DNA free energy-based promoter prediction and comparative analysis of Arabidopsis and rice genomes

Identification of oil palm cis-regulatory elements based on DNA free energy and single nucleotide polymorphism density

Transcription control through cis-regulatory elements (CREs) is one of important regulators of gene expression. This study aimed to identify the location of CREs in oil palm (Elaeis guineensis Jacq.) using the combination of DNA free energy and single nucleotide polymorphism (SNP) density approaches. Promoter region sequences were extracted oil palm genome spanning from 1500 nucleotides (nt) upstream to 1000 nt downstream of every annotated transcription start sites (TSS). Free energy profiles of each promoter region were calculated using PromPredict software. Raw reads from the deep sequencing of 59 oil palm origins were used to calculate SNP density of each promoter region. The result showed that the average free energy (AFE) on the upstream region of TSS is about 1.5 kcal/mol higher compared to the downstream region. Using DNA free energy method, 16,281 regions of CREs were predicted. Most of predicted CREs was located between 1 and 500 nt upstream of TSS. Anti-correlation pattern between free energy and SNP density was observed on the predicted regions of CREs. This anti-correlated pattern was also observed on an experimentally determined promoter of the oil palm metallothionein gene, EgMSP1. Considering the increasing use of promoter information on plant biotechnology, an easy and accurate promoter prediction using the combination of free energy and SNP density method could be recommended.

Transcriptome-based Mining of the Constitutive Promoters for Tuning Gene Expression in Aspergillus oryzae

Transcriptional regulation has been adopted for developing metabolic engineering tools. The regulatory promoter is a crucial genetic element for strain optimization. In this study, a gene set of Aspergillus oryzae with highly constitutive expression across different growth stages was identified through transcriptome data analysis. The candidate promoters were functionally characterized in A. oryzae by transcriptional control of β-glucuronidase (GUS) as a reporter. The results showed that the glyceraldehyde triphosphate dehydrogenase promoter (PgpdA1) of A. oryzae with a unique structure displayed the most robust strength in constitutively controlling the expression compared to the PgpdA2 and other putative promoters tested. In addition, the ubiquitin promoter (Pubi) of A. oryzae exhibited a moderate expression strength. The deletion analysis revealed that the 5' untranslated regions of gpdA1 and ubi with the length of 1028 and 811 nucleotides, counted from the putative translation start site (ATG), respectively, could efficiently drive the GUS expression. Interestingly, both promoters could function on various carbon sources for cell growth. Glucose was the best fermentable carbon source for allocating high constitutive expressions during cell growth, and the high concentrations (6-8% glucose, w/v) did not repress their functions. It was also demonstrated that the secondary metabolite gene coding for indigoidine could express under the control of PgpdA1 or Pubi promoter. These strong and moderate promoters of A. oryzae provided beneficial options in tuning the transcriptional expression for leveraging the metabolic control towards the targeted products.

Biological and Molecular Components for Genetically Engineering Biosensors in Plants

Plants adapt to their changing environments by sensing and responding to physical, biological, and chemical stimuli. Due to their sessile lifestyles, plants experience a vast array of external stimuli and selectively perceive and respond to specific signals. By repurposing the logic circuitry and biological and molecular components used by plants in nature, genetically encoded plant-based biosensors (GEPBs) have been developed by directing signal recognition mechanisms into carefully assembled outcomes that are easily detected. GEPBs allow for in vivo monitoring of biological processes in plants to facilitate basic studies of plant growth and development. GEPBs are also useful for environmental monitoring, plant abiotic and biotic stress management, and accelerating design-build-test-learn cycles of plant bioengineering. With the advent of synthetic biology, biological and molecular components derived from alternate natural organisms (e.g., microbes) and/or de novo parts have been used to build GEPBs. In this review, we summarize the framework for engineering different types of GEPBs. We then highlight representative validated biological components for building plant-based biosensors, along with various applications of plant-based biosensors in basic and applied plant science research. Finally, we discuss challenges and strategies for the identification and design of biological components for plant-based biosensors.

Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction

Promoters are crucial regulatory DNA regions for gene transcriptional activation. Rapid advances in next-generation sequencing technologies have accelerated the accumulation of genome sequences, providing increased training data to inform computational approaches for both prokaryotic and eukaryotic promoter prediction. However, it remains a significant challenge to accurately identify species-specific promoter sequences using computational approaches. To advance computational support for promoter prediction, in this study, we curated 58 comprehensive, up-to-date, benchmark datasets for 7 different species (i.e. Escherichia coli, Bacillus subtilis, Homo sapiens, Mus musculus, Arabidopsis thaliana, Zea mays and Drosophila melanogaster) to assist the research community to assess the relative functionality of alternative approaches and support future research on both prokaryotic and eukaryotic promoters. We revisited 106 predictors published since 2000 for promoter identification (40 for prokaryotic promoter, 61 for eukaryotic promoter, and 5 for both). We systematically evaluated their training datasets, computational methodologies, calculated features, performance and software usability. On the basis of these benchmark datasets, we benchmarked 19 predictors with functioning webservers/local tools and assessed their prediction performance. We found that deep learning and traditional machine learning-based approaches generally outperformed scoring function-based approaches. Taken together, the curated benchmark dataset repository and the benchmarking analysis in this study serve to inform the design and implementation of computational approaches for promoter prediction and facilitate more rigorous comparison of new techniques in the future.

TSSFinder-fast and accurate ab initio prediction of the core promoter in eukaryotic genomes

Promoter annotation is an important task in the analysis of a genome. One of the main challenges for this task is locating the border between the promoter region and the transcribing region of the gene, the transcription start site (TSS). The TSS is the reference point to delimit the DNA sequence responsible for the assembly of the transcribing complex. As the same gene can have more than one TSS, so to delimit the promoter region, it is important to locate the closest TSS to the site of the beginning of the translation. This paper presents TSSFinder, a new software for the prediction of the TSS signal of eukaryotic genes that is significantly more accurate than other available software. We currently are the only application to offer pre-trained models for six different eukaryotic organisms: Arabidopsis thaliana, Drosophila melanogaster, Gallus gallus, Homo sapiens, Oryza sativa and Saccharomyces cerevisiae. Additionally, our software can be easily customized for specific organisms using only 125 DNA sequences with a validated TSS signal and corresponding genomic locations as a training set. TSSFinder is a valuable new tool for the annotation of genomes. TSSFinder source code and docker container can be downloaded from http://tssfinder.github.io. Alternatively, TSSFinder is also available as a web service at http://sucest-fun.org/wsapp/tssfinder/.

Delving into Eukaryotic Origins of Replication Using DNA Structural Features

DNA replication in eukaryotes is an intricate process, which is precisely synchronized by a set of regulatory proteins, and the replication fork emanates from discrete sites on chromatin called origins of replication (Oris). These spots are considered as the gateway to chromosomal replication and are stereotyped by sequence motifs. The cognate sequences are noticeable in a small group of entire origin regions or totally absent across different metazoans. Alternatively, the use of DNA secondary structural features can provide additional information compared to the primary sequence. In this article, we report the trends in DNA sequence-based structural properties of origin sequences in nine eukaryotic systems representing different families of life. Biologically relevant DNA secondary structural properties, namely, stability, propeller twist, flexibility, and minor groove shape were studied in the sequences flanking replication start sites. Results indicate that Oris in yeasts show lower stability, more rigidity, and narrow minor groove preferences compared to genomic sequences surrounding them. Yeast Oris also show preference for A-tracts and the promoter element TATA box in the vicinity of replication start sites. On the contrary, Drosophila melanogaster, humans, and Arabidopsis thaliana do not have such features in their Oris, and instead, they show high preponderance of G-rich sequence motifs such as putative G-quadruplexes or i-motifs and CpG islands. Our extensive study applies the DNA structural feature computation to delve into origins of replication across organisms ranging from yeasts to mammals and including a plant. Insights from this study would be significant in understanding origin architecture and help in designing new algorithms for predicting DNA trans-acting factor recognition events.

Identification of Regulatory SNPs Associated with Vicine and Convicine Content of Vicia faba Based on Genotyping by Sequencing Data Using Deep Learning

Faba bean (Vicia faba) is a grain legume, which is globally grown for both human consumption as well as feed for livestock. Despite its agro-ecological importance the usage of Vicia faba is severely hampered by its anti-nutritive seed-compounds vicine and convicine (V+C). The genes responsible for a low V+C content have not yet been identified. In this study, we aim to computationally identify regulatory SNPs (rSNPs), i.e., SNPs in promoter regions of genes that are deemed to govern the V+C content of Vicia faba. For this purpose we first trained a deep learning model with the gene annotations of seven related species of the Leguminosae family. Applying our model, we predicted putative promoters in a partial genome of Vicia faba that we assembled from genotyping-by-sequencing (GBS) data. Exploiting the synteny between Medicago truncatula and Vicia faba, we identified two rSNPs which are statistically significantly associated with V+C content. In particular, the allele substitutions regarding these rSNPs result in dramatic changes of the binding sites of the transcription factors (TFs) MYB4, MYB61, and SQUA. The knowledge about TFs and their rSNPs may enhance our understanding of the regulatory programs controlling V+C content of Vicia faba and could provide new hypotheses for future breeding programs.

Natural Sequence Variations and Combinations of GNP1 and NAL1 Determine the Grain Number per Panicle in Rice

BACKGROUND

The grain number per panicle (GNP), which is one of three grain yield components, is an important trait for the genetic improvement of rice. Although the NAL1 and GNP1 genes regulating the rice GNP and grain yield have been cloned, their allelic diversity, functional differences in rice germplasms, and effects of their combination on GNP and grain yield remain unclear.

RESULTS

Based on DNA sequences of these two genes in 198 cultivated rice (Oryza sativa) and 8-10 wild rice (Oryza rufipogon) germplasms, 16 and 14 haplotypes were identified for NAL1 and GNP1, respectively. The NAL1 gene had the strongest effects on GNP in indica (xian) and japonica (geng) subpopulations. In contrast, GNP1 had no significant effects in the geng subpopulation and was rare in the xian background, in which the superior GNP1 allele (GNP1-6) was detected in only 4.0% of the 198 germplasms. Compared with the transgenic lines with GNP1 or NAL1, the transgenic lines with both genes had a higher GNP (15.5%-25.4% and 11.6%-15.9% higher, respectively) and grain yield (5.7%-9.0% and 8.3%-12.3% higher, respectively) across 3 years. The two genes combined in the introgression lines in Lemont background resulted in especially favorable effects on the GNP.

CONCLUSIONS

Our results indicated that the GNP1 and NAL1 exhibited obvious differentiation and their combinations can significantly increase the grain yield in geng rice cultivars. These observations provide insights into the molecular basis of the GNP and may be useful for rice breeding of high yield potential by pyramiding GNP1 and NAL1.

Machine learning approaches and their current application in plant molecular biology: A systematic review

Machine learning (ML) is a field of artificial intelligence that has rapidly emerged in molecular biology, thus allowing the exploitation of Big Data concepts in plant genomics. In this context, the main challenges are given in terms of how to analyze massive datasets and extract new knowledge in all levels of cellular systems research. In summary, ML techniques allow complex interactions to be inferred in several biological systems. Despite its potential, ML has been underused due to complex computational algorithms and definition terms. Therefore, a systematic review to disentangle ML approaches is relevant for plant scientists and has been considered in this study. We presented the main steps for ML development (from data selection to evaluation of classification/prediction models) with a respective discussion approaching functional genomics mainly in terms of pathogen effector genes in plant immunity. Additionally, we also considered how to access public source databases under an ML framework towards advancing plant molecular biology and introduced novel powerful tools, such as deep learning.

Variation of gene expression in plants is influenced by gene architecture and structural properties of promoters

In higher eukaryotes, gene architecture and structural properties of promoters have emerged as significant factors influencing variation in number of transcripts (expression level) and specificity of gene expression in a tissue (expression breadth), which eventually shape the phenotype. In this study, transcriptome data of different tissue types at various developmental stages of A. thaliana, O. sativa, S. bicolor and Z. mays have been used to understand the relationship between properties of gene components and its expression. Our findings indicate that in plants, among all gene architecture and structural properties of promoters, compactness of genes in terms of intron content is significantly linked to gene expression level and breadth, whereas in human an exactly opposite scenario is seen. In plants, for the first time we have carried out a quantitative estimation of effect of a particular trait on expression level and breadth, by using multiple regression analysis and it confirms that intron content of primary transcript (as %) is a powerful determinant of expression breadth. Similarly, further regression analysis revealed that among structural properties of the promoters, stability is negatively linked to expression breadth, while DNase1 sensitivity strongly governs gene expression breadth in monocots and gene expression level in dicots. In addition, promoter regions of tissue specific genes are found to be enriched with TATA box and Y-patch motifs. Finally, multi copy orthologous genes in plants are found to be longer, highly regulated and tissue specific.

ShapeGTB: the role of local DNA shape in prioritization of functional variants in human promoters with machine learning

Motivation

The identification of functional sequence variations in regulatory DNA regions is one of the major challenges of modern genetics. Here, we report results of a combined multifactor analysis of properties characterizing functional sequence variants located in promoter regions of genes.

Results

We demonstrate that GC-content of the local sequence fragments and local DNA shape features play significant role in prioritization of functional variants and outscore features related to histone modifications, transcription factors binding sites, or evolutionary conservation descriptors. Those observations allowed us to build specialized machine learning classifier identifying functional single nucleotide polymorphisms within promoter regions—ShapeGTB. We compared our method with more general tools predicting pathogenicity of all non-coding variants. ShapeGTB outperformed them by a wide margin (average precision 0.93 vs. 0.47–0.55). On the external validation set based on ClinVar database it displayed worse performance but was still competitive with other methods (average precision 0.47 vs. 0.23–0.42). Such results suggest unique characteristics of mutations located within promoter regions and are a promising signal for the development of more accurate variant prioritization tools in the future.

Bacterial promoter prediction: Selection of dynamic and static physical properties of DNA for reliable sequence classification

Predicting promoter activity of DNA fragment is an important task for computational biology. Approaches using physical properties of DNA to predict bacterial promoters have recently gained a lot of attention. To select an adequate set of physical properties for training a classifier, various characteristics of DNA molecule should be taken into consideration. Here, we present a systematic approach that allows us to select less correlated properties for classification by means of both correlation and cophenetic coefficients as well as concordance matrices. To prove this concept, we have developed the first classifier that uses not only sequence and static physical properties of DNA fragment, but also dynamic properties of DNA open states. Therefore, the best performing models with accuracy values up to 90% for all types of sequences were obtained. Furthermore, we have demonstrated that the classifier can serve as a reliable tool enabling promoter DNA fragments to be distinguished from promoter islands despite the similarity of their nucleotide sequences.

Identification of putative promoters in 48 eukaryotic genomes on the basis of DNA free energy

Transcription is an intricate mechanism and is orchestrated at the promoter region. The cognate motifs in the promoters are observed in only a subset of total genes across different domains of life. Hence, sequence-motif based promoter prediction may not be a holistic approach for whole genomes. Conversely, the DNA structural property, duplex stability is a characteristic of promoters and can be used to delineate them from other genomic sequences. In this study, we have used a DNA duplex stability based algorithm ‘PromPredict’ for promoter prediction in a broad range of eukaryotes, representing various species of yeast, worm, fly, fish, and mammal. Efficiency of the software has been tested in promoter regions of 48 eukaryotic systems. PromPredict achieves recall values, which range from 68 to 92% in various eukaryotes. PromPredict performs well in mammals, although their core promoter regions are GC rich. ‘PromPredict’ has also been tested for its ability to predict promoter regions for various transcript classes (coding and non-coding), TATA-containing and TATA-less promoters as well as on promoter sequences belonging to different gene expression variability categories. The results support the idea that differential DNA duplex stability is a potential predictor of promoter regions in various genomes.

In silico comparative analysis of promoters derived from plant pararetroviruses

Promoters are specific sequence of nucleotides present upstream of gene coding region involved in initiation and regulation of transcription. Multiple cis-acting element forms the architecture of promoter to which trans-acting nucleic binding factors bind and regulates its activity. Since 1980 genome of pararetrovirus, are being exploited for developing efficient promoters. Among all of them Cauliflower mosaic virus is the most widely used promoter for gene expression. The basic rational behind the strength of promoter lies in the sequence of cis elements and the spacer nucleotide elements between them, thereby strength of these promoter fragments can be regulated by altering these nucleotide sequences. In the present study sequence of eight putative promoters of plant pararetrovirus are retrieved from National Centre for Biotechnology Information (NCBI) website. These sequence are subjected to various bioinformatics tools comprises of Clustal W, Plant Care, Mathinspector, ModelInspector for establishing the phylogenetic similarity, to identify the quantity and quality of present cis-elements, to find the various common transcription factors binding sites and to determine the presence of module for various specific functions respectively. A range of 28.80-56.0 percentage identification was observed in phylogenetic analysis, with the greatest similarity in Mirabilis mosaic virus and Dahlia mosaic virus. A broad range of cis-elements (51), transcription factor binding site (512) was obtained and 60% observed module are in combination with DOFF motif which shows a function relevance with abiotic stress inducibility. The present study had revealed the functional significance of these elements in gene regulation of pararetrovirus genome and also gives a overall idea for designing novel synthetic promoter.

Genome-wide analysis of cis-regulatory element structure and discovery of motif-driven gene co-expression networks in grapevine

Coordinated transcriptional and metabolic reprogramming ensures a plant’s continued growth and survival under adverse environmental conditions. Transcription factors (TFs) act to modulate gene expression through complex cis-regulatory element (CRE) interactions. Genome-wide analysis of known plant CREs was performed for all currently predicted protein-coding gene promoters in grapevine (Vitis vinifera L.). Many CREs such as abscisic acid (ABA)-responsive, drought-responsive, auxin-responsive, and evening elements, exhibit bona fide CRE properties such as strong position bias towards the transcription start site (TSS) and over-representation when compared with random promoters. Genes containing these CREs are enriched in a large repertoire of plant biological pathways. Large-scale transcriptome analyses also show that these CREs are highly implicated in grapevine development and stress response. Numerous CRE-driven modules in condition-specific gene co-expression networks (GCNs) were identified and many of these modules were highly enriched for plant biological functions. Several modules corroborate known roles of CREs in drought response, pathogen defense, cell wall metabolism, and fruit ripening, whereas others reveal novel functions in plants. Comparisons with Arabidopsis suggest a general conservation in promoter architecture, gene expression dynamics, and GCN structure across species. Systems analyses of CREs provide insights into the grapevine cis-regulatory code and establish a foundation for future genomic studies in grapevine.

TSSPlant: a new tool for prediction of plant Pol II promoters

Our current knowledge of eukaryotic promoters indicates their complex architecture that is often composed of numerous functional motifs. Most of known promoters include multiple and in some cases mutually exclusive transcription start sites (TSSs). Moreover, TSS selection depends on cell/tissue, development stage and environmental conditions. Such complex promoter structures make their computational identification notoriously difficult. Here, we present TSSPlant, a novel tool that predicts both TATA and TATA-less promoters in sequences of a wide spectrum of plant genomes. The tool was developed by using large promoter collections from ppdb and PlantProm DB. It utilizes eighteen significant compositional and signal features of plant promoter sequences selected in this study, that feed the artificial neural network-based model trained by the backpropagation algorithm. TSSPlant achieves significantly higher accuracy compared to the next best promoter prediction program for both TATA promoters (MCC≃0.84 and F1-score≃0.91 versus MCC≃0.51 and F1-score≃0.71) and TATA-less promoters (MCC≃0.80, F1-score≃0.89 versus MCC≃0.29 and F1-score≃0.50). TSSPlant is available to download as a standalone program at http://www.cbrc.kaust.edu.sa/download/.

DNA structural features of eukaryotic TATA-containing and TATA-less promoters

Eukaryotic genes can be broadly classified as TATA‐containing and TATA‐less based on the presence of TATA box in their promoters. Experiments on both classes of genes have revealed a disparity in the regulation of gene expression and cellular functions between the two classes. In this study, we report characteristic differences in promoter sequences and associated structural properties of the two categories of genes in six different eukaryotes. We have analyzed three structural features, DNA duplex stability, bendability, and curvature along with the distribution of A‐tracts, G‐quadruplex motifs, and CpG islands. The structural feature analyses reveal that while the two classes of gene promoters are distinctly different from each other, the properties are also distinguishable across the six organisms.

Genome-Wide Targets Regulated by the OsMADS1 Transcription Factor Reveals Its DNA Recognition Properties

OsMADS1 controls rice (Oryza sativa) floral fate and organ development. Yet, its genome-wide targets and the mechanisms underlying its role as a transcription regulator controlling developmental gene expression are unknown. We identify 3112 gene-associated OsMADS1-bound sites in the floret genome. These occur in the vicinity of transcription start sites, within gene bodies, and in intergenic regions. Majority of the bound DNA contained CArG motif variants or, in several cases, only A-tracts. Sequences flanking the binding peak had a higher AT nucleotide content, implying that broader DNA structural features may define in planta binding. Sequences for binding by other transcription factor families like MYC, AP2/ERF, bZIP, etc. are enriched in OsMADS1-bound DNAs. Target genes implicated in transcription, chromatin remodeling, cellular processes, and hormone metabolism were enriched. Combining expression data from OsMADS1 knockdown florets with these DNA binding data, a snapshot of a gene regulatory network was deduced where targets, such as AP2/ERF and bHLH transcription factors and chromatin remodelers form nodes. We show that the expression status of these nodal factors can be altered by inducing the OsMADS1-GR fusion protein and present a model for a regulatory cascade where the direct targets of OsMADS1, OsbHLH108/SPT, OsERF034, and OsHSF24, in turn control genes such as OsMADS32 and OsYABBY5 This cascade, with other similar relationships, cumulatively contributes to floral organ development. Overall, OsMADS1 binds to several regulatory genes and, probably in combination with other factors, controls a gene regulatory network that ensures rice floret development.

Bioinformatic prediction of transcription factor binding sites at promoter regions of genes for photoperiod and vernalization responses in model and temperate cereal plants

Background

Many genes involved in responses to photoperiod and vernalization have been characterized or predicted in Arabidopsis (Arabidopsis thaliana), Brachypodium (Brachypodium distachyon), wheat (Triticum aestivum) and barley (Hordeum vulgare). However, little is known about the transcription regulation of these genes, especially in the large, complex genomes of wheat and barley.

Results

We identified 68, 60, 195 and 61 genes that are known or postulated to control pathways of photoperiod (PH), vernalization (VE) and pathway integration (PI) in Arabidopsis, Brachypodium, wheat and barley for predicting transcription factor binding sites (TFBSs) in the promoters of these genes using the FIMO motif search tool of the MEME Suite. The initial predicted TFBSs were filtered to confirm the final numbers of predicted TFBSs to be 1066, 1379, 1528, and 789 in Arabidopsis, Brachypodium, wheat and barley, respectively. These TFBSs were mapped onto the PH, VE and PI pathways to infer about the regulation of gene expression in Arabidopsis and cereal species. The GC contents in promoters, untranslated regions (UTRs), coding sequences and introns were higher in the three cereal species than those in Arabidopsis. The predicted TFBSs were most abundant for two transcription factor (TF) families: MADS-box and CSD (cold shock domain). The analysis of publicly available gene expression data showed that genes with similar numbers of MADS-box and CSD TFBSs exhibited similar expression patterns across several different tissues and developmental stages. The intra-specific Tajima D-statistics of TFBS motif diversity showed different binding specificity among different TF families. The inter-specific Tajima D-statistics suggested faster TFBS divergence in TFBSs than in coding sequences and introns. Mapping TFBSs onto the PH, VE and PI pathways showed the predominance of MADS-box and CSD TFBSs in most genes of the four species, and the difference in the pathway regulations between Arabidopsis and the three cereal species.

Conclusion

Our approach to associating the key flowering genes with their potential TFs through prediction of putative TFBSs provides a framework to explore regulatory mechanisms of photoperiod and vernalization responses in flowering plants. The predicted TFBSs in the promoters of the flowering genes provide a basis for molecular characterization of transcription regulation in the large, complex genomes of important crop species, wheat and barley.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2916-7) contains supplementary material, which is available to authorized users.

The Purine Bias of Coding Sequences is Determined by Physicochemical Constraints on Proteins

For this report, we analyzed protein secondary structures in relation to the statistics of three nucleotide codon positions. The purpose of this investigation was to find which properties of the ribosome, tRNA or protein level, could explain the purine bias (Rrr) as it is observed in coding DNA. We found that the Rrr pattern is the consequence of a regularity (the codon structure) resulting from physicochemical constraints on proteins and thermodynamic constraints on ribosomal machinery. The physicochemical constraints on proteins mainly come from the hydropathy and molecular weight (MW) of secondary structures as well as the energy cost of amino acid synthesis. These constraints appear through a network of statistical correlations, such as (i) the cost of amino acid synthesis, which is in favor of a higher level of guanine in the first codon position, (ii) the constructive contribution of hydropathy alternation in proteins, (iii) the spatial organization of secondary structure in proteins according to solvent accessibility, (iv) the spatial organization of secondary structure according to amino acid hydropathy, (v) the statistical correlation of MW with protein secondary structures and their overall hydropathy, (vi) the statistical correlation of thymine in the second codon position with hydropathy and the energy cost of amino acid synthesis, and (vii) the statistical correlation of adenine in the second codon position with amino acid complexity and the MW of secondary protein structures. Amino acid physicochemical properties and functional constraints on proteins constitute a code that is translated into a purine bias within the coding DNA via tRNAs. In that sense, the Rrr pattern within coding DNA is the effect of information transfer on nucleotide composition from protein to DNA by selection according to the codon positions. Thus, coding DNA structure and ribosomal machinery co-evolved to minimize the energy cost of protein coding given the functional constraints on proteins.

Structural properties of prokaryotic promoter regions correlate with functional features

The structural properties of the DNA molecule are known to play a critical role in transcription. In this paper, the structural profiles of promoter regions were studied within the context of their diversity and their function for eleven prokaryotic species; Escherichia coli, Klebsiella pneumoniae, Salmonella Typhimurium, Pseudomonas auroginosa, Geobacter sulfurreducens Helicobacter pylori, Chlamydophila pneumoniae, Synechocystis sp., Synechoccocus elongates, Bacillus anthracis, and the archaea Sulfolobus solfataricus. The main anchor point for these promoter regions were transcription start sites identified through high-throughput experiments or collected within large curated databases. Prokaryotic promoter regions were found to be less stable and less flexible than the genomic mean across all studied species. However, direct comparison between species revealed differences in their structural profiles that can not solely be explained by the difference in genomic GC content. In addition, comparison with functional data revealed that there are patterns in the promoter structural profiles that can be linked to specific functional loci, such as sigma factor regulation or transcription factor binding. Interestingly, a novel structural element clearly visible near the transcription start site was found in genes associated with essential cellular functions and growth in several species. Our analyses reveals the great diversity in promoter structural profiles both between and within prokaryotic species. We observed relationships between structural diversity and functional features that are interesting prospects for further research to yet uncharacterized functional loci defined by DNA structural properties.

Role of DNA sequence based structural features of promoters in transcription initiation and gene expression

Regulatory information for transcription initiation is present in a stretch of genomic DNA, called the promoter region that is located upstream of the transcription start site (TSS) of the gene. The promoter region interacts with different transcription factors and RNA polymerase to initiate transcription and contains short stretches of transcription factor binding sites (TFBSs), as well as structurally unique elements. Recent experimental and computational analyses of promoter sequences show that they often have non-B-DNA structural motifs, as well as some conserved structural properties, such as stability, bendability, nucleosome positioning preference and curvature, across a class of organisms. Here, we briefly describe these structural features, the differences observed in various organisms and their possible role in regulation of gene expression.

A double SORLIP1 element is required for high light induction of ELIP genes in Arabidopsis thaliana

Promoter elements that contribute to high light (HL) induction of the Arabidopsis ELIP1 gene were defined using a transgenic promoter-reporter system. Two adjacent SORLIP1 elements (double SORLIP1, dSL) were found to be essential for HL induction of a GUS reporter gene. The dSL element was also found to be essential for HL induction conferred by the ELIP2 promoter. SORLIP1 elements were enriched in ELIP promoters throughout the plant kingdom, and showed a clade-specific pattern of gain or loss that suggested functionality. In addition, two G-box elements were found to redundantly contribute to HL induction conferred by the ELIP1 promoter.

Genetic and epigenetic determinants mediate proneness of oncogene breakpoint sites for involvement in TCR translocations

T-cell receptor (TCR) translocations are a genetic hallmark of T-cell acute lymphoblastic leukemia and lead to juxtaposition of oncogene and TCR loci. Oncogene loci become involved in translocations because they are accessible to the V(D)J recombination machinery. Such accessibility is predicted at cryptic recombination signal sequence (cRSS) sites ('Type 1') as well as other sites that are subject to DNA double-strand breaks (DSBs) ('Type 2') during early stages of thymocyte development. As chromatin accessibility markers have not been analyzed in the context of TCR-associated translocations, various genetic and epigenetic determinants of LMO2, TAL1 and TLX1 translocation breakpoint (BP) sites and BP cluster regions (BCRs) were examined in human thymocytes to establish DSB proneness and heterogeneity of BP site involvement in TCR translocations. Our data show that DSBs in BCRs are primarily induced in the presence of a genetic element of sequence vulnerability (cRSSs, transposable elements), whereas breaks at single BP sites lacking such elements are more likely induced by chance or perhaps because of patient-specific genetic vulnerability. Vulnerability to obtain DSBs is increased by features that determine chromatin organization, such as methylation status and nucleosome occupancy, although at different levels at different BP sites.

Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the computational prediction of CPEs across eight plant genomes to help better understand the transcription initiation complex assembly. The distribution of thirteen known CPEs across four monocots (Brachypodium distachyon, Oryza sativa ssp. japonica, Sorghum bicolor, Zea mays) and four dicots (Arabidopsis thaliana, Populus trichocarpa, Vitis vinifera, Glycine max) reveals the structural organization of the core promoter in relation to the TATA-box as well as with respect to other CPEs. The distribution of known CPE motifs with respect to transcription start site (TSS) exhibited positional conservation within monocots and dicots with slight differences across all eight genomes. Further, a more refined subset of annotated genes based on orthologs of the model monocot (O. sativa ssp. japonica) and dicot (A. thaliana) genomes supported the positional distribution of these thirteen known CPEs. DNA free energy profiles provided evidence that the structural properties of promoter regions are distinctly different from that of the non-regulatory genome sequence. It also showed that monocot core promoters have lower DNA free energy than dicot core promoters. The comparison of monocot and dicot promoter sequences highlights both the similarities and differences in the core promoter architecture irrespective of the species-specific nucleotide bias. This study will be useful for future work related to genome annotation projects and can inspire research efforts aimed to better understand regulatory mechanisms of transcription.

Comparative analysis of microRNA promoters in Arabidopsis and rice

Endogenously-encoded microRNAs (miRNAs) are a class of small regulatory RNAs that modulate gene expression at the post-transcriptional level. In plants, miRNAs have increasingly been identified by experiments based on next-generation sequencing (NGS). However, promoter organization is currently unknown for most plant miRNAs, which are transcribed by RNA polymerase II. This deficiency prevents a comprehensive understanding of miRNA-mediated gene networks. In this study, by analyzing full-length cDNA sequences related to miRNAs, we mapped transcription start sites (TSSs) for 62 and 55 miRNAs in Arabidopsis and rice, respectively. The average free energy (AFE) profiles in the vicinity of TSSs were studied for both species. By employing position weight matrices (PWM) for 99 plant cis-elements, we discovered that three cis-elements were over-represented in the miRNA promoters of both species, while four and ten cis-elements were over-represented in Arabidopsis only and in rice only. Thus, comparison of miRNA promoters between Arabidopsis and rice provides a new perspective for studying miRNA regulation in plants.

Identification and analysis of the proximal promoters of microRNA genes in Arabidopsis

Endogenous microRNAs (miRNAs) modulate gene expression at the post-transcription level. In plants, a vast majority of MIR genes are thought to be transcribed by RNA Polymerase II (Pol II). However, promoter organization is currently unknown for most plant MIR genes. This deficiency prevents a comprehensive understanding of miRNA-mediated gene networks. In this study, we performed Pol II chromatin immunoprecipitation (ChIP) analysis in Arabidopsis using a genome tiling microarray. Distinct Pol II binding was found at most MIR loci, which allowed prediction of the transcription start sites (TSSs) for 167 MIR genes in Arabidopsis that was validated by average free energy profiling. By employing 99 position weight matrices (PWM), we systematically scanned the regulatory regions upstream of the TSSs. We discovered eleven and ten cis-elements that are statistically over- and under-represented in MIR promoters, respectively. Thus, analysis of Pol II binding provides a new perspective for studying miRNAs in plants.

DNA-energetics-based analyses suggest additional genes in prokaryotes

We present here a novel methodology for predicting new genes in prokaryotic genomes on the basis of inherent energetics of DNA. Regions of higher thermodynamic stability were identified, which were filtered based on already known annotations to yield a set of potentially new genes. These were then processed for their compatibility with the stereo-chemical properties of proteins and tripeptide frequencies of proteins in Swissprot data, which results in a reliable set of new genes in a genome. Quite surprisingly, the methodology identifies new genes even in well-annotated genomes. Also, the methodology can handle genomes of any GC-content, size and number of annotated genes.

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.

Development and functional analysis of novel genetic promoters using DNA shuffling, hybridization and a combination thereof

BACKGROUND

Development of novel synthetic promoters with enhanced regulatory activity is of great value for a diverse range of plant biotechnology applications.

METHODOLOGY

Using the Figwort mosaic virus full-length transcript promoter (F) and the sub-genomic transcript promoter (FS) sequences, we generated two single shuffled promoter libraries (LssF and LssFS), two multiple shuffled promoter libraries (LmsFS-F and LmsF-FS), two hybrid promoters (FuasFScp and FSuasFcp) and two hybrid-shuffled promoter libraries (LhsFuasFScp and LhsFSuasFcp). Transient expression activities of approximately 50 shuffled promoter clones from each of these libraries were assayed in tobacco (Nicotiana tabacum cv. Xanthi) protoplasts. It was observed that most of the shuffled promoters showed reduced activity compared to the two parent promoters (F and FS) and the CaMV35S promoter. In silico studies (computer simulated analyses) revealed that the reduced promoter activities of the shuffled promoters could be due to their higher helical stability. On the contrary, the hybrid promoters FuasFScp and FSuasFcp showed enhanced activities compared to F, FS and CaMV 35S in both transient and transgenic Nicotiana tabacum and Arabidopsis plants. Northern-blot and qRT-PCR data revealed a positive correlation between transcription and enzymatic activity in transgenic tobacco plants expressing hybrid promoters. Histochemical/X-gluc staining of whole transgenic seedlings/tissue-sections and fluorescence images of ImaGene Green™ treated roots and stems expressing the GUS reporter gene under the control of the FuasFScp and FSuasFcp promoters also support the above findings. Furthermore, protein extracts made from protoplasts expressing the human defensin (HNP-1) gene driven by hybrid promoters showed enhanced antibacterial activity compared to the CaMV35S promoter.

SIGNIFICANCE/CONCLUSION

Both shuffled and hybrid promoters developed in the present study can be used as molecular tools to study the regulation of ectopic gene expression in plants.

A comparison study on feature selection of DNA structural properties for promoter prediction

Background

Promoter prediction is an integrant step for understanding gene regulation and annotating genomes. Traditional promoter analysis is mainly based on sequence compositional features. Recently, many kinds of structural features have been employed in promoter prediction. However, considering the high-dimensionality and overfitting problems, it is unfeasible to utilize all available features for promoter prediction. Thus it is necessary to choose some appropriate features for the prediction task.

Results

This paper conducts an extensive comparison study on feature selection of DNA structural properties for promoter prediction. Firstly, to examine whether promoters possess some special structures, we carry out a systematical comparison among the profiles of thirteen structural features on promoter and non-promoter sequences. Secondly, we investigate the correlations between these structural features and promoter sequences. Thirdly, both filter and wrapper methods are utilized to select appropriate feature subsets from thirteen different kinds of structural features for promoter prediction, and the predictive power of the selected feature subsets is evaluated. Finally, we compare the prediction performance of the feature subsets selected in this paper with nine existing promoter prediction approaches.

Conclusions

Experimental results show that the structural features are differentially correlated to promoters. Specifically, DNA-bending stiffness, DNA denaturation and energy-related features are highly correlated with promoters. The predictive power for promoter sequences differentiates greatly among different structural features. Selecting the relevant features can significantly improve the accuracy of promoter prediction.

Isolation and in silico analysis of promoter of a high salinity stress-regulated pea DNA helicase 45

Helicases are motor proteins that can transiently catalyze the unwinding of energetically stable duplex DNA or RNA molecules by using ATP hydrolysis as the source of energy. Many helicases share a core region of highly conserved sequence motifs, and belong to the rapidly growing DEAD-box protein family. Pea DNA helicase 45 (PDH45), that exhibits striking homology with eukaryotic translation initiation factor 4A (eIF4A), contains ATP-dependent DNA and RNA helicase, DNA-dependent ATPase, and ATP-binding activities. The transcript of the PDH45 gene was reported to be upregulated in pea plant in response to high salinity, cold stress, abscisic acid (ABA), dehydration and early wounding. The first direct evidence that overexpression of PDH45 confers salinity stress tolerance without yield loss has also been reported. A promoter analysis of PDH45 gene has not been studied. The cis-regulatory elements present on promoter region of the gene act as binding sites for RNA polymerase and transcription factors and control the regulation of gene expression. Here we report the promoter of the PDH45 gene that contains stress-responsive cis-regulatory elements which may be responsible for regulating the expression of PDH45 under abiotic stress conditions.