2397414  PMID: 18485226
12.  Identifying Functional Transcription Factor Binding Sites in Yeast by Considering Their Positional Preference in the Promoters 
PLoS ONE  2013;8(12):e83791.
Transcription factor binding site (TFBS) identification plays an important role in deciphering gene regulatory codes. With comprehensive knowledge of TFBSs, one can understand molecular mechanisms of gene regulation. In the recent decades, various computational approaches have been proposed to predict TFBSs in the genome. The TFBS dataset of a TF generated by each algorithm is a ranked list of predicted TFBSs of that TF, where top ranked TFBSs are statistically significant ones. However, whether these statistically significant TFBSs are functional (i.e. biologically relevant) is still unknown. Here we develop a post-processor, called the functional propensity calculator (FPC), to assign a functional propensity to each TFBS in the existing computationally predicted TFBS datasets. It is known that functional TFBSs reveal strong positional preference towards the transcriptional start site (TSS). This motivates us to take TFBS position relative to the TSS as the key idea in building our FPC. Based on our calculated functional propensities, the TFBSs of a TF in the original TFBS dataset could be reordered, where top ranked TFBSs are now the ones with high functional propensities. To validate the biological significance of our results, we perform three published statistical tests to assess the enrichment of Gene Ontology (GO) terms, the enrichment of physical protein-protein interactions, and the tendency of being co-expressed. The top ranked TFBSs in our reordered TFBS dataset outperform the top ranked TFBSs in the original TFBS dataset, justifying the effectiveness of our post-processor in extracting functional TFBSs from the original TFBS dataset. More importantly, assigning functional propensities to putative TFBSs enables biologists to easily identify which TFBSs in the promoter of interest are likely to be biologically relevant and are good candidates to do further detailed experimental investigation. The FPC is implemented as a web tool at
PMCID: PMC3873331  PMID: 24386279
13.  De novo assembly and characterization of Camelina sativa transcriptome by paired-end sequencing 
BMC Genomics  2013;14:146.
Biofuels extracted from the seeds of Camelina sativa have recently been used successfully as environmentally friendly jet-fuel to reduce greenhouse gas emissions. Camelina sativa is genetically very close to Arabidopsis thaliana, and both are members of the Brassicaceae. Although public databases are currently available for some members of the Brassicaceae, such as A. thaliana, A. lyrata, Brassica napus, B. juncea and B. rapa, there are no public Expressed Sequence Tags (EST) or genomic data for Camelina sativa. In this study, a high-throughput, large-scale RNA sequencing (RNA-seq) of the Camelina sativa transcriptome was carried out to generate a database that will be useful for further functional analyses.
Approximately 27 million clean “reads” filtered from raw reads by removal of adaptors, ambiguous reads and low-quality reads (2.42 gigabase pairs) were generated by Illumina paired-end RNA-seq technology. All of these clean reads were assembled de novo into 83,493 unigenes and 103,196 transcripts using SOAPdenovo and Trinity, respectively. The average length of the transcripts generated by Trinity was 697 bp (N50 = 976), which was longer than the average length of unigenes (319 bp, N50 = 346 bp). Nonetheless, the assembly generated by SOAPdenovo produced similar number of non-redundant hits (22,435) with that of Trinity (22,433) in BLASTN searches of the Arabidopsis thaliana CDS sequence database (TAIR). Four public databases, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Swiss-prot, NCBI non-redundant protein (NR), and the Cluster of Orthologous Groups (COG), were used for unigene annotation; 67,791 of 83,493 unigenes (81.2%) were finally annotated with gene descriptions or conserved protein domains that were mapped to 25,329 non-redundant protein sequences. We mapped 27,042 of 83,493 unigenes (32.4%) to 119 KEGG metabolic pathways.
This is the first report of a transcriptome database for Camelina sativa, an environmentally important member of the Brassicaceae. We showed that C. savita is closely related to Arabidopsis spp. and more distantly related to Brassica spp. Although the majority of annotated genes had high sequence identity to those of A. thaliana, a substantial proportion of disease-resistance genes (NBS-encoding LRR genes) were instead more closely similar to the genes of other Brassicaceae; these genes included BrCN, BrCNL, BrNL, BrTN, BrTNL in B. rapa. As plant genomes are under long-term selection pressure from environmental stressors, conservation of these disease-resistance genes in C. sativa and B. rapa genomes implies that they are exposed to the threats from closely-related pathogens in their natural habitats.
PMCID: PMC3635884  PMID: 23496985
Brassicaceae; Camelina sativa; Transcriptome; de novo; Paired-end sequencing; NBS-LRR
14.  Genetic and transcriptomic analysis of transcription factor genes in the model halophilic Archaeon: coordinate action of TbpD and TfbA 
BMC Genetics  2007;8:61.
Archaea are prokaryotic organisms with simplified versions of eukaryotic transcription systems. Genes coding for the general transcription factors TBP and TFB are present in multiple copies in several Archaea, including Halobacterium sp. NRC-1. Multiple TBP and TFBs have been proposed to participate in transcription of genes via recognition and recruitment of RNA polymerase to different classes of promoters.
We attempted to knock out all six TBP and seven TFB genes in Halobacterium sp. NRC-1 using the ura3-based gene deletion system. Knockouts were obtained for six out of thirteen genes, tbpCDF and tfbACG, indicating that they are not essential for cell viability under standard conditions. Screening of a population of 1,000 candidate mutants showed that genes which did not yield mutants contained less that 0.1% knockouts, strongly suggesting that they are essential. The transcriptomes of two mutants, ΔtbpD and ΔtfbA, were compared to the parental strain and showed coordinate down regulation of many genes. Over 500 out of 2,677 total genes were regulated in the ΔtbpD and ΔtfbA mutants with 363 regulated in both, indicating that over 10% of genes in both strains require the action of both TbpD and TfbA for normal transcription. Culturing studies on the ΔtbpD and ΔtfbA mutant strains showed them to grow more slowly than the wild-type at an elevated temperature, 49°C, and they showed reduced viability at 56°C, suggesting TbpD and TfbA are involved in the heat shock response. Alignment of TBP and TFB protein sequences suggested the expansion of the TBP gene family, especially in Halobacterium sp. NRC-1, and TFB gene family in representatives of five different genera of haloarchaea in which genome sequences are available.
Six of thirteen TBP and TFB genes of Halobacterium sp. NRC-1 are non-essential under standard growth conditions. TbpD and TfbA coordinate the expression of over 10% of the genes in the NRC-1 genome. The ΔtbpD and ΔtfbA mutant strains are temperature sensitive, possibly as a result of down regulation of heat shock genes. Sequence alignments suggest the existence of several families of TBP and TFB transcription factors in Halobacterium which may function in transcription of different classes of genes.
PMCID: PMC2121645  PMID: 17892563
15.  TFB1 or TFB2 is sufficient for Thermococcus kodakaraensis viability and for basal transcription in vitro 
Journal of molecular biology  2006;367(2):344-357.
Archaeal RNA polymerases (RNAPs) are most similar to eukaryotic RNAP II (Pol II) but require the support of only two archaeal general transcription factors, TBP (TATA-box binding protein) and TFB (archaeal homologue of the eukaryotic general transcription factors TFIIB) to initiate basal transcription. However, many archaeal genomes encode more than one TFB and/or TBP leading to the hypothesis that different TFB/TBP combinations may be employed to direct initiation from different promoters in Archaea. As a first test of this hypothesis, we have determined the ability of RNAP purified from Thermococcus kodakaraensis (T.k.) to initiate transcription from a variety of T.k. promoters in vitro when provided with T.k. TBP and either TFB1 or TFB2, the two TFBs encoded in the T.k. genome. With every promoter active in vitro, transcription initiation occurred with either TFB1 or TFB2 although the optimum salt concentration for initiation was generally higher for TFB2 (~250 mM K+) than for TFB1 (~200 mM K+). Consistent with this functional redundancy in vitro, T.k. strains have been constructed with the TFB1- (tfb1; TK1280) or TFB2- (tfb2; TK2287) encoding gene deleted. These mutants exhibit no detectable growth defects under laboratory conditions. Domain swapping between TFB1 and TFB2 has identified a central region that contributes to the salt sensitivity of TFB activity, and deleting residues predicted to form the tip of the B-finger region of TFB2 had no detectable effects on promoter recognition or transcription initiation but did eliminate the production of very short (≤ 5 nt) abortive transcripts.
PMCID: PMC1855253  PMID: 17275836
Archaea; transcription factor B; promoter recognition; RNA polymerase
16.  Cell-type specific analysis of translating RNAs in developing flowers reveals new levels of control 
Combining translating ribosome affinity purification with RNA-seq for cell-specific profiling of translating RNAs in developing flowers.Cell type comparisons of cell type-specific hormone responses, promoter motifs, coexpressed cognate binding factor candidates, and splicing isoforms.Widespread post-transcriptional regulation at both the intron splicing and translational stages.A new class of noncoding RNAs associated with polysomes.
What constitutes a differentiated cell type? How much do cell types differ in their transcription of genes? The development and functions of tissues rely on constant interactions among distinct and nonequivalent cell types. Answering these questions will require quantitative information on transcriptomes, proteomes, protein–protein interactions, protein–nucleic acid interactions, and metabolomes at cellular resolution. The systems approaches emerging in biology promise to explain properties of biological systems based on genome-wide measurements of expression, interaction, regulation, and metabolism. To facilitate a systems approach, it is essential first to capture such components in a global manner, ideally at cellular resolution.
Recently, microarray analysis of transcriptomes has been extended to a cellular level of resolution by using laser microdissection or fluorescence-activated sorting (for review, see Nelson et al, 2008). These methods have been limited by stresses associated with cellular separation and isolation procedures, and biases associated with mandatory RNA amplification steps. A newly developed method, translating ribosome affinity purification (TRAP; Zanetti et al, 2005; Heiman et al, 2008; Mustroph et al, 2009), circumvents these problems by epitopetagging a ribosomal protein in specific cellular domains to selectively purify polysomes. We combined TRAP with deep sequencing, which we term TRAP-seq, to provide cell-level spatiotemporal maps for Arabidopsis early floral development at single-base resolution.
Flower development in Arabidopsis has been studied extensively and is one of the best understood aspects of plant development (for review, see Krizek and Fletcher, 2005). Genetic analysis of homeotic mutants established the ABC model, in which three classes of regulatory genes, A, B and C, work in a combinatorial manner to confer organ identities of four whorls (Coen and Meyerowitz, 1991). Each class of regulatory gene is expressed in a specific and evolutionarily conserved domain, and the action of the class A, B and C genes is necessary for specification of organ identity (Figure 1A).
Using TRAP-seq, we purified cell-specific translating mRNA populations, which we and others call the translatome, from the A, B and C domains of early developing flowers, in which floral patterning and the specification of floral organs is established. To achieve temporal specificity, we used a floral induction system to facilitate collection of early stage flowers (Wellmer et al, 2006). The combination of TRAP-seq with domain-specific promoters and this floral induction system enabled fine spatiotemporal isolation of translating mRNA in specific cellular domains, and at specific developmental stages.
Multiple lines of evidence confirmed the specificity of this approach, including detecting the expression in expected domains but not in other domains for well-studied flower marker genes and known physiological functions (Figures 1B–D and 2A–C). Furthermore, we provide numerous examples from flower development in which a spatiotemporal map of rigorously comparable cell-specific translatomes makes possible new views of the properties of cell domains not evident in data obtained from whole organs or tissues, including patterns of transcription and cis-regulation, new physiological differences among cell domains and between flower stages, putative hormone-active centers, and splicing events specific for flower domains (Figure 2A–D). Such findings may provide new targets for reverse genetics studies and may aid in the formulation and validation of interaction and pathway networks.
Beside cellular heterogeneity, the transcriptome is regulated at several steps through the life of mRNA molecules, which are not directly available through traditional transcriptome profiling of total mRNA abundance. By comparing the translatome and transcriptome, we integratively profiled two key posttranscriptional control points, intron splicing and translation state. From our translatome-wide profiling, we (i) confirmed that both posttranscriptional regulation control points were used by a large portion of the transcriptome; (ii) identified a number of cis-acting features within the coding or noncoding sequences that correlate with splicing or translation state; and (iii) revealed correlation between each regulation mechanism and gene function. Our transcriptome-wide surveys have highlighted target genes transcripts of which are probably under extensive posttranscriptional regulation during flower development.
Finally, we reported the finding of a large number of polysome-associated ncRNAs. About one-third of all annotated ncRNA in the Arabidopsis genome were observed co-purified with polysomes. Coding capacity analysis confirmed that most of them are real ncRNA without conserved ORFs. The group of polysome-associated ncRNA reported in this study is a potential new addition to the expanding riboregulator catalog; they could have roles in translational regulation during early flower development.
Determining both the expression levels of mRNA and the regulation of its translation is important in understanding specialized cell functions. In this study, we describe both the expression profiles of cells within spatiotemporal domains of the Arabidopsis thaliana flower and the post-transcriptional regulation of these mRNAs, at nucleotide resolution. We express a tagged ribosomal protein under the promoters of three master regulators of flower development. By precipitating tagged polysomes, we isolated cell type-specific mRNAs that are probably translating, and quantified those mRNAs through deep sequencing. Cell type comparisons identified known cell-specific transcripts and uncovered many new ones, from which we inferred cell type-specific hormone responses, promoter motifs and coexpressed cognate binding factor candidates, and splicing isoforms. By comparing translating mRNAs with steady-state overall transcripts, we found evidence for widespread post-transcriptional regulation at both the intron splicing and translational stages. Sequence analyses identified structural features associated with each step. Finally, we identified a new class of noncoding RNAs associated with polysomes. Findings from our profiling lead to new hypotheses in the understanding of flower development.
PMCID: PMC2990639  PMID: 20924354
Arabidopsis; flower; intron; transcriptome; translation
17.  Analysis of variation at transcription factor binding sites in Drosophila and humans 
Genome Biology  2012;13(9):R49.
Advances in sequencing technology have boosted population genomics and made it possible to map the positions of transcription factor binding sites (TFBSs) with high precision. Here we investigate TFBS variability by combining transcription factor binding maps generated by ENCODE, modENCODE, our previously published data and other sources with genomic variation data for human individuals and Drosophila isogenic lines.
We introduce a metric of TFBS variability that takes into account changes in motif match associated with mutation and makes it possible to investigate TFBS functional constraints instance-by-instance as well as in sets that share common biological properties. We also take advantage of the emerging per-individual transcription factor binding data to show evidence that TFBS mutations, particularly at evolutionarily conserved sites, can be efficiently buffered to ensure coherent levels of transcription factor binding.
Our analyses provide insights into the relationship between individual and interspecies variation and show evidence for the functional buffering of TFBS mutations in both humans and flies. In a broad perspective, these results demonstrate the potential of combining functional genomics and population genetics approaches for understanding gene regulation.
PMCID: PMC3491393  PMID: 22950968
18.  D-Light on promoters: a client-server system for the analysis and visualization of cis-regulatory elements 
BMC Bioinformatics  2013;14:140.
The binding of transcription factors to DNA plays an essential role in the regulation of gene expression. Numerous experiments elucidated binding sequences which subsequently have been used to derive statistical models for predicting potential transcription factor binding sites (TFBS). The rapidly increasing number of genome sequence data requires sophisticated computational approaches to manage and query experimental and predicted TFBS data in the context of other epigenetic factors and across different organisms.
We have developed D-Light, a novel client-server software package to store and query large amounts of TFBS data for any number of genomes. Users can add small-scale data to the server database and query them in a large scale, genome-wide promoter context. The client is implemented in Java and provides simple graphical user interfaces and data visualization. Here we also performed a statistical analysis showing what a user can expect for certain parameter settings and we illustrate the usage of D-Light with the help of a microarray data set.
D-Light is an easy to use software tool to integrate, store and query annotation data for promoters. A public D-Light server, the client and server software for local installation and the source code under GNU GPL license are available at
PMCID: PMC3685601  PMID: 23617301
19.  The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools 
Nucleic Acids Research  2011;40(Database issue):D1202-D1210.
The Arabidopsis Information Resource (TAIR, is a genome database for Arabidopsis thaliana, an important reference organism for many fundamental aspects of biology as well as basic and applied plant biology research. TAIR serves as a central access point for Arabidopsis data, annotates gene function and expression patterns using controlled vocabulary terms, and maintains and updates the A. thaliana genome assembly and annotation. TAIR also provides researchers with an extensive set of visualization and analysis tools. Recent developments include several new genome releases (TAIR8, TAIR9 and TAIR10) in which the A. thaliana assembly was updated, pseudogenes and transposon genes were re-annotated, and new data from proteomics and next generation transcriptome sequencing were incorporated into gene models and splice variants. Other highlights include progress on functional annotation of the genome and the release of several new tools including Textpresso for Arabidopsis which provides the capability to carry out full text searches on a large body of research literature.
PMCID: PMC3245047  PMID: 22140109
20.  Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression 
BMC Genomics  2004;5:16.
Gene expression is regulated mainly by transcription factors (TFs) that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS) using position weight matrices (PWMs) that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions.
We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI) against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster), we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI.
Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1) those that show TFBS clustered in promoters associated with CGI, and (2) those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in regulatory regions.
PMCID: PMC375527  PMID: 15053842
promoter; tissue-specific gene expression; position weight matrix; regulatory motif
21.  Prediction of synergistic transcription factors by function conservation 
Genome Biology  2007;8(12):R257.
A new strategy is proposed for identifying synergistic transcription factors by function conservation, leading to the identification of 51 homotypic transcription-factor combinations.
Previous methods employed for the identification of synergistic transcription factors (TFs) are based on either TF enrichment from co-regulated genes or phylogenetic footprinting. Despite the success of these methods, both have limitations.
We propose a new strategy to identify synergistic TFs by function conservation. Rather than aligning the regulatory sequences from orthologous genes and then identifying conserved TF binding sites (TFBSs) in the alignment, we developed computational approaches to implement the novel strategy. These methods include combinatorial TFBS enrichment utilizing distance constraints followed by enrichment of overlapping orthologous genes from human and mouse, whose regulatory sequences contain the enriched TFBS combinations. Subsequently, integration of function conservation from both TFBS and overlapping orthologous genes was achieved by correlation analyses. These techniques have been used for genome-wide promoter analyses, which have led to the identification of 51 homotypic TF combinations; the validity of these approaches has been exemplified by both known TF-TF interactions and function coherence analyses. We further provide computational evidence that our novel methods were able to identify synergistic TFs to a much greater extent than phylogenetic footprinting.
Function conservation based on the concordance of combinatorial TFBS enrichment along with enrichment of overlapping orthologous genes has been proven to be a successful means for the identification of synergistic TFs. This approach avoids the limitations of phylogenetic footprinting as it does not depend upon sequence alignment. It utilizes existing gene annotation data, such as those available in GO, thus providing an alternative method for functional TF discovery and annotation.
PMCID: PMC2246259  PMID: 18053230
22.  Global transcriptional profiling of the toxic dinoflagellate Alexandrium fundyense using Massively Parallel Signature Sequencing 
BMC Genomics  2006;7:88.
Dinoflagellates are one of the most important classes of marine and freshwater algae, notable both for their functional diversity and ecological significance. They occur naturally as free-living cells, as endosymbionts of marine invertebrates and are well known for their involvement in "red tides". Dinoflagellates are also notable for their unusual genome content and structure, which suggests that the organization and regulation of dinoflagellate genes may be very different from that of most eukaryotes. To investigate the content and regulation of the dinoflagellate genome, we performed a global analysis of the transcriptome of the toxic dinoflagellate Alexandrium fundyense under nitrate- and phosphate-limited conditions using Massively Parallel Signature Sequencing (MPSS).
Data from the two MPSS libraries showed that the number of unique signatures found in A. fundyense cells is similar to that of humans and Arabidopsis thaliana, two eukaryotes that have been extensively analyzed using this method. The general distribution, abundance and expression patterns of the A. fundyense signatures were also quite similar to other eukaryotes, and at least 10% of the A. fundyense signatures were differentially expressed between the two conditions. RACE amplification and sequencing of a subset of signatures showed that multiple signatures arose from sequence variants of a single gene. Single signatures also mapped to different sequence variants of the same gene.
The MPSS data presented here provide a quantitative view of the transcriptome and its regulation in these unusual single-celled eukaryotes. The observed signature abundance and distribution in Alexandrium is similar to that of other eukaryotes that have been analyzed using MPSS. Results of signature mapping via RACE indicate that many signatures result from sequence variants of individual genes. These data add to the growing body of evidence for widespread gene duplication in dinoflagellates, which would contribute to the transcriptional complexity of these organisms. The MPSS data also demonstrate that a significant number of dinoflagellate mRNAs are transcriptionally regulated, indicating that dinoflagellates commonly employ transcriptional gene regulation along with the post-transcriptional regulation that has been well documented in these organisms.
PMCID: PMC1473201  PMID: 16638123
23.  Relationship between gene co-expression and sharing of transcription factor binding sites in Drosophila melanogaster 
Bioinformatics  2009;25(19):2473-2477.
Motivation: In functional genomics, it is frequently useful to correlate expression levels of genes to identify transcription factor binding sites (TFBS) via the presence of common sequence motifs. The underlying assumption is that co-expressed genes are more likely to contain shared TFBS and, thus, TFBS can be identified computationally. Indeed, gene pairs with a very high expression correlation show a significant excess of shared binding sites in yeast. We have tested this assumption in a more complex organism, Drosophila melanogaster, by using experimentally determined TFBS and microarray expression data. We have also examined the reverse relationship between the expression correlation and the extent of TFBS sharing.
Results: Pairs of genes with shared TFBS show, on average, a higher degree of co-expression than those with no common TFBS in Drosophila. However, the reverse does not hold true: gene pairs with high expression correlations do not share significantly larger numbers of TFBS. Exception to this observation exists when comparing expression of genes from the earliest stages of embryonic development. Interestingly, semantic similarity between gene annotations (Biological Process) is much better associated with TFBS sharing, as compared to the expression correlation. We discuss these results in light of reverse engineering approaches to computationally predict regulatory sequences by using comparative genomics.
PMCID: PMC2752616  PMID: 19633094
24.  CTF: a CRF-based transcription factor binding sites finding system 
BMC Genomics  2012;13(Suppl 8):S18.
Identifying the location of transcription factor bindings is crucial to understand transcriptional regulation. Currently, Chromatin Immunoprecipitation followed with high-throughput Sequencing (ChIP-seq) is able to locate the transcription factor binding sites (TFBSs) accurately in high throughput and it has become the gold-standard method for TFBS finding experimentally. However, due to its high cost, it is impractical to apply the method in a very large scale. Considering the large number of transcription factors, numerous cell types and various conditions, computational methods are still very valuable to accurate TFBS identification.
In this paper, we proposed a novel integrated TFBS prediction system, CTF, based on Conditional Random Fields (CRFs). Integrating information from different sources, CTF was able to capture patterns of TFBSs contained in different features (sequence, chromatin and etc) and predicted the TFBS locations with a high accuracy. We compared CTF with several existing tools as well as the PWM baseline method on a dataset generated by ChIP-seq experiments (TFBSs of 13 transcription factors in mouse genome). Results showed that CTF performed significantly better than existing methods tested.
CTF is a powerful tool to predict TFBSs by integrating high throughput data and different features. It can be a useful complement to ChIP-seq and other experimental methods for TFBS identification and thus improve our ability to investigate functional elements in post-genomic era.
Availability: CTF is freely available to academic users at:
PMCID: PMC3535700  PMID: 23282203
25.  The Next Generation of Transcription Factor Binding Site Prediction 
PLoS Computational Biology  2013;9(9):e1003214.
Finding where transcription factors (TFs) bind to the DNA is of key importance to decipher gene regulation at a transcriptional level. Classically, computational prediction of TF binding sites (TFBSs) is based on basic position weight matrices (PWMs) which quantitatively score binding motifs based on the observed nucleotide patterns in a set of TFBSs for the corresponding TF. Such models make the strong assumption that each nucleotide participates independently in the corresponding DNA-protein interaction and do not account for flexible length motifs. We introduce transcription factor flexible models (TFFMs) to represent TF binding properties. Based on hidden Markov models, TFFMs are flexible, and can model both position interdependence within TFBSs and variable length motifs within a single dedicated framework. The availability of thousands of experimentally validated DNA-TF interaction sequences from ChIP-seq allows for the generation of models that perform as well as PWMs for stereotypical TFs and can improve performance for TFs with flexible binding characteristics. We present a new graphical representation of the motifs that convey properties of position interdependence. TFFMs have been assessed on ChIP-seq data sets coming from the ENCODE project, revealing that they can perform better than both PWMs and the dinucleotide weight matrix extension in discriminating ChIP-seq from background sequences. Under the assumption that ChIP-seq signal values are correlated with the affinity of the TF-DNA binding, we find that TFFM scores correlate with ChIP-seq peak signals. Moreover, using available TF-DNA affinity measurements for the Max TF, we demonstrate that TFFMs constructed from ChIP-seq data correlate with published experimentally measured DNA-binding affinities. Finally, TFFMs allow for the straightforward computation of an integrated TF occupancy score across a sequence. These results demonstrate the capacity of TFFMs to accurately model DNA-protein interactions, while providing a single unified framework suitable for the next generation of TFBS prediction.
Author Summary
Transcription factors are critical proteins for sequence-specific control of transcriptional regulation. Finding where these proteins bind to DNA is of key importance for global efforts to decipher the complex mechanisms of gene regulation. Greater understanding of the regulation of transcription promises to improve human genetic analysis by specifying critical gene components that have eluded investigators. Classically, computational prediction of transcription factor binding sites (TFBS) is based on models giving weights to each nucleotide at each position. We introduce a novel statistical model for the prediction of TFBS tolerant of a broader range of TFBS configurations than can be conveniently accommodated by existing methods. The new models are designed to address the confounding properties of nucleotide composition, inter-positional sequence dependence and variable lengths (e.g. variable spacing between half-sites) observed in the more comprehensive experimental data now emerging. The new models generate scores consistent with DNA-protein affinities measured experimentally and can be represented graphically, retaining desirable attributes of past methods. It demonstrates the capacity of the new approach to accurately assess DNA-protein interactions. With the rich experimental data generated from chromatin immunoprecipitation experiments, a greater diversity of TFBS properties has emerged that can now be accommodated within a single predictive approach.
PMCID: PMC3764009  PMID: 24039567

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