DNA Sequence Elements Research Articles

Consulting prostate cancer cohort data uncovers transcriptional control: Regulation of the MARCH6 gene

Cholesterol accumulation is a hallmark of prostate cancer (PCa) enabled by the upregulation of its synthesis, which presents a potential therapeutic target. This pathway is suppressed by the E3 ubiquitin ligase membrane-associated RING-CH-type finger 6 (MARCH6); however, little is known of MARCH6 regulation, particularly at the transcriptional level. Here, we consulted large transcriptomic PCa datasets to investigate transcription factors and DNA sequence elements that regulate the MARCH6 gene. Amongst 498 primary PCa tissues of The Cancer Genome Atlas, we identified a striking positive correlation between MARCH6 and androgen receptor (AR) gene expression (r = 0.81, p < 1 × 10−117) that held in other primary tumour datasets. Two putative androgen response elements were identified in the MARCH6 gene using motif prediction and mining of publicly accessible chromatin immunoprecipitation-sequencing data. However, MARCH6 expression was not androgen-responsive in luciferase reporter and qRT-PCR assays. Instead, we established that the MARCH6–AR correlation in primary PCa is due to common regulation by the transcription factor Sp1. We located a region 100 bp downstream of the MARCH6 transcriptional start site that contains three Sp1 binding sites and strongly upregulates promoter activity. The functionality of this region, and Sp1-mediated upregulation of MARCH6, was confirmed using pharmacological and genetic inhibition of Sp1. Moreover, modulation of Sp1 activity affected the stability of squalene monooxygenase, a cholesterol biosynthesis enzyme and MARCH6 substrate. We thus establish Sp1 as the first known regulator of the MARCH6 gene and demonstrate that interrogation of transcriptomic datasets can assist in the de novo inference of transcriptional regulation.

Location deviations of DNA functional elements affected SNP mapping in the published databases and references.

The recent extensive application of next-generation sequencing has led to the rapid accumulation of multiple types of data for functional DNA elements. With the advent of precision medicine, the fine-mapping of risk loci based on these elements has become of paramount importance. In this study, we obtained the human reference genome (GRCh38) and the main DNA sequence elements, including protein-coding genes, miRNAs, lncRNAs and single nucleotide polymorphism flanking sequences, from different repositories. We then realigned these elements to identify their exact locations on the genome. Overall, 5%-20% of all sequence element locations deviated among databases, on the scale of kilobase-pair to megabase-pair. These deviations even affected the selection of genome-wide association study risk-associated genes. Our results implied that the location information for functional DNA elements may deviate among public databases. Researchers should take care when using cross-database sources and should perform pilot sequence alignments before element location-based studies.

The TAFs of TFIID Bind and Rearrange the Topology of the TATA-Less RPS5 Promoter

The general transcription factor TFIID is a core promoter selectivity factor that recognizes DNA sequence elements and nucleates the assembly of a pre-initiation complex (PIC). The mechanism by which TFIID recognizes the promoter is poorly understood. The TATA-box binding protein (TBP) is a subunit of the multi-protein TFIID complex believed to be key in this process. We reconstituted transcription from highly purified components on a ribosomal protein gene (RPS5) and discovered that TFIIDΔTBP binds and rearranges the promoter DNA topology independent of TBP. TFIIDΔTBP binds ~200 bp of the promoter and changes the DNA topology to a larger extent than the nucleosome core particle. We show that TBP inhibits the DNA binding activities of TFIIDΔTBP and conclude that the complete TFIID complex may represent an auto-inhibited state. Furthermore, we show that the DNA binding activities of TFIIDΔTBP are required for assembly of a PIC poised to select the correct transcription start site (TSS).

Insights into the DNA sequence elements required for partitioning and copy number control of the yeast 2-micron plasmid.

The yeast 2-micron plasmid is an almost perfect selfish DNA. The entire coding capacity of the plasmid is dedicated to ensuring its own inheritance, with no benefit to its host. Despite high copy number, the plasmid confers no phenotype. It manages this feat by possessing mechanisms for plasmid copy-number control and for partitioning. The former increases plasmid numbers when they fall, but is repressed at high copy number, while the latter ensures 2-micron copies are equally partitioned during host cell division. Although the plasmid amplification mechanism is well established, the partitioning system and the means by which the 2-micron plasmid partitioning proteins, Rep1 and Rep2, regulate plasmid copy number remain incompletely understood. This review focuses on recent efforts to determine the nature of Rep protein complexes formed at the plasmid stability locus (STB) and at plasmid gene promoters, the identity of DNA sequence elements required for Rep protein association, and the mechanism by which the Rep proteins manage their dual roles of plasmid partitioning and plasmid gene repression.

Physicochemical property based computational scheme for classifying DNA sequence elements of Saccharomyces cerevisiae

GenerationE of huge “omics” data necessitates the development and application of computational methods to annotate the data in terms of biological features. In the context of DNA sequence, it is important to unravel the hidden physicochemical signatures. For this purpose, we have considered various sequence elements such as promoter, ACS, LTRs, telomere, and retrotransposon of the model organism Saccharomyces cerevisiae. Contributions due to di-nucleotides play a major role in studying the DNA conformation profile. The physicochemical parameters used are hydrogen bonding energy, stacking energy and solvation energy per base pair. Our computational study shows that all sequence elements in this study have distinctive physicochemical signatures and the same can be exploited for prediction experiments. The order that we see in a DNA sequence is dictated by biological regions and hence, there exists role of dependency in the sequence makeup, keeping this in mind we are proposing two computational schemes (a) using a windowing block size procedure and (b) using di-nucleotide transitions. We obtained better discriminating profile when we analyzed the sequence data in windowing manner. In the second novel approach, we introduced the di-nucleotide transition probability matrix (DTPM) to study the hidden layer of information embedded in the sequences. DTPM has been used as weights for scanning and predictions. This proposed computational scheme incorporates the memory property which is more realistic to study the physicochemical properties embedded in DNA sequences. Our analysis shows that the DTPM scheme performs better than the existing method in this applied region. Characterization of these elements will be a key to genome editing applications and advanced machine learning approaches may also require such distinctive profiles as useful input features.

Control of human gene expression: High abundance of divergent transcription in genes containing both INR and BRE elements in the core promoter.

BackgroundDNA sequence elements in the core promoter can play a central role in regulation of gene expression. Core elements (e.g. INR and TATA box) are located within ~50bp of the transcription start site and both upstream and downstream elements are known. Although all can affect the level of gene expression, their mechanism of action has yet to be fully defined. The studies described here are focused on two core promoter elements, INR and BRE, in the human genome. The locations of the two elements were determined in a large number of human promoters and the results were interpreted in terms of overall promoter function.ResultsA total of 13,406 promoters were collected from the reference version of the human genome and found to contain 62,891 INR sequences and 32,290 BRE. An INR sequence was found in the core region of 1231 (9.2%) promoters and a BRE in 2592 (19.3%); 121 promoters (0.9%) have both INR and BRE elements. Counts support the view that most human promoters lack an INR or BRE element in the core promoter. Further analysis was carried out with the aligned aggregate of promoters from each chromosome. The results showed distinct INR distributions in separate chromosome groups indicating a degree of chromosome specificity to the way core promoter elements are deployed in the genome. The rare promoters with both INR and BRE elements were found to be enriched among the genes with divergent transcription. Enrichment raises the possibility that core promoter elements can have a function in chromosome organization as well as in initiation of transcription.

Mutational analysis of a Drosophila neuroblast enhancer governing nubbin expression during CNS development

SummaryWhile developmental studies of Drosophila neural stem cell lineages have identified transcription factors (TFs) important to cell identity decisions, currently only an incomplete understanding exists of the cis‐regulatory elements that control the dynamic expression of these TFs. Our previous studies have identified multiple enhancers that regulate the POU‐domain TF paralogs nubbin and pdm‐2 genes. Evolutionary comparative analysis of these enhancers reveals that they each contain multiple conserved sequence blocks (CSBs) that span TF DNA‐binding sites for known regulators of neuroblast (NB) gene expression in addition to novel sequences. This study functionally analyzes the conserved DNA sequence elements within a NB enhancer located within the nubbin gene and highlights a high level of complexity underlying enhancer structure. Mutational analysis has revealed CSBs that are important for enhancer activation and silencing in the developing CNS. We have also observed that adjusting the number and relative positions of the TF binding sites within these CSBs alters enhancer function.

G-Anchor: a novel approach for whole-genome comparative mapping utilizing evolutionary conserved DNA sequences.

BackgroundCross-species whole-genome sequence alignment is a critical first step for genome comparative analyses, ranging from the detection of sequence variants to studies of chromosome evolution. Animal genomes are large and complex, and whole-genome alignment is a computationally intense process, requiring expensive high-performance computing systems due to the need to explore extensive local alignments. With hundreds of sequenced animal genomes available from multiple projects, there is an increasing demand for genome comparative analyses.ResultsHere, we introduce G-Anchor, a new, fast, and efficient pipeline that uses a strictly limited but highly effective set of local sequence alignments to anchor (or map) an animal genome to another species’ reference genome. G-Anchor makes novel use of a databank of highly conserved DNA sequence elements. We demonstrate how these elements may be aligned to a pair of genomes, creating anchors. These anchors enable the rapid mapping of scaffolds from a de novo assembled genome to chromosome assemblies of a reference species. Our results demonstrate that G-Anchor can successfully anchor a vertebrate genome onto a phylogenetically related reference species genome using a desktop or laptop computer within a few hours and with comparable accuracy to that achieved by a highly accurate whole-genome alignment tool such as LASTZ. G-Anchor thus makes whole-genome comparisons accessible to researchers with limited computational resources.ConclusionsG-Anchor is a ready-to-use tool for anchoring a pair of vertebrate genomes. It may be used with large genomes that contain a significant fraction of evolutionally conserved DNA sequences and that are not highly repetitive, polypoid, or excessively fragmented. G-Anchor is not a substitute for whole-genome aligning software but can be used for fast and accurate initial genome comparisons.G-Anchor is freely available and a ready-to-use tool for the pairwise comparison of two genomes.

Recognition of the long range enhancer-promoter interactions by further adding DNA structure properties and transcription factor binding motifs in human cell lines

The enhancer-promoter interactions (EPIs) with strong tissue-specificity play an important role in cis-regulatory mechanism of human cell lines. However, it still remains a challenging work to predict these interactions so far. Due to that these interactions are regulated by the cooperativeness of diverse functional genomic signatures, DNA spatial structure and DNA sequence elements. In this paper, by adding DNA structure properties and transcription factor binding motifs, we presented an improved computational method to predict EPIs in human cell lines. In comparison with the results of other group on the same datasets, our best accuracies by cross-validation test were about 15%–24% higher in the same cell lines, and the accuracies by independent test were about 11%–15% higher in new cell lines. Meanwhile, we found that transcription factor binding motifs and DNA structure properties have important information that would largely determine long range EPIs prediction. From the distribution comparisons, we also found their distinct differences between interacting and non-interacting sets in each cell line. Then, the correlation analysis and network models for relationships among top-ranked functional genomic signatures indicated that diverse genomic signatures would cooperatively establish a complex regulatory network to facilitate long range EPIs. The experimental results provided additional insights about the roles of DNA intrinsic properties and functional genomic signatures in EPIs prediction.

SINE_scan: an efficient tool to discover short interspersed nuclear elements (SINEs) in large-scale genomic datasets.

MotivationShort Interspersed Nuclear Elements (SINEs) are transposable elements (TEs) that amplify through a copy-and-paste mode via RNA intermediates. The computational identification of new SINEs are challenging because of their weak structural signals and rapid diversification in sequences.ResultsHere we report SINE_Scan, a highly efficient program to predict SINE elements in genomic DNA sequences. SINE_Scan integrates hallmark of SINE transposition, copy number and structural signals to identify a SINE element. SINE_Scan outperforms the previously published de novo SINE discovery program. It shows high sensitivity and specificity in 19 plant and animal genome assemblies, of which sizes vary from 120 Mb to 3.5 Gb. It identifies numerous new families and substantially increases the estimation of the abundance of SINEs in these genomes.Availability and ImplementationThe code of SINE_Scan is freely available at http://github.com/maohlzj/SINE_Scan, implemented in PERL and supported on Linux.Supplementary information Supplementary data are available at Bioinformatics online.

Control of transcriptional pausing by biased thermal fluctuations on repetitive genomic sequences

In the process of transcription elongation, RNA polymerase (RNAP) pauses at highly nonrandom positions across genomic DNA, broadly regulating transcription; however, molecular mechanisms responsible for the recognition of such pausing positions remain poorly understood. Here, using a combination of statistical mechanical modeling and high-throughput sequencing and biochemical data, we evaluate the effect of thermal fluctuations on the regulation of RNAP pausing. We demonstrate that diffusive backtracking of RNAP, which is biased by repetitive DNA sequence elements, causes transcriptional pausing. This effect stems from the increased microscopic heterogeneity of an elongation complex, and thus is entropy-dominated. This report shows a linkage between repetitive sequence elements encoded in the genome and regulation of RNAP pausing driven by thermal fluctuations.

Identification of repeats in DNA sequences using nucleotide distribution uniformity

Repetitive elements are important in genomic structures, functions and regulations, yet effective methods in precisely identifying repetitive elements in DNA sequences are not fully accessible, and the relationship between repetitive elements and periodicities of genomes is not clearly understood. We present an ab initio method to quantitatively detect repetitive elements and infer the consensus repeat pattern in repetitive elements. The method uses the measure of the distribution uniformity of nucleotides at periodic positions in DNA sequences or genomes. It can identify periodicities, consensus repeat patterns, copy numbers and perfect levels of repetitive elements. The results of using the method on different DNA sequences and genomes demonstrate efficacy and accuracy in identifying repeat patterns and periodicities. The complexity of the method is linear with respect to the lengths of the analyzed sequences. The Python programs in this study are freely available to the public upon request or at https://github.com/cyinbox/DNADU.

Modulation of tissue repair by regeneration enhancer elements.

How tissue regeneration programs are triggered by injury has received limited research attention. Here we investigate the existence of enhancer regulatory elements that are activated in regenerating tissue. Transcriptomic analyses reveal that leptin b (lepb) is highly induced in regenerating hearts and fins of zebrafish. Epigenetic profiling identified a short DNA sequence element upstream and distal to lepb that acquires open chromatin marks during regeneration and enables injury-dependent expression from minimal promoters. This element could activate expression in injured neonatal mouse tissues and was divisible into tissue-specific modules sufficient for expression in regenerating zebrafish fins or hearts. Simple enhancer-effector transgenes employing lepb-linked sequences upstream of pro- or anti-regenerative factors controlled the efficacy of regeneration in zebrafish. Our findings provide evidence for 'tissue regeneration enhancer elements' (TREEs) that trigger gene expression in injury sites and can be engineered to modulate the regenerative potential of vertebrate organs.

The Study of Molecular Evidences for Human Evolution, Gene Flow, Genetic Isolation, Interbreeding and Their Significance in the Human Physiology

Human evolution, from its inception, has become an interesting topic for the scientific community as well as a very controversial and sensitive issue in different times, certain communities and ethnic groups. Evidences of evolution in the nineteenth century used to be mostly paleontological studies from fossil records and the comparative studies of the living organism. From the middle of the twentieth century, almost a hundred years after Darwin and Wallace’s work, molecular biology has become an invaluable tool along with genetics and genomics for the study of evolution. Our understanding of the underlying molecular basis of human evolution provides us with the opportunity to closely examine the relationship between the DNA sequence element of anatomically modern humans, archaic humans and their closely related ape ancestors. Emerging evidence of specific DNA sequences within our genome and their expression in proteins aids our understanding of human health, survival advantages or to disease susceptibilities.

Determinants of RNA metabolism in the Schizosaccharomyces pombe genome.

To decrypt the regulatory code of the genome, sequence elements must be defined that determine the kinetics of RNA metabolism and thus gene expression. Here, we attempt such decryption in an eukaryotic model organism, the fission yeast S. pombe. We first derive an improved genome annotation that redefines borders of 36% of expressed mRNAs and adds 487 non‐coding RNAs (ncRNAs). We then combine RNA labeling in vivo with mathematical modeling to obtain rates of RNA synthesis and degradation for 5,484 expressed RNAs and splicing rates for 4,958 introns. We identify functional sequence elements in DNA and RNA that control RNA metabolic rates and quantify the contributions of individual nucleotides to RNA synthesis, splicing, and degradation. Our approach reveals distinct kinetics of mRNA and ncRNA metabolism, separates antisense regulation by transcription interference from RNA interference, and provides a general tool for studying the regulatory code of genomes.

Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters.

Sparse linear models approximate target variable(s) by a sparse linear combination of input variables. Since they are simple, fast, and able to select features, they are widely used in classification and regression. Essentially they are shallow feed-forward neural networks that have three limitations: (1) incompatibility to model nonlinearity of features, (2) inability to learn high-level features, and (3) unnatural extensions to select features in a multiclass case. Deep neural networks are models structured by multiple hidden layers with nonlinear activation functions. Compared with linear models, they have two distinctive strengths: the capability to (1) model complex systems with nonlinear structures and (2) learn high-level representation of features. Deep learning has been applied in many large and complex systems where deep models significantly outperform shallow ones. However, feature selection at the input level, which is very helpful to understand the nature of a complex system, is still not well studied. In genome research, the cis-regulatory elements in noncoding DNA sequences play a key role in the expression of genes. Since the activity of regulatory elements involves highly interactive factors, a deep tool is strongly needed to discover informative features. In order to address the above limitations of shallow and deep models for selecting features of a complex system, we propose a deep feature selection (DFS) model that (1) takes advantages of deep structures to model nonlinearity and (2) conveniently selects a subset of features right at the input level for multiclass data. Simulation experiments convince us that this model is able to correctly identify both linear and nonlinear features. We applied this model to the identification of active enhancers and promoters by integrating multiple sources of genomic information. Results show that our model outperforms elastic net in terms of size of discriminative feature subset and classification accuracy.

Structural and Mechanistic Basis of PAM-Dependent Spacer Acquisition in CRISPR-Cas Systems

Bacteria acquire memory of viral invaders by incorporating invasive DNA sequence elements into the host CRISPR locus, generating a new spacer within the CRISPR array. We report on the structures of Cas1-Cas2-dual-forked DNA complexes in an effort toward understanding how the protospacer is sampled prior to insertion into the CRISPR locus. Our study reveals a protospacer DNA comprising a 23-bp duplex bracketed by tyrosine residues, together with anchored flanking 3' overhang segments. The PAM-complementary sequence in the 3' overhang is recognized by the Cas1a catalytic subunits in a base-specific manner, and subsequent cleavage at positions 5 nt from the duplex boundary generates a 33-nt DNA intermediate that is incorporated into the CRISPR array via a cut-and-paste mechanism. Upon protospacer binding, Cas1-Cas2 undergoes a significant conformational change, generating a flat surface conducive to proper protospacer recognition. Here, our study provides important structure-based mechanistic insights into PAM-dependent spacer acquisition.

Molecular Mechanisms of Transcription Initiation at gal Promoters and their Multi-Level Regulation by GalR, CRP and DNA Loop.

Studying the regulation of transcription of the gal operon that encodes the amphibolic pathway of d-galactose metabolism in Escherichia coli discerned a plethora of principles that operate in prokaryotic gene regulatory processes. In this chapter, we have reviewed some of the more recent findings in gal that continues to reveal unexpected but important mechanistic details. Since the operon is transcribed from two overlapping promoters, P1 and P2, regulated by common regulatory factors, each genetic or biochemical experiment allowed simultaneous discernment of two promoters. Recent studies range from genetic, biochemical through biophysical experiments providing explanations at physiological, mechanistic and single molecule levels. The salient observations highlighted here are: the axiom of determining transcription start points, discovery of a new promoter element different from the known ones that influences promoter strength, occurrence of an intrinsic DNA sequence element that overrides the transcription elongation pause created by a DNA-bound protein roadblock, first observation of a DNA loop and determination its trajectory, and piggybacking proteins and delivering to their DNA target.

Nonconsensus Protein Binding to Repetitive DNA Sequence Elements Significantly Affects Eukaryotic Genomes.

Recent genome-wide experiments in different eukaryotic genomes provide an unprecedented view of transcription factor (TF) binding locations and of nucleosome occupancy. These experiments revealed that a large fraction of TF binding events occur in regions where only a small number of specific TF binding sites (TFBSs) have been detected. Furthermore, in vitro protein-DNA binding measurements performed for hundreds of TFs indicate that TFs are bound with wide range of affinities to different DNA sequences that lack known consensus motifs. These observations have thus challenged the classical picture of specific protein-DNA binding and strongly suggest the existence of additional recognition mechanisms that affect protein-DNA binding preferences. We have previously demonstrated that repetitive DNA sequence elements characterized by certain symmetries statistically affect protein-DNA binding preferences. We call this binding mechanism nonconsensus protein-DNA binding in order to emphasize the point that specific consensus TFBSs do not contribute to this effect. In this paper, using the simple statistical mechanics model developed previously, we calculate the nonconsensus protein-DNA binding free energy for the entire C. elegans and D. melanogaster genomes. Using the available chromatin immunoprecipitation followed by sequencing (ChIP-seq) results on TF-DNA binding preferences for ~100 TFs, we show that DNA sequences characterized by low predicted free energy of nonconsensus binding have statistically higher experimental TF occupancy and lower nucleosome occupancy than sequences characterized by high free energy of nonconsensus binding. This is in agreement with our previous analysis performed for the yeast genome. We suggest therefore that nonconsensus protein-DNA binding assists the formation of nucleosome-free regions, as TFs outcompete nucleosomes at genomic locations with enhanced nonconsensus binding. In addition, here we perform a new, large-scale analysis using in vitro TF-DNA preferences obtained from the universal protein binding microarrays (PBM) for ~90 eukaryotic TFs belonging to 22 different DNA-binding domain types. As a result of this new analysis, we conclude that nonconsensus protein-DNA binding is a widespread phenomenon that significantly affects protein-DNA binding preferences and need not require the presence of consensus (specific) TFBSs in order to achieve genome-wide TF-DNA binding specificity.

Dynamic regulation of transcription factors by nucleosome remodeling.

The chromatin landscape and promoter architecture are dominated by the interplay of nucleosome and transcription factor (TF) binding to crucial DNA sequence elements. However, it remains unclear whether nucleosomes mobilized by chromatin remodelers can influence TFs that are already present on the DNA template. In this study, we investigated the interplay between nucleosome remodeling, by either yeast ISW1a or SWI/SNF, and a bound TF. We found that a TF serves as a major barrier to ISW1a remodeling, and acts as a boundary for nucleosome repositioning. In contrast, SWI/SNF was able to slide a nucleosome past a TF, with concurrent eviction of the TF from the DNA, and the TF did not significantly impact the nucleosome positioning. Our results provide direct evidence for a novel mechanism for both nucleosome positioning regulation by bound TFs and TF regulation via dynamic repositioning of nucleosomes.