SITECON: a tool for detecting conservative conformational and physicochemical properties in transcription factor binding site alignments and for site recognition

The misregulation of mitochondria-associated genes caused by GAGA-factor lack promotes autophagic germ cell death in Drosophila testes

The Drosophila GAGA-factor encoded by the Trithorax-like (Trl) gene is DNA-binding protein with unusually wide range of applications in diverse cell contexts. In Drosophila spermatogenesis, reduced GAGA expression caused by Trl mutations induces mass autophagy leading to germ cell death. In this work, we investigated the contribution of mitochondrial abnormalities to autophagic germ cell death in Trl gene mutants. Using a cytological approach, in combination with an analysis of high-throughput RNA sequencing (RNA-seq) data, we demonstrated that the GAGA deficiency led to considerable defects in mitochondrial ultrastructure, by causing misregulation of GAGA target genes encoding essential components of mitochondrial molecular machinery. Mitochondrial anomalies induced excessive production of reactive oxygen species and their release into the cytoplasm, thereby provoking oxidative stress. Changes in transcription levels of some GAGA-independent genes in the Trl mutants indicated that testis cells experience ATP deficiency and metabolic aberrations, that may trigger extensive autophagy progressing to cell death.

Protein-DNA recognition mechanisms and specificity

The accumulated knowledge about the structure of protein-DNA complexes allowed us to understand the mechanisms of protein-DNA recognition and searching for a specific site on DNA. Obviously, the mechanism of specific DNA recognition by a protein must satisfy two requirements. First, the probability of incorrect binding should be very small. Second, the time to find the "correct" binding site should not be too long. If we assume that protein recognition of a precise site on DNA occurs at some distance from DNA and calculate global minima, we can avoid local minima at short distances. The only long-range interaction is the interaction of charges. The location of charges on DNA in three-dimensional space depends on the local conformation of DNA and thus reflects the DNA sequence and sets the spatial pattern for recognition. Various factors such as counter ion concentration, ionic strength, and pH can affect protein recognition of DNA. Nowadays, the theory of long-range interactions makes it possible to calculate the best mutual spatial arrangement of protein and DNA molecules by charged groups and avoid misplaced binding.

Regulation of adhesin synthesis in Aggregatibacter actinomycetemcomitans

Aggregatibacter actinomycetemcomitans is a gram-negative bacterium associated with periodontal disease and a variety of disseminated extra-oral infections. Tissue colonization is mediated by fimbriae and non-fimbriae adhesins resulting in the formation of a sessile bacterial community or biofilm, which confers enhanced resistance to antibiotics and mechanical removal. The environmental changes experienced by A. actinomycetemcomitans during infection are detected and processed by undefined signaling pathways that alter gene expression. In this study, we have characterized the promoter region of the extracellular matrix protein adhesin A (EmaA), which is an important surface adhesin in biofilm biogenesis and disease initiation using a series of deletion constructs consisting of the emaA intergenic region and a promotor-less lacZ sequence. Two regions of the promoter sequence were found to regulate gene transcription and in silico analysis indicated the presence of multiple transcriptional regulatory binding sequences. Analysis of four regulatory elements, CpxR, ArcA, OxyR, and DeoR, was undertaken in this study. Inactivation of arcA, the regulator moiety of the ArcAB two-component signaling pathway involved in redox homeostasis, resulted in a decrease in EmaA synthesis and biofilm formation. Analysis of the promoter sequences of other adhesins identified binding sequences for the same regulatory proteins, which suggests that these proteins are involved in the coordinate regulation of adhesins required for colonization and pathogenesis.

The complex role of transcription factor GAGA in germline death during Drosophila spermatogenesis: transcriptomic and bioinformatic analyses

The GAGA protein (also known as GAF) is a transcription factor encoded by the Trl gene in D. melanogaster. GAGA is involved in the regulation of transcription of many genes at all stages of fly development and life. Recently, we investigated the participation of GAGA in spermatogenesis and discovered that Trl mutants experience massive degradation of germline cells in the testes. Trl underexpression induces autophagic death of spermatocytes, thereby leading to reduced testis size. Here, we aimed to determine the role of the transcription factor GAGA in the regulation of ectopic germline cell death. We investigated how Trl underexpression affects gene expression in the testes. We identified 15,993 genes in three biological replicates of our RNA-seq analysis and compared transcript levels between hypomorphic Trl ^R85/Trl ³⁶² and Oregon testes. A total of 2,437 differentially expressed genes were found, including 1,686 upregulated and 751 downregulated genes. At the transcriptional level, we detected the development of cellular stress in the Trl-mutant testes: downregulation of the genes normally expressed in the testes (indicating slowed or abrogated spermatocyte differentiation) and increased expression of metabolic and proteolysis-related genes, including stress response long noncoding RNAs. Nonetheless, in the Flybase Gene Ontology lists of genes related to cell death, autophagy, or stress, there was no enrichment with GAGA-binding sites. Furthermore, we did not identify any specific GAGA-dependent cell death pathway that could regulate spermatocyte death. Thus, our data suggest that GAGA deficiency in male germline cells leads to an imbalance of metabolic processes, impaired mitochondrial function, and cell death due to cellular stress.

Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif

Spatial and temporal expression of genes is essential for maintaining phenotype integrity. Transcription factors (TFs) modulate expression patterns by binding to specific DNA sequences in the genome. Along with the core binding motif, the flanking sequence context can play a role in DNA-TF recognition. Here, we employ high-throughput in vitro and in silico analyses to understand the influence of sequences flanking the cognate sites in binding of three most prevalent eukaryotic TF families (zinc finger, homeodomain and bZIP). In vitro binding preferences of each TF toward the entire DNA sequence space were correlated with a wide range of DNA structural parameters, including DNA flexibility. Results demonstrate that conformational plasticity of flanking regions modulates binding affinity of certain TF families. DNA duplex stability and minor groove width also play an important role in DNA-TF recognition but differ in how exactly they influence the binding in each specific case. Our analyses further reveal that the structural features of preferred flanking sequences are not universal, as similar DNA-binding folds can employ distinct DNA recognition modes.

Hidden heterogeneity of transcription factor binding sites: A case study of SF-1

Steroidogenic factor 1 (SF-1) belongs to a small group of the transcription factors that bind DNA only as a monomer. Three different approaches-Sitecon, SiteGA, and oPWM-constructed using the same training sample of experimentally confirmed SF-1 binding sites have been used to recognize these sites. The appropriate prediction thresholds for recognition models have been selected. Namely, the thresholds concordant by false positive or negative rates for various methods were used to optimize the discrimination of steroidogenic gene promoters from the datasets of non-specific promoters. After experimental verification, the models were used to analyze the ChIP-seq data for SF-1. It has been shown that the sets of sites recognized by different models overlap only partially and that an integration of these models allows for identification of SF-1 sites in up to 80% of the ChIP-seq loci. The structures of the sites detected using the three recognition models in the ChIP-seq peaks falling within the [-5000, +5000] region relative to the transcription start sites (TSS) extracted from the FANTOM5 project have been analyzed. The MATLIGN classified the frequency matrices for the sites predicted by oPWM, Sitecon, and SiteGA into two groups. The first group is described by oPWM/Sitecon and the second, by SiteGA. Gene ontology (GO) analysis has been used to clarify the differences between the sets of genes carrying different variants of SF-1 binding sites. Although this analysis in general revealed a considerable overlap in GO terms for the genes carrying the binding sites predicted by oPWM, Sitecon, or SiteGA, only the last method elicited notable trend to terms related to negative regulation and apoptosis. The results suggest that the SF-1 binding sites are different in both their structure and the functional annotation of the set of target genes correspond to the predictions by oPWM+Sitecon and SiteGA. Further application of Homer software for de novo identification of enriched motifs in ChIP-Seq data for SF-1ChIP-seq dataset gave the data similar to oPWM+Sitecon.

Sequence-based prediction of transcription upregulation by auxin in plants

Auxin is one of the main regulators of growth and development in plants. Prediction of auxin response based on gene sequence is of high importance. We found the TGTCNC consensus of 111 known natural and artificially mutated auxin response elements (AuxREs) with measured auxin-caused relative increase in genes' transcription levels, so-called either "a response to auxin" or "an auxin response." This consensus was identical to the most cited AuxRE motif. Also, we found several DNA sequence features that correlate with auxin-caused increase in genes' transcription levels, namely: number of matches with TGTCNC, homology score based on nucleotide frequencies at the consensus positions, abundances of five trinucleotides and five B-helical DNA features around these known AuxREs. We combined these correlations using a four-step empirical model of auxin response based on a gene's sequence with four steps, namely: (1) search for AuxREs with no auxin; (2) stop at the found AuxRE; (3) repression of the basal transcription of the gene having this AuxRE; and (4) manifold increase of this gene's transcription in response to auxin. Independently measured increases in transcription levels in response to auxin for 70 Arabidopsis genes were found to significantly correlate with predictions of this equation (r = 0.44, p < 0.001) as well as with TATA-binding protein (TBP)'s affinity to promoters of these genes and with nucleosome packing of these promoters (both, p < 0.025). Finally, we improved our equation for prediction of a gene's transcription increase in response to auxin by taking into account TBP-binding and nucleosome packing (r = 0.53, p < 10(-6)). Fisher's F-test validated the significant impact of both TBP/promoter-affinity and promoter nucleosome on auxin response in addition to those of AuxRE, F = 4.07, p < 0.025. It means that both TATA-box and nucleosome should be taken into account to recognize transcription factor binding sites upon DNA sequences: in the case of the TATA-less nucleosome-rich promoters, recognition scores must be higher than in the case of the TATA-containing nucleosome-free promoters at the same transcription activity.

Evolutionary optimization of transcription factor binding motif detection

All the cell types are under strict control of how their genes are transcribed into expressed transcripts by the temporally dynamic orchestration of the transcription factor binding activities. Given a set of known binding sites (BSs) of a given transcription factor (TF), computational TFBS screening technique represents a cost efficient and large scale strategy to complement the experimental ones. There are two major classes of computational TFBS prediction algorithms based on the tertiary and primary structures, respectively. A tertiary structure based algorithm tries to calculate the binding affinity between a query DNA fragment and the tertiary structure of the given TF. Due to the limited number of available TF tertiary structures, primary structure based TFBS prediction algorithm is a necessary complementary technique for large scale TFBS screening. This study proposes a novel evolutionary algorithm to randomly mutate the weights of different positions in the binding motif of a TF, so that the overall TFBS prediction accuracy is optimized. The comparison with the most widely used algorithm, Position Weight Matrix (PWM), suggests that our algorithm performs better or the same level in all the performance measurements, including sensitivity, specificity, accuracy and Matthews correlation coefficient. Our data also suggests that it is necessary to remove the widely used assumption of independence between motif positions. The supplementary material may be found at: http://www.healthinformaticslab.org/supp/ .

Genomic and comparative genomic analyses of Rickettsia heilongjiangensis provide insight into its evolution and pathogenesis

Rickettsia heilongjiangensis, the causative agent of far eastern spotted fever, is an obligate intracellular gram-negative bacterium that belongs to the spotted fever group rickettsiae. To understand the evolution and pathogenesis of R. heilongjiangensis, we analyzed its genome and compared it with other rickettsial genomes available in GenBank. The R. heilongjiangensis chromosome contains 1333 genes, including 1297 protein coding genes and 36 RNA coding genes. The genome also contains 121 pseudogenes, 54 insertion sequences, and 39 tandem repeats. Sixteen genes encoding the major components of the type IV secretion systems were identified in the R. heilongjiangensis genome. In total, 37 β-barrel outer membrane proteins were predicted in the genome, eight of which have been previously confirmed to be outer membrane proteins. In addition, 266 potential virulence factor genes, seven partially deleted antibiotic resistance genes, and a genomic island were identified in the genome. The codon usage in the genome is compatible with its low GC content, and the amino acid usage shows apparent bias. A comparative genomic analysis showed that R. heilongjiangensis and R. japonica share one unique fragment that may be a target sequence for a diagnostic assay. The orthologs of 37 genes of R. heilongjiangensis were found in pathogenic R. rickettsii str. Sheila Smith but not in non-pathogenic R. rickettsii str. Iowa, which may explain why R. heilongjiangensis is pathogenic. Pan-genome analysis showed that R. heilongjiangensis and 42 other rickettsiae strains share 693 core genes with a pan-genome size of 4837 genes. The pan-genome-based phylogeny showed that R. heilongjiangensis was closely related to R. japonica.

Identification of functionally significant elements in the second intron of the Drosophila melanogaster Trithorax-like gene

It is known that a lot of genes having a distinct expression pattern require the complex system of transcription regulation. The regulatory regions of such genes can include not only the 5'-flanking regions, but also other regions, particularly their intron sequences. The Drosophila melanogaster Trithorax-like (Trl) gene, encoding the GAGA protein, is one of the genes with complex expression pattern. GAGA is one of a few transcription factors that can regulate gene expression at multiple levels. The GAGA-mediated modulation of expression seems to be linked with modifications of the chromatin structure. Nowadays, the regulatory potential of the Trl 5'-flanking region that contains multiple GAGA binding sites has been analyzed, but the presence of the functionally significant elements in other Trl regions has not been examined. We found DNase I hypersensitive sites, evolutionary-conserved sequences and numerous GAGA binding sites in the second intron of the Trl gene. Interestingly, these sequences localize in two main regions of the intron in immediate proximity to preferred regions of transposon insertions. Additionally, we revealed that deletion of the intron fragment in the Trl(1-72) mutants caused an alteration of the Trl expression pattern. These results allow us to conclude that the second intron of the Trl gene contains functionally significant elements.

From binding motifs in ChIP-Seq data to improved models of transcription factor binding sites

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) became a method of choice to locate DNA segments bound by different regulatory proteins. ChIP-Seq produces extremely valuable information to study transcriptional regulation. The wet-lab workflow is often supported by downstream computational analysis including construction of models of nucleotide sequences of transcription factor binding sites in DNA, which can be used to detect binding sites in ChIP-Seq data at a single base pair resolution. The most popular TFBS model is represented by positional weight matrix (PWM) with statistically independent positional weights of nucleotides in different columns; such PWMs are constructed from a gapless multiple local alignment of sequences containing experimentally identified TFBSs. Modern high-throughput techniques, including ChIP-Seq, provide enough data for careful training of advanced models containing more parameters than PWM. Yet, many suggested multiparametric models often provide only incremental improvement of TFBS recognition quality comparing to traditional PWMs trained on ChIP-Seq data. We present a novel computational tool, diChIPMunk, that constructs TFBS models as optimal dinucleotide PWMs, thus accounting for correlations between nucleotides neighboring in input sequences. diChIPMunk utilizes many advantages of ChIPMunk, its ancestor algorithm, accounting for ChIP-Seq base coverage profiles ("peak shape") and using the effective subsampling-based core procedure which allows processing of large datasets. We demonstrate that diPWMs constructed by diChIPMunk outperform traditional PWMs constructed by ChIPMunk from the same ChIP-Seq data. Software website: http://autosome.ru/dichipmunk/

DNA structural properties in the classification of genomic transcription regulation elements

It has been long known that DNA molecules encode information at various levels. The most basic level comprises the base sequence itself and is primarily important for the encoding of proteins and direct base recognition by DNA-binding proteins. A more elusive level consists of the local structural properties of the DNA molecule wherein the DNA sequence only plays an indirect supportive role. These properties are nevertheless an important factor in a large number of biomolecular processes and can be considered as informative signals for the presence of a variety of genomic features. Several recent studies have unequivocally shown the benefit of relying on such DNA properties for modeling and predicting genomic features as diverse as transcription start sites, transcription factor binding sites, or nucleosome occupancy. This review is meant to provide an overview of the key aspects of these DNA conformational and physicochemical properties. To illustrate their potential added value compared to relying solely on the nucleotide sequence in genomics studies, we discuss their application in research on transcription regulation mechanisms as representative cases.

Analysis and recognition of the GAGA transcription factor binding sites in Drosophila genes

The transcription factor GAGA, encoded by the gene Trl, controls expression of many Drosophila melanogaster genes. We have compiled the presently largest sample (120 sites) of published nucleotide sequences with experimentally confirmed binding to GAGA protein. Analysis of the sample has demonstrated that despite an apparent structural diversity of the GAGA sites, they fall into four distinct groups, namely, (1) the sites containing two GAG trinucleotides with no more than one nucleotide substitution in each and separated by spacers with a length of 1 or 3 nucleotides (GAGnGAG and GAGnnnGAG); (2) the sites containing a single GAGAG motif; (3) (GA)(3-9) microsatellite repeats; and (4) the sites corresponding to three and more direct repeats of GAG trinucleotide homolog and its inverted repeats separated by spacers of various lengths. Using the software package SITECON, the methods were elaborated for recognizing the sites of GAGnGAG (method 1) and GAGnnnGAG (method 2) types in DNA sequences. Experimental verification confirmed the ability to interact with the GAGA factor for 72% of the sites predicted using method 1 and 94.5% of the sites predicted by method 2. Application of the experimentally verified methods to analyzing the localization of potential GAGA binding sites in the target genes of this transcription factor has demonstrated that the 5'-untranslated regions (5'UTRs) and first introns are enriched for these sites (two-threefold relative to the average occurrence frequency in the D. melanogaster genome) as compared with a moderate enrichment (not exceeding 1.5-fold) of promoter regions (-4000/+200 bp or -1000/+100 bp).

In silico prediction of transcriptional factor-binding sites

The recognition of transcription factor binding sites (TFBSs) is the first step on the way to deciphering the DNA regulatory code. A large variety of computational approaches and corresponding in silico tools for TFBS recognition are available, each having their own advantages and shortcomings. This chapter provides a brief tutorial to assist end users in the application of these tools for functional characterization of genes.

Molecular characterization of vernalization loci VRN1 in wild and cultivated wheats

BACKGROUND

Variability of the VRN1 promoter region of the unique collection of spring polyploid and wild diploid wheat species together with diploid goatgrasses (donor of B and D genomes of polyploid wheats) were investigated. Accessions of wild diploid (T. boeoticum, T. urartu) and tetraploid (T. araraticum, T. timopheevii) species were studied for the first time.

RESULTS

Sequence analysis indicated great variability in the region from -62 to -221 nucleotide positions of the VRN1 promoter region. Different indels were found within this region in spring wheats. It was shown that VRN1 promoter region of B and G genome can also contain damages such as the insertion of the transposable element.Some transcription factor recognition sites including hybrid C/G-box for TaFDL2 protein known as the VRN1 gene upregulator were predicted inside the variable region. It was shown that deletions leading to promoter damage occurred in diploid and polyploid species independently. DNA transposon insertions first occurred in polyploid species. At the same time, the duplication of the promoter region was observed in A genomes of polyploid species.

CONCLUSIONS

We can conclude that supposed molecular mechanism of the VRN1 gene activating in cultivated diploid wheat species T. monococcum is common also for wild T. boeoticum and was inherited by T. monococcum. The spring polyploids are not related in their origin to spring diploids. The spring T. urartu and goatgrass accessions have another mechanism of flowering activation that is not connected with indels in VRN1 promoter region. All obtained data may be useful for detailed insight into origin of spring wheat forms in evolution and domestication process.

Promoters of the genes encoding the transcription factors regulating the cytokine gene expression in macrophages contain putative binding sites for aryl hydrocarbon receptor

The computer system SITECON was used to study the regulatory regions in the transcription factor genes expressed in the activated macrophage and the genes of the proteins mediating the macrophage involvement in the immune response. Dioxin responsive elements (DREs), the specific sites responsible for expression regulation of the genes involved in the cell response to dioxin, were found in these gene regions. Thus, the role of dioxin in activity regulation of the genes involved in development of the immune response can be regulated both directly, by the transcription complex containing dioxin as a ligand, and indirectly, via intrinsic transcription factors.The double regulation, via DRE and the binding sites for the corresponding transcription factors in the promoter regions of macrophage genes, and the interregulation of the genes providing for the immune response allow the system to rapidly respond to a provocative agent (xenobiotic) and finely tune its function.