DNA Sequence Of Human Genome Research Articles

Assessing Autosomal InDel Loci With Multiple Insertions or Deletions of Random DNA Sequences in Human Genome.

Multiple mutational events of insertion/deletion occurring at or around InDel sites could form multi-allelic InDels and multi-InDels (abbreviated as MM-InDels), while InDels with random DNA sequences could imply a unique mutation event at these loci. In this study, preliminary investigation of MM-InDels with random sequences was conducted using high-throughput phased data from the 1000 Genomes Project. A total of 3,599 multi-allelic InDels and 6,375 multi-InDels were filtered with multiple alleles. A vast majority of the obtained MM-InDels (85.59%) presented 3 alleles, which implies that only one secondary insertion or deletion mutation event occurred at these loci. The more frequent presence of two adjacent InDel loci was observed within 20 bp. MM-InDels with random sequences presented an uneven distribution across the genome and showed a correlation with InDels, SNPs, recombination rate, and GC content. The average allelic frequencies and prevalence of multi-allelic InDels and multi-InDels presented similar distribution patterns in different populations. Altogether, MM-InDels with random sequences can provide useful information for population resolution.

Solid-phase enzyme catalysis of DNA end repair and 3\u2032 A-tailing reduces GC-bias in next-generation sequencing of human genomic DNA

The use of next-generation sequencing (NGS) has been instrumental in advancing biological research and clinical diagnostics. To fully utilize the power of NGS, complete, uniform coverage of the entire genome is required. In this study, we identified the primary sources of bias observed in sequence coverage across AT-rich regions of the human genome with existing amplification-free DNA library preparation methods. We have found evidence that a major source of bias is the inefficient processing of AT-rich DNA in end repair and 3′ A-tailing, causing under-representation of extremely AT-rich regions. We have employed immobilized DNA modifying enzymes to catalyze end repair and 3′ A-tailing reactions, to notably reduce the GC bias observed with existing library construction methods.

Abstract 1041: XenofilteR: Computational dissection of mouse and human reads in PDX and xenograft sequence data

Abstract Mouse xenografts from (patient-derived) tumors (PDX) or tumor cell lines are widely used as models to study various biological and preclinical aspects of cancer. However, analysis of their RNA and DNA profiles is challenging, because they comprise reads not only from the grafted human cancer but also from the murine host. The reads of murine origin can result both in the generation of false positives in mutation analysis of DNA samples and obscure gene expression levels when sequencing RNA. Therefore, we developed the open-source R-package XenofilteR, which separates mouse from human sequence reads based on the number of discordant base pairs between each read and the reference genomes. To assess the accuracy of XenofilteR, we generated sequence data by in silico mixing of mouse and human whole genome and whole exome DNA sequence data. This analysis revealed that XenofilteR removes >99.9% of sequence reads of mouse origin while retaining sequence reads of human origin. The filtering allowed for mutation analysis of PDX samples with accurate variant allele frequencies, and retrieved all non-synonymous somatic mutations present in the original tumor. These findings were further validated in breast cancer and melanoma PDX samples, confirming the retrieval of accurate variant allele frequencies and somatic mutations. In conclusion, XenofilteR accurately dissects sequence reads from mouse and human origin in PDX sequence data, thereby outperforming currently available tools. Citation Format: Oscar Krijgsman, Roelof JC Kluin, Kristel Kemper, Thomas Kuilman, Julian R. de Ruiter, Vivek Iyer, Josep V. Forment, Paulien Cornelissen-Steijger, Iris de Rink, Petra ter Brugge, Ji-Ying Song, Sjoerd Klarenbeek, Ultan McDermott, Jos Jonkers, Arno Velds, David J. Adams, Daniel S. Peeper. XenofilteR: Computational dissection of mouse and human reads in PDX and xenograft sequence data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1041.

The Modeling and Analysis of Mechanisms for lncRNA Regulation

Long non-coding RNA- lncRNA is a class of RNA molecule that is found in eukaryotes with a length between 200-100000 nt and no long reading frame, but its structural features are similar to mRNA [1,2]. The achievements in the genomic research project show that in the human genome sequence only 1.5% of nucleic acid sequences are used for protein coding (Data from ENCODE research published in 2012 [3]), 98.5% of DNA sequence in human genome belongs to non-coding sequence, most of the non-coding sequence are transcribed into RNA which length is more than 200 bases so-called “long noncoding RNA”.

Omni-PolyA: a method and tool for accurate recognition of Poly(A) signals in human genomic DNA

BackgroundPolyadenylation is a critical stage of RNA processing during the formation of mature mRNA, and is present in most of the known eukaryote protein-coding transcripts and many long non-coding RNAs. The correct identification of poly(A) signals (PAS) not only helps to elucidate the 3′-end genomic boundaries of a transcribed DNA region and gene regulatory mechanisms but also gives insight into the multiple transcript isoforms resulting from alternative PAS. Although progress has been made in the in-silico prediction of genomic signals, the recognition of PAS in DNA genomic sequences remains a challenge.ResultsIn this study, we analyzed human genomic DNA sequences for the 12 most common PAS variants. Our analysis has identified a set of features that helps in the recognition of true PAS, which may be involved in the regulation of the polyadenylation process. The proposed features, in combination with a recognition model, resulted in a novel method and tool, Omni-PolyA. Omni-PolyA combines several machine learning techniques such as different classifiers in a tree-like decision structure and genetic algorithms for deriving a robust classification model. We performed a comparison between results obtained by state-of-the-art methods, deep neural networks, and Omni-PolyA. Results show that Omni-PolyA significantly reduced the average classification error rate by 35.37% in the prediction of the 12 considered PAS variants relative to the state-of-the-art results.ConclusionsThe results of our study demonstrate that Omni-PolyA is currently the most accurate model for the prediction of PAS in human and can serve as a useful complement to other PAS recognition methods. Omni-PolyA is publicly available as an online tool accessible at www.cbrc.kaust.edu.sa/omnipolya/.

Simplifying Nucleic Acid Amplification from Whole Blood with Direct Polymerase Chain Reaction on Chitosan Microparticles.

Tremendous advances have been made in the development of portable nucleic acid amplification devices for near-patient use. However, the true limitation in the realization of nucleic acid amplification tests (NAATs) for near-patient applications is not the amplification reaction, it is the complexity of the sample preparation. Conventional approaches require several precise intervention steps during the protocol. There are numerous reports in the literature that mimic the sample preparation procedure within a lab-on-a-chip device or cartridge, but these systems require a high number of integrated steps, making the devices and/or their supporting equipment too complex to meet the necessary cost targets and regulatory requirements for near-patient applications. Here we report a simplified method to purify and amplify DNA from complex samples in a minimal number of steps. We show that chitosan-coated microparticles can lyse human cells and capture the released DNA in a single mechanical agitation step, and we show that bound DNA can be amplified directly from the microparticle surface when the magnetic microparticles are transferred to a polymerase chain reaction (PCR). This procedure eliminates (i) the use of PCR-inhibiting reagents (e.g., chaotropic salts and alcohol) and (ii) the washing and elution steps that are required to remove these reagents and release DNA in typical NAAT sample preparation methods. To illustrate the use of this direct PCR method in diagnostics, we amplify human genomic DNA sequences from a ∼1 μL droplet of whole blood, and we amplify plasmid DNA spiked into whole blood droplets to represent circulating viral DNA or cell-free DNA. The qPCR threshold cycle for direct PCR from whole blood is comparable to that of direct PCR with purified DNA, demonstrating that the lysis and capture steps effectively bind DNA and sufficiently enable its amplification. Furthermore, the efficient amplification of plasmid DNA spiked into whole blood proves that the large mass of human genomic DNA captured from the lysed cells does not inhibit the capture and amplification of other circulating DNA. We anticipate that this new streamlined method for preparing DNA for amplification will expand the diagnostic applications of nucleic acid amplification tests, in particular for near-patient applications.

Targeting 24 bp within Telomere Repeat Sequences with Tandem Tetramer Pyrrole-Imidazole Polyamide Probes.

Synthetic molecules that bind sequence-specifically to DNA have been developed for varied biological applications, including anticancer activity, regulation of gene expression, and visualization of specific genomic regions. Increasing the number of base pairs targeted by synthetic molecules strengthens their sequence specificity. Our group has been working on the development of pyrrole-imidazole polyamides that bind to the minor groove of DNA in a sequence-specific manner without causing denaturation. Recently, we reported a simple synthetic method of fluorescent tandem dimer polyamide probes composed of two hairpin moieties with a linking hinge, which bound to 12 bp in human telomeric repeats (5'-(TTAGGG)n-3') and could be used to specifically visualize telomeres in chemically fixed cells under mild conditions. We also performed structural optimization and extension of the target base pairs to allow more specific staining of telomeres. In the present study, we synthesized tandem tetramer polyamides composed of four hairpin moieties, targeting 24 bp in telomeric repeats, the longest reported binding site for synthetic, non-nucleic-acid-based, sequence-specific DNA-binding molecules. The novel tandem tetramers bound with a nanomolar dissociation constant to 24 bp sequences made up of four telomeric repeats. Fluorescently labeled tandem tetramer polyamide probes could visualize human telomeres in chemically fixed cells with lower background signals than polyamide probes reported previously, suggesting that they had higher specificity for telomeres. Furthermore, high-throughput sequencing of human genomic DNA pulled down by the biotin-labeled tandem tetramer polyamide probe confirmed its effective binding to telomeric repeats in the complex chromatinized genome.

Isolation of Human Genomic DNA Sequences with Expanded Nucleobase Selectivity.

We report the direct isolation of user-defined DNA sequences from the human genome with programmable selectivity for both canonical and epigenetic nucleobases. This is enabled by the use of engineered transcription-activator-like effectors (TALEs) as DNA major groove-binding probes in affinity enrichment. The approach provides the direct quantification of 5-methylcytosine (5mC) levels at single genomic nucleotide positions in a strand-specific manner. We demonstrate the simple, multiplexed typing of a variety of epigenetic cancer biomarker 5mC with custom TALE mixes. Compared to antibodies as the most widely used affinity probes for 5mC analysis, i.e., employed in the methylated DNA immunoprecipitation (MeDIP) protocol, TALEs provide superior sensitivity, resolution and technical ease. We engineer a range of size-reduced TALE repeats and establish full selectivity profiles for their binding to all five human cytosine nucleobases. These provide insights into their nucleobase recognition mechanisms and reveal the ability of TALEs to isolate genomic target sequences with selectivity for single 5-hydroxymethylcytosine and, in combination with sodium borohydride reduction, single 5-formylcytosine nucleobases.

Spectrum of AGL mutations in Chinese patients with glycogen storage disease type III: identification of 31 novel mutations

Glycogen storage disease type III (GSD III), a rare autosomal recessive disease characterized by hepatomegaly, fasting hypoglycemia, growth retardation, progressive myopathy and cardiomyopathy, is caused by deficiency of the glycogen debranching enzyme (AGL). Direct sequencing of human AGL cDNA and genomic DNA has enabled analysis of the underlying genetic defects responsible for GSD III. To date, the frequent mutations in different areas and populations have been described in Italy, Japan, Faroe Islands and Mediterranean area, whereas little has been performed in Chinese population. Here we report a sequencing-based mutation analysis in 43 Chinese patients with GSD III from 41 families. We identified 51 different mutations, including 15 splice-site (29.4%), 11 small deletions (21.6%), 12 nonsense (23.5%), 7 missense (13.7%), 5 duplication (9.8%) and 1 complex deletion/insertion (2.0%), 31 of which are novel mutations. The most common mutation is c.1735+1G>T (11.5%). The association of AGL missense and small in-frame deletion mutations with normal creatine kinase level was observed. Our study extends the spectrum of AGL mutations and suggests a genotype-phenotype correlation in GSD III.

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.

Statistical methods in experimentation recommendation models for discovering gene regulation pathways

AbstractIn recent years, scientists and health professionals have become overwhelmed by the amount of genomic data available for epidemiological studies and patient care. In April 1996, the genome sequence of the yeast Saccharomyces cerevisiae was completed. By December 1999, the first plant's complete genome sequence from Arabidopsis thaliana was published. The Human Genome Project and Celera completed a working draft reference of the human genome DNA sequence in June 2000. Microarray and high throughput RNA sequence technology has opened a new era for gene expression studies. It enables us to measure the level of mRNA from different genes among different cells. Large microarray datasets provide opportunities to learn causal relationships among the genes, and compile in‐depth knowledge of physiology of different diseases. We have to deal with many issues to achieve this, including: Validity of the microarray and high throughput RNA sequence measurements; Experimental design of gene expression studies; Analysis of gene expression experimental results. For meaningful interpretation of experimental results, we need to start with a sound experimental design. However, not most of the statistical methods concentrate on issues related to gene expression data analyses. They do not take into consideration experimental design of microarray studies. The main topic of this article is review of modeling methods of the expected value of experimentation for discovering gene regulation pathways. In this article, we use experimentation as both interventions (e.g., an experiment with gene knock‐outs) and observations (e.g., passively observing the expression level of genes with no interventions). WIREs Comput Stat 2013, 5:121–134. doi: 10.1002/wics.1244This article is categorized under: Applications of Computational Statistics > Genomics/Proteomics/Genetics Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition

10IN - Initial Sequencing of Breast Cancer Genomes

ABSTRACT Over the last decade since the provision of the reference human genome DNA sequence, increasingly extensive sequence analyses of cancer genomes have led to the discovery of new mutated cancer genes and have explored the extant patterns of somatic mutation. The scope of these investigations has been constrained by sequence throughout and cost. However, the recent advent of novel sequencing technologies has ushered in a new era of cancer genome characterisation leading to partial or complete catalogues of somatic mutations in individual cancers. The combinations of mutated cancer genes and the mutational processes that are operative in the subclasses of breast cancer are becoming apparent. These studies are bringing new insights into the etiology, pathogenesis and classification of the genetically heterogeneous set of diseases that are collectively termed breast cancer. Disclosure The author has declared no conflicts of interest.

Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences

Motivation: Recognition of poly(A) signals in mRNA is relatively straightforward due to the presence of easily recognizable polyadenylic acid tail. However, the task of identifying poly(A) motifs in the primary genomic DNA sequence that correspond to poly(A) signals in mRNA is a far more challenging problem. Recognition of poly(A) signals is important for better gene annotation and understanding of the gene regulation mechanisms. In this work, we present one such poly(A) motif prediction method based on properties of human genomic DNA sequence surrounding a poly(A) motif. These properties include thermodynamic, physico-chemical and statistical characteristics. For predictions, we developed Artificial Neural Network and Random Forest models. These models are trained to recognize 12 most common poly(A) motifs in human DNA. Our predictors are available as a free web-based tool accessible at http://cbrc.kaust.edu.sa/dps. Compared with other reported predictors, our models achieve higher sensitivity and specificity and furthermore provide a consistent level of accuracy for 12 poly(A) motif variants.Contact: vladimir.bajic@kaust.edu.saSupplementary information: Supplementary data are available at Bioinformatics online.

The Genome-Wide Association Study—A New Era for Common Polygenic Disorders

This review covers the advances made in the last decade utilizing the high-density single-nucleotide microarrays to screen the entire human genome for genetic risk variants and outlines future strategies to draw deeper into the human genetic front. The sequence of the human genome provides the blueprint for life, while its variation provides the spice of life. Approximately 99.5% of the human genome DNA sequence is identical among humans with 0.5% of the genome sequence (15 million bps) accounting for all individual differences including susceptibility for disease. The new technology of the computerized chip array containing up to millions of SNPs as DNA markers makes possible genome-wide association studies to detect genetic predisposition to common polygenic disorders such as coronary artery disease (CAD). The sample sizes required for these studies are massive and large; worldwide consortiums such as CARDIoGRAM have been formed to accommodate this requirement. The progress has been remarkable with the identification of 9p21 followed by several others within the past 2 years. It is expected that most of the common variants (minor allele frequency, MAF >5%) will be identified for CAD within the next 2 to 3 years. Rare variants (MAF <5%) will require direct sequencing which will be delayed somewhat. The ultimate objective for the future is the sequencing and functional analysis of the causative polymorphisms. This will require a new approach involving several disciplines, namely, bioinformatics, high-throughput cell expression, and animal models.

Computation of Rank and Select Functions on Hierarchical Binary String and Its Application to Genome Mapping Problems for Short-Read DNA Sequences

Abstract We have developed efficient in-practice algorithms for computing rank and select functions on a binary string, based on a novel data structure, a hierarchical binary string with hierarchical accumulatives. It efficiently stores decomposed information on partial summations over various scales of subregions of a given binary string, so that the required space overhead ratio is only about 3.5% irrespective of the string length. Values of rank and select functions are computed hierarchically in [(log(2)n)/8] iterations, where n is the string length. For example, for an unbiased random binary string of 64 G bits, each value of these functions can be computed in about a microsecond, on average, on a single 3.0-GHz CPU using 8+ GB of memory. We also present their applications to genome mapping problems for large-scale short-read DNA sequence data, especially produced by ultra-high-throughput new-generation DNA sequencers. The algorithms are applied to the binarization of the Burrows-Wheeler transform of the human genome DNA sequence. For the sake of high-speed performance, we adopted a somewhat stringent mapping condition that allows at most a single-base mismatch (either a substitution, insertion, or deletion of a single base) per query sequence. An experimentally implemented program mapped several thousands of sequences per second on a single 3.0-GHz CPU, several times faster than ELAND, a widely used mapping program with the Illumina-Solexa 1G analyser.

Cover Picture: Proteomics 22'09

AbstractShigellosis, dysentery — by whatever name — Don't kiss the chimpsWith a 10–15% mortality rate when untreated in young children and immunedeficient patients, over one million deaths per year are attributable to this primate/human‐only disease. Furthermore, the Shigella spp. have developed resistance to b‐lactam, tetracycline, and aminoglycoside antibiotics very rapidly. A non‐primate model of the disease is based on gnotobiotic piglets. Aerobically grown bacteria shift to anaerobic metabolism when introduced into the GI tract of the piglets. Pieper et al. examined the aerobic and anaerobic proteomes using differential display methodology on 2‐D gels. Over 1050 separate gene products were identified. Bacterial defense genes and secretion system genes were among the types found. Novel proteins that might be targets for vaccines or drugs were also identified (OmpA, HtpG, and OspC2).Pieper, R. et al., Proteomics 2009, 9, 5029–5045.Form follow/leads functions? Essentiality, centrality and network topologyWho ever thought eight or ten years ago that we would be learning network‐speak to keep up with contemporary molecular and cell biology? Collaborating with mathematicians and physicists? Raise your hand. As I thought, not many. With the completion of the human genome DNA sequence it became clear that the sequence did not code for enough proteins to account for the complexity of life. At least two sources of complexity have been discovered to date: post‐translational modification and protein–protein interaction networks (PPINs). The structure of PPINs is examined in this work from Park et al., who raise the question (in Facebook terms): does popularity correlate with importance? They used two yeast PPINs to see how well centrality correlated with essentiality and found that, using 40 measures of centrality, the relationship was close for path‐based localized information centrality and gene essentiality. They found that random forest classifiers can work, too.Park, K. et al., Proteomics 2009, 9, 5143–5154.Standing on the shoulders of the great: Telomerase proteomicsIn those early days of molecular biology, when all “model replication systems” (bacteria and phages) went through circular intermediates, we did not need to worry about linear ends. Then we came to the end of the world, the end of the linear chromosome. Elizabeth Blackburn, Carol Greider, and Jack Szostak worked out the mechanics and enzymology of faithful replication of those linear ends and for that work received the 2009 Nobel Prize in physiology and medicine. Now researchers such as Zimmermann et al. can apply the tools of proteomics to tease apart the subtleties of telomere control of and control by other proteins. These researchers demonstrate the utility of SELDI MS/MS to examine the changes in specific cell fractions upon up‐ or down‐expression of telomere regulatory components. They confirmed several observations and found a new role for S100A6 (AKA “calcyclin”) in cell response to telomere dysfunction.Zimmermann, S. et al., Proteomics 2009, 9, 5175–5187.

Human urinary kallikrein. Complete amino acid sequence and sites of glycosylation.

Human glandular kallikrein was purified from urine and subjected to detailed structural characterization. The protein was carboxymethylated with iodoacetic acid and digested with TPCK-trypsin, Staphylococcal aureus V-8 protease and endo LysC peptidase. The resulting peptide fragments were separated by reverse-phase HPLC using C-4 columns and acetonitrile-trifluoroacetic acid gradient elution. The complete amino acid sequence of the carboxymethylated derivative was elucidated by sequence analysis and alignment of peptides derived from different proteolytic cleavages. A procedure using in situ CNBr cleavage of a large endo LysC peptidase-derived peptide followed by direct sequencing was carried out to provide overlap for two glycosylation sites at residues 78 and 84. Three Asn-linked glycosylation sites were confirmed by the direct sequence analysis of the isolated glycopeptides. However, the third glycosylation at Asn-144 occurs only in 60% of kallikrein molecules. Reverse-phase HPLC effectively separates two species of HUK which correspond to molecules glycosylated and non-glycosylated at Asn-144, respectively. The human urinary kallikrein contains 238 amino acid residues with Ile and Ser as N- and C-terminal amino acids, respectively. The primary structure is completely identical to that deduced from a human genomic DNA sequence (F.K. Lin et al., manuscript in preparation) and is different in one amino acid (Lys-162 vs. Glu-162) from that deduced from pancreatic or kidney cDNA sequence.

Exaptation of an ancient Alu short interspersed element provides a highly conserved vitamin D-mediated innate immune response in humans and primates.

BackgroundAbout 45% of the human genome is comprised of mobile transposable elements or "junk DNA". The exaptation or co-option of these elements to provide important cellular functions is hypothesized to have played a powerful force in evolution; however, proven examples are rare. An ancient primate-specific Alu short interspersed element (SINE) put the human CAMP gene under the regulation of the vitamin D pathway by providing a perfect vitamin D receptor binding element (VDRE) in its promoter. Subsequent studies demonstrated that the vitamin D-cathelicidin pathway may be a key component of a novel innate immune response of human to infection. The lack of evolutionary conservation in non-primate mammals suggested that this is a primate-specific adaptation. Evidence for evolutionary conservation of this regulation in additional primate lineages would provide strong evidence that the TLR2/1-vitamin D-cathelicidin pathway evolved as a biologically important immune response mechanism protecting human and non-human primates against infection.ResultsPCR-based amplification of the Alu SINE from human and non-human primate genomic DNA and subsequent sequence analysis, revealed perfect structural conservation of the VDRE in all primates examined. Reporter gene studies and induction of the endogenous CAMP gene in Rhesus macaque peripheral blood mononuclear cells demonstrated that the VDREs were conserved functionally. In addition, New World monkeys (NWMs) have maintained additional, functional steroid-hormone receptor binding sites in the AluSx SINE that confer retinoic acid responsiveness and provide potential thyroid hormone receptor binding sites. These sites were less well-conserved during human, ape and Old World monkey (OWM) evolution and the human CAMP gene does not respond to either retinoic acid or thyroid hormone.ConclusionWe demonstrated that the VDRE in the CAMP gene originated from the exaptation of an AluSx SINE in the lineage leading to humans, apes, OWMs and NWMs and remained under purifying selection for the last 55–60 million years. We present convincing evidence of an evolutionarily fixed, Alu-mediated divergence in steroid hormone nuclear receptor gene regulation between humans/primates and other mammals. Evolutionary selection to place the primate CAMP gene under regulation of the vitamin D pathway potentiates the innate immune response and may counter the anti-inflammatory properties of vitamin D.

Human Replication Protein A Melts a DNA Triple Helix Structure in a Potent and Specific Manner

Alternate DNA structures other than double-stranded B-form DNA can potentially impede cellular processes such as transcription and replication. The DNA triplex helix and G4 tetraplex structures that form by Hoogsteen hydrogen bonding are two examples of alternate DNA structures that can be a source of genomic instability. In this study, we have examined the ability of human replication protein A (RPA), a single-stranded DNA binding protein that is implicated in all facets of DNA metabolism, to destabilize DNA triplexes and tetraplexes. Biochemical studies demonstrate that RPA efficiently melts an intermolecular DNA triple helix consisting of a pyrimidine motif third strand annealed to a 4 kb duplex DNA fragment at protein concentrations equimolar to the triplex substrate. Heterologous single-stranded DNA binding proteins ( Escherichia coli SSB, T4 gene 32) melt the triplex substrate very poorly or not at all, suggesting that the triplex destabilizing effect of RPA is specific. In contrast to the robust activity on DNA triplexes, RPA does not melt intermolecular G4 tetraplex structures. Cellular assays demonstrated increased triplex DNA content when RPA is transiently repressed, suggesting that RPA melting of triple helical structures is physiologically important. On the basis of our results, we suggest that the abundance of RPA known to exist in vivo is likely to be a strong deterrent to the stability of triplexes that can potentially form from human genomic DNA sequences.

EnsemPro: An ensemble approach to predicting transcription start sites in human genomic DNA sequences

Although several computational methods have been developed to identify transcription start sites (TSSs)/promoters, the computational prediction still needs improvement. Due to low performance, the promoter prediction programs can provide misleading results in functional genomic studies. To improve the prediction accuracy, we propose the use of an ensemble approach, EnsemPro (Ensemble Promoter), which combines the prediction results of the existing promoter predictors. We schematically compared the prediction performance of the currently available promoter prediction programs in an identical evaluating environment, and the results served as a guide for choosing the combined predictors. We applied three representative ensemble schemes—the majority voting, the weighted voting, and the Bayesian approach—for the TSS prediction of hundreds of human genomic sequences. EnsemPro identified the TSSs more precisely than other combining methods as well as the currently available individual predictor programs. The source code of EnsemPro is available on request from the authors.