ALBERT

Description: DNA methylation is a mechanism for long-term transcriptional regulation and is required for normal cellular differentiation. Failure to properly establish or maintain DNA methylation patterns leads to cell dysfunction and diseases such as cancer. Identifying DNA methylation signatures in complex tissues can be challenging owing to inaccurate cell enrichment methods and low DNA yields. We have developed a technique called laser capture microdissection-reduced representation bisulfite sequencing (LCM-RRBS) for the multiplexed interrogation of the DNA methylation status of cytosine–guanine dinucleotide islands and promoters. LCM-RRBS accurately and reproducibly profiles genome-wide methylation of DNA extracted from microdissected fresh frozen or formalin-fixed paraffin-embedded tissue samples. To demonstrate the utility of LCM-RRBS, we characterized changes in DNA methylation associated with gonadectomy-induced adrenocortical neoplasia in the mouse. Compared with adjacent normal tissue, the adrenocortical tumors showed reproducible gains and losses of DNA methylation at genes involved in cell differentiation and organ development. LCM-RRBS is a rapid, cost-effective, and sensitive technique for analyzing DNA methylation in heterogeneous tissues and will facilitate the investigation of DNA methylation in cancer and organ development.

Description: DNA repair helicases function in the cell to separate DNA duplexes or remodel nucleoprotein complexes. These functions are influenced by sensing and signaling; the cellular pool of a DNA helicase may contain subpopulations of enzymes carrying different post-translational modifications and performing distinct biochemical functions. Here, we report a novel experimental strategy, single-molecule sorting, which overcomes difficulties associated with comprehensive analysis of heterologously modified pool of proteins. This methodology was applied to visualize human DNA helicase F-box–containing DNA helicase (FBH1) acting on the DNA structures resembling a stalled or collapsed replication fork and its interactions with RAD51 nucleoprotein filament. Individual helicase molecules isolated from human cells with their native post-translational modifications were analyzed using total internal reflection fluorescence microscopy. Separation of the activity trajectories originated from ubiquitylated and non-ubiquitylated FBH1 molecules revealed that ubiquitylation affects FBH1 interaction with the RAD51 nucleoprotein filament, but not its translocase and helicase activities.

Description: The advent in high-throughput-sequencing (HTS) technologies has revolutionized conventional biodiversity research by enabling parallel capture of DNA sequences possessing species-level diagnosis. However, polymerase chain reaction (PCR)-based implementation is biased by the efficiency of primer binding across lineages of organisms. A PCR-free HTS approach will alleviate this artefact and significantly improve upon the multi-locus method utilizing full mitogenomes. Here we developed a novel multiplex sequencing and assembly pipeline allowing for simultaneous acquisition of full mitogenomes from pooled animals without DNA enrichment or amplification. By concatenating assemblies from three de novo assemblers, we obtained high-quality mitogenomes for all 49 pooled taxa, with 36 species 〉15 kb and the remaining 〉10 kb, including 20 complete mitogenomes and nearly all protein coding genes (99.6%). The assembly quality was carefully validated with Sanger sequences, reference genomes and conservativeness of protein coding genes across taxa. The new method was effective even for closely related taxa, e.g. three Drosophila spp., demonstrating its broad utility for biodiversity research and mito-phylogenomics. Finally, the in silico simulation showed that by recruiting multiple mito-loci, taxon detection was improved at a fixed sequencing depth. Combined, these results demonstrate the plausibility of a multi-locus mito-metagenomics approach as the next phase of the current single-locus metabarcoding method.

Description: Chromatin modifiers and histone modifications are components of a chromatin-signaling network involved in transcription and its regulation. The interactions between chromatin modifiers and histone modifications are often unknown, are based on the analysis of few genes or are studied in vitro . Here, we apply computational methods to recover interactions between chromatin modifiers and histone modifications from genome-wide ChIP-Seq data. These interactions provide a high-confidence backbone of the chromatin-signaling network. Many recovered interactions have literature support; others provide hypotheses about yet unknown interactions. We experimentally verified two of these predicted interactions, leading to a link between H4K20me1 and members of the Polycomb Repressive Complexes 1 and 2. Our results suggest that our computationally derived interactions are likely to lead to novel biological insights required to establish the connectivity of the chromatin-signaling network involved in transcription and its regulation.

Description: The Differential Radial Capillary Action of Ligand Assay (DRaCALA) allows detection of protein interactions with low-molecular weight ligands based on separation of the protein–ligand complex by differential capillary action. Here, we present an application of DRaCALA to the study of nucleic acid–protein interactions using the Escherichia coli cyclic AMP receptor protein (CRP). CRP bound in DRaCALA specifically to 32 P-labeled oligonucleotides containing the consensus CRP binding site, but not to oligonucleotides with point mutations known to abrogate binding. Affinity and kinetic studies using DRaCALA yielded a dissociation constant and dissociation rate similar to previously reported values. Because DRaCALA is not subject to ligand size restrictions, whole plasmids with a single CRP-binding site were used as probes, yielding similar results. DNA can also function as an easily labeled carrier molecule for a conjugated ligand. Sequestration of biotinylated nucleic acids by streptavidin allowed nucleic acids to take the place of the protein as the immobile binding partner. Therefore, any molecular interactions involving nucleic acids can be tested. We demonstrate this principle utilizing a bacterial riboswitch that binds cyclic-di-guanosine monophosphate. DRaCALA is a flexible and complementary approach to other biochemical methods for rapid and accurate measurements of affinity and kinetics at near-equilibrium conditions.

Description: X-ray crystallography provides excellent structural data on protein–DNA interfaces, but crystallographic complexes typically contain only small fragments of large DNA molecules. We present a new approach that can use longer DNA substrates and reveal new protein–DNA interactions even in extensively studied systems. Our approach combines rigid-body computational docking with hydrogen/deuterium exchange mass spectrometry (DXMS). DXMS identifies solvent-exposed protein surfaces; docking is used to create a 3-dimensional model of the protein–DNA interaction. We investigated the enzyme uracil-DNA glycosylase (UNG), which detects and cleaves uracil from DNA. UNG was incubated with a 30 bp DNA fragment containing a single uracil, giving the complex with the abasic DNA product. Compared with free UNG, the UNG–DNA complex showed increased solvent protection at the UNG active site and at two regions outside the active site: residues 210–220 and 251–264. Computational docking also identified these two DNA-binding surfaces, but neither shows DNA contact in UNG–DNA crystallographic structures. Our results can be explained by separation of the two DNA strands on one side of the active site. These non-sequence-specific DNA-binding surfaces may aid local uracil search, contribute to binding the abasic DNA product and help present the DNA product to APE-1, the next enzyme on the DNA-repair pathway.

Description: Tethered particle motion (TPM) monitors the variations in the effective length of a single DNA molecule by tracking the Brownian motion of a bead tethered to a support by the DNA molecule. Providing information about DNA conformations in real time, this technique enables a refined characterization of DNA–protein interactions. To increase the output of this powerful but time-consuming single-molecule assay, we have developed a biochip for the simultaneous acquisition of data from more than 500 single DNA molecules. The controlled positioning of individual DNA molecules is achieved by self-assembly on nanoscale arrays fabricated through a standard microcontact printing method. We demonstrate the capacity of our biochip to study biological processes by applying our method to explore the enzymatic activity of the T7 bacteriophage exonuclease. Our single molecule observations shed new light on its behaviour that had only been examined in bulk assays previously and, more specifically, on its processivity.

Description: Nuclear receptors (NRs) regulate gene expression by binding specific DNA sequences consisting of AG[G/T]TCA or AGAACA half site motifs in a variety of configurations. However, those motifs/configurations alone do not adequately explain the diversity of NR function in vivo . Here, a systematic examination of DNA binding specificity by protein-binding microarrays (PBMs) of three closely related human NRs—HNF4α, retinoid X receptor alpha (RXRα) and COUPTF2—reveals an HNF4-specific binding motif (H4-SBM), xxxxCAAAGTCCA, as well as a previously unrecognized polarity in the classical DR1 motif (AGGTCAxAGGTCA) for HNF4α, RXRα and COUPTF2 homodimers. ChIP-seq data indicate that the H4-SBM is uniquely bound by HNF4α but not 10 other NRs in vivo , while NRs PXR, FXRα, Rev-Erbα appear to bind adjacent to H4-SBMs. HNF4-specific DNA recognition and transactivation are mediated by residues Asp69 and Arg76 in the DNA-binding domain; this combination of amino acids is unique to HNF4 among all human NRs. Expression profiling and ChIP data predict ~100 new human HNF4α target genes with an H4-SBM site, including several Co-enzyme A-related genes and genes with links to disease. These results provide important new insights into NR DNA binding.

Description: Identity by descent (IBD) can be reliably detected for long shared DNA segments, which are found in related individuals. However, many studies contain cohorts of unrelated individuals that share only short IBD segments. New sequencing technologies facilitate identification of short IBD segments through rare variants, which convey more information on IBD than common variants. Current IBD detection methods, however, are not designed to use rare variants for the detection of short IBD segments. Short IBD segments reveal genetic structures at high resolution. Therefore, they can help to improve imputation and phasing, to increase genotyping accuracy for low-coverage sequencing and to increase the power of association studies. Since short IBD segments are further assumed to be old, they can shed light on the evolutionary history of humans. We propose HapFABIA, a computational method that applies biclustering to identify very short IBD segments characterized by rare variants. HapFABIA is designed to detect short IBD segments in genotype data that were obtained from next-generation sequencing, but can also be applied to DNA microarray data. Especially in next-generation sequencing data, HapFABIA exploits rare variants for IBD detection. HapFABIA significantly outperformed competing algorithms at detecting short IBD segments on artificial and simulated data with rare variants. HapFABIA identified 160 588 different short IBD segments characterized by rare variants with a median length of 23 kb (mean 24 kb) in data for chromosome 1 of the 1000 Genomes Project. These short IBD segments contain 752 000 single nucleotide variants (SNVs), which account for 39% of the rare variants and 23.5% of all variants. The vast majority—152 000 IBD segments—are shared by Africans, while only 19 000 and 11 000 are shared by Europeans and Asians, respectively. IBD segments that match the Denisova or the Neandertal genome are found significantly more often in Asians and Europeans but also, in some cases exclusively, in Africans. The lengths of IBD segments and their sharing between continental populations indicate that many short IBD segments from chromosome 1 existed before humans migrated out of Africa. Thus, rare variants that tag these short IBD segments predate human migration from Africa. The software package HapFABIA is available from Bioconductor. All data sets, result files and programs for data simulation, preprocessing and evaluation are supplied at http://www.bioinf.jku.at/research/short-IBD .

Description: Glioma is the most common and fatal primary brain tumour with poor prognosis; however, the functional roles of miRNAs in glioma malignant progression are insufficiently understood. Here, we used an integrated approach to identify miRNA functional targets during glioma malignant progression by combining the paired expression profiles of miRNAs and mRNAs across 160 Chinese glioma patients, and further constructed the functional miRNA–mRNA regulatory network. As a result, most tumour-suppressive miRNAs in glioma progression were newly discovered, whose functions were widely involved in gliomagenesis. Moreover, three miRNA signatures, with different combinations of hub miRNAs (regulations≥30) were constructed, which could independently predict the survival of patients with all gliomas, high-grade glioma and glioblastoma. Our network-based method increased the ability to identify the prognostic biomarkers, when compared with the traditional method and random conditions. Hsa-miR-524-5p and hsa-miR-628-5p, shared by these three signatures, acted as protective factors and their expression decreased gradually during glioma progression. Functional analysis of these miRNA signatures highlighted their critical roles in cell cycle and cell proliferation in glioblastoma malignant progression, especially hsa-miR-524-5p and hsa-miR-628-5p exhibited dominant regulatory activities. Therefore, network-based biomarkers are expected to be more effective and provide deep insights into the molecular mechanism of glioma malignant progression.

Description: Understanding gene regulation is a key challenge in today's biology. The new technologies of protein-binding microarrays (PBMs) and high-throughput SELEX (HT-SELEX) allow measurement of the binding intensities of one transcription factor (TF) to numerous synthetic double-stranded DNA sequences in a single experiment. Recently, Jolma et al. reported the results of 547 HT-SELEX experiments covering human and mouse TFs. Because 162 of these TFs were also covered by PBM technology, for the first time, a large-scale comparison between implementations of these two in vitro technologies is possible. Here we assessed the similarities and differences between binding models, represented as position weight matrices, inferred from PBM and HT-SELEX, and also measured how well these models predict in vivo binding. Our results show that HT-SELEX- and PBM-derived models agree for most TFs. For some TFs, the HT-SELEX-derived models are longer versions of the PBM-derived models, whereas for other TFs, the HT-SELEX models match the secondary PBM-derived models. Remarkably, PBM-based 8-mer ranking is more accurate than that of HT-SELEX, but models derived from HT-SELEX predict in vivo binding better. In addition, we reveal several biases in HT-SELEX data including nucleotide frequency bias, enrichment of C-rich k-mers and oligos and underrepresentation of palindromes.

Description: A major challenge in cancer genomics is uncovering genes with an active role in tumorigenesis from a potentially large pool of mutated genes across patient samples. Here we focus on the interactions that proteins make with nucleic acids, small molecules, ions and peptides, and show that residues within proteins that are involved in these interactions are more frequently affected by mutations observed in large-scale cancer genomic data than are other residues. We leverage this observation to predict genes that play a functionally important role in cancers by introducing a computational pipeline ( http://canbind.princeton.edu ) for mapping large-scale cancer exome data across patients onto protein structures, and automatically extracting proteins with an enriched number of mutations affecting their nucleic acid, small molecule, ion or peptide binding sites. Using this computational approach, we show that many previously known genes implicated in cancers are enriched in mutations within the binding sites of their encoded proteins. By focusing on functionally relevant portions of proteins—specifically those known to be involved in molecular interactions—our approach is particularly well suited to detect infrequent mutations that may nonetheless be important in cancer, and should aid in expanding our functional understanding of the genomic landscape of cancer.

Description: Genome duplication with hybridization, or allopolyploidization, occurs commonly in plants, and is considered to be a strong force for generating new species. However, genome-wide quantification of homeolog expression ratios was technically hindered because of the high homology between homeologous gene pairs. To quantify the homeolog expression ratio using RNA-seq obtained from polyploids, a new method named HomeoRoq was developed, in which the genomic origin of sequencing reads was estimated using mismatches between the read and each parental genome. To verify this method, we first assembled the two diploid parental genomes of Arabidopsis halleri subsp. gemmifera and Arabidopsis lyrata subsp. petraea ( Arabidopsis petraea subsp. umbrosa ), then generated a synthetic allotetraploid, mimicking the natural allopolyploid Arabidopsis kamchatica . The quantified ratios corresponded well to those obtained by Pyrosequencing. We found that the ratios of homeologs before and after cold stress treatment were highly correlated ( r = 0.870). This highlights the presence of nonstochastic polyploid gene regulation despite previous research identifying stochastic variation in expression. Moreover, our new statistical test incorporating overdispersion identified 226 homeologs (1.11% of 20 369 expressed homeologs) with significant ratio changes, many of which were related to stress responses. HomeoRoq would contribute to the study of the genes responsible for polyploid-specific environmental responses.

Description: Ribosome assembly in eukaryotes involves the activity of hundreds of assembly factors that direct the hierarchical assembly of ribosomal proteins and numerous ribosomal RNA folding steps. However, detailed insights into the function of assembly factors and ribosomal RNA folding events are lacking. To address this, we have developed ChemModSeq, a method that combines structure probing, high-throughput sequencing and statistical modeling, to quantitatively measure RNA structural rearrangements during the assembly of macromolecular complexes. By applying ChemModSeq to purified 40S assembly intermediates we obtained nucleotide-resolution maps of ribosomal RNA flexibility revealing structurally distinct assembly intermediates and mechanistic insights into assembly dynamics not readily observed in cryo-electron microscopy reconstructions. We show that RNA restructuring events coincide with the release of assembly factors and predict that completion of the head domain is required before the Rio1 kinase enters the assembly pathway. Collectively, our results suggest that 40S assembly factors regulate the timely incorporation of ribosomal proteins by delaying specific folding steps in the 3' major domain of the 20S pre-ribosomal RNA.

Description: High-throughput sequencing was previously applied to phage-selected peptides in order to gain insight into the abundance and diversity of isolated peptides. Herein we developed a procedure to efficiently compare the sequences of large numbers of phage-selected peptides for the purpose of identifying target-binding peptide motifs. We applied the procedure to analyze bicyclic peptides isolated against five different protein targets: sortase A, urokinase-type plasminogen activator, coagulation factor XII, plasma kallikrein and streptavidin. We optimized sequence data filters to reduce biases originating from the sequencing method and developed sequence correction algorithms to prevent identification of false consensus motifs. With our strategy, we were able to identify rare target-binding peptide motifs, as well as to define more precisely consensus sequences and sub-groups of consensus sequences. This information is valuable to choose peptide leads for drug development and it facilitates identification of epitopes. We furthermore show that binding motifs can be identified after a single round of phage selection. Such a selection regimen reduces propagation-related bias and may facilitate application of phage display in non-specialized laboratories, as procedures such as bacterial infection, phage propagation and purification are not required.

Description: Enriching target sequences in sequencing libraries via capture hybridization to bait/probes is an efficient means of leveraging the capabilities of next-generation sequencing for obtaining sequence data from target regions of interest. However, homologous sequences from non-target regions may also be enriched by such methods. Here we investigate the fidelity of capture enrichment for complete mitochondrial DNA (mtDNA) genome sequencing by analyzing sequence data for nuclear copies of mtDNA (NUMTs). Using capture-enriched sequencing data from a mitochondria-free cell line and the parental cell line, and from samples previously sequenced from long-range PCR products, we demonstrate that NUMT alleles are indeed present in capture-enriched sequence data, but at low enough levels to not influence calling the authentic mtDNA genome sequence. However, distinguishing NUMT alleles from true low-level mutations (e.g. heteroplasmy) is more challenging. We develop here a computational method to distinguish NUMT alleles from heteroplasmies, using sequence data from artificial mixtures to optimize the method.

Description: Single nucleotide polymorphisms (SNPs) are increasingly used to tag genetic loci associated with phenotypes such as risk of complex diseases. Technically, this is done genome-wide without prior restriction or knowledge of biological feasibility in scans referred to as genome-wide association studies (GWAS). Depending on the linkage disequilibrium (LD) structure at a particular locus, such tagSNPs may be surrogates for many thousands of other SNPs, and it is difficult to distinguish those that may play a functional role in the phenotype from those simply genetically linked. Because a large proportion of tagSNPs have been identified within non-coding regions of the genome, distinguishing functional from non-functional SNPs has been an even greater challenge. A strategy was recently proposed that prioritizes surrogate SNPs based on non-coding chromatin and epigenomic mapping techniques that have become feasible with the advent of massively parallel sequencing. Here, we introduce an R/Bioconductor software package that enables the identification of candidate functional SNPs by integrating information from tagSNP locations, lists of linked SNPs from the 1000 genomes project and locations of chromatin features which may have functional significance. Availability: FunciSNP is available from Bioconductor (bioconductor.org).

Description: Reconstructing the evolutionary relationships of species is a major goal in biology. Despite the increasing number of completely sequenced genomes, a large number of phylogenetic projects rely on targeted sequencing and analysis of a relatively small sample of marker genes. The selection of these phylogenetic markers should ideally be based on accurate predictions of their combined, rather than individual, potential to accurately resolve the phylogeny of interest. Here we present and validate a new phylogenomics strategy to efficiently select a minimal set of stable markers able to reconstruct the underlying species phylogeny. In contrast to previous approaches, our methodology does not only rely on the ability of individual genes to reconstruct a known phylogeny, but it also explores the combined power of sets of concatenated genes to accurately infer phylogenetic relationships of species not previously analyzed. We applied our approach to two broad sets of cyanobacterial and ascomycetous fungal species, and provide two minimal sets of six and four genes, respectively, necessary to fully resolve the target phylogenies. This approach paves the way for the informed selection of phylogenetic markers in the effort of reconstructing the tree of life.

Description: We demonstrate a single DNA molecule optical mapping assay able to resolve a specific Escherichia coli strain from other strains. The assay is based on competitive binding of the fluorescent dye YOYO-1 and the AT-specific antibiotic netropsin. The optical map is visualized by stretching the DNA molecules in nanofluidic channels. We optimize the experimental conditions to obtain reproducible barcodes containing as much information as possible. We implement a multi-ligand transfer matrix method for calculating theoretical barcodes from known DNA sequences. Our method extends previous theoretical approaches for competitive binding of two types of ligands to many types of ligands and introduces a recursive approach that allows long barcodes to be calculated with standard computer floating point formats. The identification of a specific E . coli strain (CCUG 10979) is based on mapping of 50–160 kilobasepair experimental DNA fragments onto the theoretical genome using the developed theory. Our identification protocol introduces two theoretical constructs: a P -value for a best experiment-theory match and an information score threshold. The developed methods provide a novel optical mapping toolbox for identification of bacterial species and strains. The protocol does not require cultivation of bacteria or DNA amplification, which allows for ultra-fast identification of bacterial pathogens.

Description: Increasing awareness of the importance of protein–RNA interactions has motivated many approaches to predict residue-level RNA binding sites in proteins based on sequence or structural characteristics. Sequence-based predictors are usually high in sensitivity but low in specificity; conversely structure-based predictors tend to have high specificity, but lower sensitivity. Here we quantified the contribution of both sequence- and structure-based features as indicators of RNA-binding propensity using a machine-learning approach. In order to capture structural information for proteins without a known structure, we used homology modeling to extract the relevant structural features. Several novel and modified features enhanced the accuracy of residue-level RNA-binding propensity beyond what has been reported previously, including by meta-prediction servers. These features include: hidden Markov model-based evolutionary conservation, surface deformations based on the Laplacian norm formalism, and relative solvent accessibility partitioned into backbone and side chain contributions. We constructed a web server called aaRNA that implements the proposed method and demonstrate its use in identifying putative RNA binding sites.

Description: Spontaneous deamination of DNA is mutagenic, if it is not repaired by the base excision repair (BER) pathway. Crystallographic data suggest that each BER enzyme has a compact DNA binding site. However, these structures lack information about poorly ordered termini, and the energetic contributions of specific protein–DNA contacts cannot be inferred. Furthermore, these structures do not reveal how DNA repair intermediates are passed between enzyme active sites. We used a functional footprinting approach to define the binding sites of the first two enzymes of the human BER pathway for the repair of deaminated purines, alkyladenine DNA glycosylase (AAG) and AP endonuclease (APE1). Although the functional footprint for full-length AAG is explained by crystal structures of truncated AAG, the footprint for full-length APE1 indicates a much larger binding site than is observed in crystal structures. AAG turnover is stimulated in the presence of APE1, indicating rapid exchange of AAG and APE1 at the abasic site produced by the AAG reaction. The coordinated reaction does not require an extended footprint, suggesting that each enzyme engages the site independently. Functional footprinting provides unique information relative to traditional footprinting approaches and is generally applicable to any DNA modifying enzyme or system of enzymes.

Description: Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33 684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO 2 . Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges.

Description: Due to dramatic advances in DNA technology, quantitative measures of annotation data can now be obtained in continuous coordinates across the entire genome, allowing various heterogeneous ‘genomic landscapes’ to emerge. Although much effort has been devoted to comparing DNA sequences, not much attention has been given to comparing these large quantities of data comprehensively. In this article, we introduce a method for rapidly detecting local regions that show high correlations between genomic landscapes. We overcame the size problem for genome-wide data by converting the data into series of symbols and then carrying out sequence alignment. We also decomposed the oscillation of the landscape data into different frequency bands before analysis, since the real genomic landscape is a mixture of embedded and confounded biological processes working at different scales in the cell nucleus. To verify the usefulness and generality of our method, we applied our approach to well investigated landscapes from the human genome, including several histone modifications. Furthermore, by applying our method to over 20 genomic landscapes in human and 12 in mouse, we found that DNA replication timing and the density of Alu insertions are highly correlated genome-wide in both species, even though the Alu elements have amplified independently in the two genomes. To our knowledge, this is the first method to align genomic landscapes at multiple scales according to their shape.

Description: The numerous discovered cases of domesticated transposable element (TE) proteins led to the recognition that TEs are a significant source of evolutionary innovation. However, much less is known about the reverse process, whether and to what degree the evolution of TEs is influenced by the genome of their hosts. We addressed this issue by searching for cases of incorporation of host genes into the sequence of TEs and examined the systems-level properties of these genes using the Saccharomyces cerevisiae and Drosophila melanogaster genomes. We identified 51 cases where the evolutionary scenario was the incorporation of a host gene fragment into a TE consensus sequence, and we show that both the yeast and fly homologues of the incorporated protein sequences have central positions in the cellular networks. An analysis of selective pressure (Ka/Ks ratio) detected significant selection in 37% of the cases. Recent research on retrovirus-host interactions shows that virus proteins preferentially target hubs of the host interaction networks enabling them to take over the host cell using only a few proteins. We propose that TEs face a similar evolutionary pressure to evolve proteins with high interacting capacities and take some of the necessary protein domains directly from their hosts.

Description: Enzymes that form transient DNA–protein covalent complexes are targets for several potent classes of drugs used to treat infectious disease and cancer, making it important to establish robust and rapid procedures for analysis of these complexes. We report a method for isolation of DNA–protein adducts and their identification and quantification, using techniques compatible with high-throughput screening. This method is based on the RADAR assay for DNA adducts that we previously developed (Kiianitsa and Maizels (2013) A rapid and sensitive assay for DNA–protein covalent complexes in living cells. Nucleic Acids Res. , 41:e104), but incorporates three key new steps of broad applicability. (i) Silica-assisted ethanol/isopropanol precipitation ensures reproducible and efficient recovery of DNA and DNA–protein adducts at low centrifugal forces, enabling cell culture and DNA precipitation to be carried out in a single microtiter plate. (ii) Rigorous purification of DNA–protein adducts by a procedure that eliminates free proteins and free nucleic acids, generating samples suitable for detection of novel protein adducts (e.g. by mass spectroscopy). (iii) Identification and quantification of DNA–protein adducts by direct ELISA assay. The ELISA-based RADAR assay can detect Top1–DNA and Top2a–DNA adducts in human cells, and gyrase–DNA adducts in Escherichia coli . This approach will be useful for discovery and characterization of new drugs to treat infectious disease and cancer, and for development of companion diagnostics assays for individualized medicine.

Description: In recent years, evidence has emerged for the existence of many diverse types of RNA, which play roles in a wide range of biological processes in all kingdoms of life. These molecules generally do not, however, act in isolation, and identifying which proteins partner with RNA is a major challenge. Many methods, in vivo and in vitro , have been used to address this question, including combinatorial or high-throughput approaches, such as systematic evolution of ligands, cross-linking and immunoprecipitation and RNA immunoprecipitation combined with deep sequencing. However, most of these methods are not trivial to pursue and often require substantial optimization before results can be achieved. Here, we demonstrate a simple technique that allows one to screen proteins for RNA-binding properties in a gel-shift experiment and can be easily implemented in any laboratory. This assay should be a useful first-pass tool for assessing whether a protein has RNA- or DNA-binding properties, prior to committing resources to more complex procedures.

Description: A number of studies have shown that transcriptome analysis in terms of chromosomal location can reveal regions of non-random transcriptional activity within the genome. Genomic clusters of differentially expressed genes can identify genomic patterns of structural organization, underlying copy number variations or long-range epigenetic regulation such as X-chromosome inactivation. Here we apply an integrative bioinformatics analysis to a collection of 315 freely available mouse pluripotent stem cell samples to discover transcriptional clusters in the genome. We show that over half of the analysed samples (56.83%) carry whole or partial-chromosome spanning clusters which recur in genomic regions previously implicated in chromosomal imbalances. Strikingly, we found that the presence of such large-clusters is linked to the differential expression of a limited number of genes, common to all samples carrying clusters irrespectively of the chromosome where the cluster is found. We have used these genes to train and test classification models that can predict samples that carry large-scale clusters on any chromosome with over 90% accuracy. Our findings suggest that there is a common downstream activation in these cells that affects a limited number of nodes. We propose that this effect is linked to selective advantage and identify potential driver genes.

Description: The rapidly growing amount of genomic sequence data being generated and made publicly available necessitate the development of new data storage and archiving methods. The vast amount of data being shared and manipulated also create new challenges for network resources. Thus, developing advanced data compression techniques is becoming an integral part of data production and analysis. The HapMap project is one of the largest public resources of human single-nucleotide polymorphisms (SNPs), characterizing over 3 million SNPs genotyped in over 1000 individuals. The standard format and biological properties of HapMap data suggest that a dedicated genetic compression method can outperform generic compression tools. We propose a compression methodology for genetic data by introducing H ap Z ipper , a lossless compression tool tailored to compress HapMap data beyond benchmarks defined by generic tools such as gzip , bzip2 and lzma . We demonstrate the usefulness of H ap Z ipper by compressing HapMap 3 populations to 〈5% of their original sizes. H ap Z ipper is freely downloadable from https://bitbucket.org/pchanda/hapzipper/downloads/HapZipper.tar.bz2 .

Description: Spliced alignment plays a central role in the precise identification of eukaryotic gene structures. Even though many spliced alignment programs have been developed, recent rapid progress in DNA sequencing technologies demands further improvements in software tools. Benchmarking algorithms under various conditions is an indispensable task for the development of better software; however, there is a dire lack of appropriate datasets usable for benchmarking spliced alignment programs. In this study, we have constructed two types of datasets: simulated sequence datasets and actual cross-species datasets. The datasets are designed to correspond to various real situations, i.e. divergent eukaryotic species, different types of reference sequences, and the wide divergence between query and target sequences. In addition, we have developed an extended version of our program Spaln , which incorporates two additional features to the scoring scheme of the original version, and examined this extended version, Spaln2, together with the original Spaln and other representative aligners based on our benchmark datasets. Although the effects of the modifications are not individually striking, Spaln2 is consistently most accurate and reasonably fast in most practical cases, especially for plants and fungi and for increasingly divergent pairs of target and query sequences.

Description: RIP-seq has recently been developed to discover genome-wide RNA transcripts that interact with a protein or protein complex. RIP-seq is similar to both RNA-seq and ChIP-seq, but presents unique properties and challenges. Currently, no statistical tool is dedicated to RIP-seq analysis. We developed RIPSeeker ( http://www.bioconductor.org/packages/2.12/bioc/html/RIPSeeker.html ), a free open-source Bioconductor/R package for de novo RIP peak predictions based on HMM. To demonstrate the utility of the software package, we applied RIPSeeker and six other published programs to three independent RIP-seq datasets and two PAR-CLIP datasets corresponding to six distinct RNA-binding proteins. Based on receiver operating curves, RIPSeeker demonstrates superior sensitivity and specificity in discriminating high-confidence peaks that are consistently agreed on among a majority of the comparison methods, and dominated 9 of the 12 evaluations, averaging 80% area under the curve. The peaks from RIPSeeker are further confirmed based on their significant enrichment for biologically meaningful genomic elements, published sequence motifs and association with canonical transcripts known to interact with the proteins examined. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within a self-contained software package comprehensively addressing issues ranging from post-alignments’ processing to visualization and annotation.

Description: Sequence-specific DNA-binding proteins must quickly and reliably localize specific target sites on DNA. This search process has been well characterized for monomeric proteins, but it remains poorly understood for systems that require assembly into dimers or oligomers at the target site. We present a single-molecule study of the target-search mechanism of protelomerase TelK, a recombinase-like protein that is only active as a dimer. We show that TelK undergoes 1D diffusion on non-target DNA as a monomer, and it immobilizes upon dimerization even in the absence of a DNA target site. We further show that dimeric TelK condenses non-target DNA, forming a tightly bound nucleoprotein complex. Together with theoretical calculations and molecular dynamics simulations, we present a novel target-search model for TelK, which may be generalizable to other dimer and oligomer-active proteins.

Description: We describe a new, broadly applicable methodology for screening in parallel interactions of RNA-binding proteins (RBPs) with large numbers of microRNA (miRNA) precursors and for determining their affinities in native form in the presence of cellular factors. The assays aim at identifying pre-miRNAs that are potentially affected by the selected RBP during their biogenesis. The assays are carried out in microtiter plates and use chemiluminescent readouts. Detection of bound RBPs is achieved by protein or tag-specific antibodies allowing crude cell lysates to be used as a source of RBP. We selected 70 pre-miRNAs with phylogenetically conserved loop regions and 25 precursors of other well-characterized miRNAs for chemical synthesis in 3'-biotinylated form. An equivalent set in unmodified form served as inhibitors in affinity determinations. By testing three RBPs known to regulate miRNA biogenesis on this set of pre-miRNAs, we demonstrate that Lin28 and hnRNP A1 from cell lysates or as recombinant protein domains recognize preferentially precursors of the let-7 family, and that KSRP binds strongly to pre-miR-1-2.

Description: Various ‘omics’ technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

Description: A number of proteins form covalent bonds with DNA as obligatory transient intermediates in normal nuclear transactions. Drugs that trap these complexes have proven to be potent therapeutics in both cancer and infectious disease. Nonetheless, current assays for DNA–protein adducts are cumbersome, limiting both mechanistic studies and translational applications. We have developed a rapid and sensitive assay that enables quantitative immunodetection of protein–DNA adducts. This new ‘RADAR’ (rapid approach to DNA adduct recovery) assay accelerates processing time 4-fold, increases sample throughput 20-fold and requires 50-fold less starting material than the current standard. It can be used to detect topoisomerase 1-DNA adducts in as little as 60 ng of DNA, corresponding to 10 000 human cells. We apply the RADAR assay to demonstrate that expression of SLFN11 does not increase camptothecin sensitivity by promoting accumulation of topoisomerase 1-DNA adducts. The RADAR assay will be useful for analysis of the mechanisms of formation and resolution of DNA–protein adducts in living cells, and identification and characterization of reactions in which covalent DNA adducts are transient intermediates. The assay also has potential application to drug discovery and individualized medicine.

Description: Consistent with their complex lifestyles and rich secondary metabolite profiles, the genomes of streptomycetes encode a plethora of transcription factors, the vast majority of which are uncharacterized. Herein, we use Surface Plasmon Resonance (SPR) to identify and delineate putative operator sites for SCO3205, a MarR family transcriptional regulator from Streptomyces coelicolor that is well represented in sequenced actinomycete genomes. In particular, we use a novel SPR footprinting approach that exploits indirect ligand capture to vastly extend the lifetime of a standard streptavidin SPR chip. We define two operator sites upstream of sco3205 and a pseudopalindromic consensus sequence derived from these enables further potential operator sites to be identified in the S. coelicolor genome. We evaluate each of these through SPR and test the importance of the conserved bases within the consensus sequence. Informed by these results, we determine the crystal structure of a SCO3205-DNA complex at 2.8 Å resolution, enabling molecular level rationalization of the SPR data. Taken together, our observations support a DNA recognition mechanism involving both direct and indirect sequence readout.

Description: Multiplex analytical systems that allow detection of multiple nucleic acid targets in one assay can provide rapid characterization of a sample while still saving cost and resources. However, few systems have proven to offer a solution for mid-plex (e.g. 10- to 50-plex) analysis that is high throughput and cost effective. Here we describe the combined use of fluorescence color and melting temperature (T m ) as a virtual 2D label that enables homogenous detection of one order of magnitude more targets than current strategies on real-time polymerase chain reaction platform. The target was first hybridized with a pair of ligation oligonucleotides, one of which harbored an artificial sequence that had a unique T m when hybridized with a reporter fluorogenic probe. The ligated products were then amplified by a universal primer pair and denatured by a melting curve analysis procedure. The targets were identified by their respective T m values in the corresponding fluorescence detection channels. The proof-of-principle of this approach was validated by genotyping 15 high-risk human papillomaviruses and 48 human single-nucleotide polymorphisms. The robustness of this method was demonstrated by analyzing a large number of clinical samples in both cases. The combined merits of multiplexity, flexibility and simplicity should make this approach suitable for a variety of applications.

Description: The chromatin structure of eukaryotic telomeres plays an essential role in telomere functions. However, their study might be impaired by the presence of interstitial telomeric sequences (ITSs), which have a widespread distribution in different model systems. We have developed a simple approach to study the chromatin structure of Arabidopsis telomeres independently of ITSs by analyzing ChIP-seq data. This approach could be used to study the chromatin structure of telomeres in some other eukaryotes. The analysis of ChIP-seq experiments revealed that Arabidopsis telomeres have higher density of histone H3 than centromeres, which might reflects their short nucleosomal organization. These experiments also revealed that Arabidopsis telomeres have lower levels of heterochromatic marks than centromeres (H3K9 Me2 and H3K27 Me ), higher levels of some euchromatic marks (H3K4 Me2 and H3K9Ac) and similar or lower levels of other euchromatic marks (H3K4 Me3 , H3K36 Me2 , H3K36 Me3 and H3K18Ac). Interestingly, the ChIP-seq experiments also revealed that Arabidopsis telomeres exhibit high levels of H3K27 Me3 , a repressive mark that associates with many euchromatic genes. The epigenetic profile of Arabidopsis telomeres is closely related to the previously defined chromatin state 2. This chromatin state is found in 23% of Arabidopsis genes, many of which are repressed or lowly expressed. At least, in part, this scenario is similar in rice.

Description: To depict the largest picture of a core promoter interactome, we developed a one-step DNA-affinity capture method coupled with an improved mass spectrometry analysis process focused on the identification of low abundance proteins. As a proof of concept, this method was developed through the analysis of 230 bp contained in the 5'long terminal repeat (LTR) of the human immunodeficiency virus 1 (HIV-1). Beside many expected interactions, many new transcriptional regulators were identified, either transcription factors (TFs) or co-regulators, which interact directly or indirectly with the HIV-1 5'LTR. Among them, the homeodomain-containing TF myeloid ectopic viral integration site was confirmed to functionally interact with a specific binding site in the HIV-1 5'LTR and to act as a transcriptional repressor, probably through recruitment of the repressive Sin3A complex. This powerful and validated DNA-affinity approach could also be used as an efficient screening tool to identify a large set of proteins that physically interact, directly or indirectly, with a DNA sequence of interest. Combined with an in silico analysis of the DNA sequence of interest, this approach provides a powerful approach to select the interacting candidates to validate functionally by classical approaches.