Paired-end Ditag Research Articles

Transcript Profiling Analysis Through Paired-End Ditag (PET) Approach Coupled with Deep Sequencing Reveals Transcriptome Complexity in Yeast.

The identification of structural and functional elements encoded in a genome is a challenging task. Although the transcriptome of budding yeast has been extensively analyzed, the boundaries and untranslated regions of yeast genes remain elusive. To address this least-explored field of yeast genomics, we performed a transcript profiling analysis through paired-end ditag (PET) approach coupled with deep sequencing. With 562,133 PET sequences we accurately defined the boundaries and untranslated regions of 3,409 ORFs, suggesting many yeast genes have multiple transcription start sites (TSSs). We also identified 85 previously uncharacterized transcripts either in intergenic regions or from the opposite strand of reported genomic features. Furthermore, our data revealed the extensive 3' end heterogeneity of yeast genes and identified a novel putative motif for polyadenylation. This study would serve as an invaluable resource for elucidating the regulation and evolution of yeast genes. Here we present a detailed protocol with minor modifications, which couldbe broadly applied to investigate transcripts from budding yeast to mammalian organisms.

Genome-wide profiling of untranslated regions by paired-end ditag sequencing reveals unexpected transcriptome complexity in yeast.

The identification of structural and functional elements encoded in a genome is a challenging task. Although the transcriptome of budding yeast has been extensively analyzed, the boundaries and untranslated regions of yeast genes remain elusive. To address this least-explored field of yeast genomics, we performed a transcript profiling analysis through paired-end ditag (PET) approach coupled with deep sequencing. With 562,133 PET sequences we accurately defined the boundaries and untranslated regions of 3,409 ORFs, suggesting many yeast genes have multiple transcription start sites (TSSs). We also identified 85 previously uncharacterized transcripts either in intergenic regions or from the opposite strand of reported genomic features. Furthermore, our data revealed the extensive 3' end heterogeneity of yeast genes and identified a novel putative motif for polyadenylation. Our results indicate the yeast transcriptome is more complex than expected. This study would serve as an invaluable resource for elucidating the regulation and evolution of yeast genes.

Palindromic sequence impedes sequencing-by-ligation mechanism

BackgroundCurrent next-generation sequencing (NGS) platforms adopt two types of sequencing mechanisms: by synthesis or by ligation. The former is employed by 454 and Solexa systems, while the latter by SOLiD system. Although the pros and cons for each sequencing mechanism have more or less been discussed in a number of occasions, the potential obstacle imposed by palindromic sequences has not yet been addressed.MethodsTo test the effect of the palindromic region on sequencing efficacy, we clonally amplified a paired-end ditag sequence composed of a 24-bp palindromic sequence flanked by a pair of tags from the E. coli genome. We used the near homogeneous fragments produced from MmeI digestion of the amplified clone to generate a sequencing library for SOLiD 5500xl sequencer.ResultsResults showed that, traditional ABI sequencers, which adopt sequencing-by-synthesis mechanism, were able to read through the palindromic region. However, SOLiD 5500xl was unable to do so. Instead, the palindromic region was read as miscellaneous random sequences. Moreover, readable tag sequence turned obscure ~2 bp prior to the palindromic region.ConclusionsTaken together, we demonstrate that SOLiD machines, which employ sequencing-by-ligation mechanism, are unable to read through the palindromic region. On the other hand, sequencing-by-synthesis sequencers had no difficulty in doing so.

A Common Deletion Polymorphism in the BIM Gene Contributes to Intrinsic Imatinib Resistance in Chronic Myelogenous Leukemia

Abstract 1666The use of the tyrosine kinase inhibitor (TKI), imatinib (IM), to target the oncogenic BCR-ABL kinase has resulted in profound responses in patients with chronic phase (CP) chronic myelogenous leukemia (CML). However, a subset of patients do not respond to TKIs, and are deemed to have primary resistance. Importantly, patients with European LeukemiaNet (ELN)-defined ‘failure' or ‘suboptimal response' are at increased risk of poorer long-term outcomes. Little is known about mechanisms underlying primary resistance, where only a minority of patients have BCR-ABL kinase domain (KD) mutations. Interestingly, East-Asian CML patients are reported to have lower complete cytogenetic response rates compared to the West (∼50 vs 80% respectively, Au et al. 2009). We used massively parallel DNA sequencing of paired-end ditags to identify genetic factors associated with resistance in CML patient samples. We discovered a novel deletion polymorphism in the BIM gene that correlated with resistance, and which represented a common polymorphism in normal East-Asian (12.3% carriers), but not African or Caucasian (0%), populations (n=2465). BIM is a pro-apoptotic BCL2 family member, and plays a central role in CML pathophysiology. Here, BCR-ABL suppresses FoxO3a-mediated BIM transcription to maintain a survival advantage, while preventing BIM expression following BCR-ABL inhibition results in TKI resistance. Inspection of BIM gene structure suggested the polymorphism would result in mutually exclusive splicing of exon 3 (E3) vs 4 (E4), leading to decreased expression of BIM transcripts encoding the pro-apoptotic BH3 domain (found only in E4). To test this hypothesis, we constructed a minigene to measure E3 vs E4 splicing, and found the polymorphism decreased splicing to E4 over E3 by >5-fold. Importantly, primary CML cells exhibited the same phenomenon, since polymorphism-containing samples expressed lower levels of E4- vs E3-containing transcripts (p=0.008), while general BIM transcription was unaffected. Our observations suggested a novel mechanism for intrinsic TKI resistance. Here, upon IM exposure, polymorphism-containing CML cells would favor induction of E3- vs E4-containing BIM transcripts, decreased expression of BH3-containing BIM isoforms, and impaired apoptosis. To facilitate these studies, we identified a Japanese CML cell line, KCL22, which contained the polymorphism, and confirmed it had a decreased E4/E3 transcript ratio compared to cells without the polymorphism. KCL22 cells also had decreased induction of E4-containing transcripts following IM, as well as lower levels of BIMEL protein, a major BH3-containing BIM isoform. Consistent with prior reports, KCL22 cells were resistant to IM, despite effective BCR-ABL inhibition, and had impaired apoptotic signalling upon IM exposure. Importantly, and as predicted by our model, pharmacologic restoration of BH3 activity (using the BH3-mimetic drug, ABT-737) sensitized cells to IM-induced death. Next, we used zinc finger nuclease-facilitated gene targeting to precisely create the polymorphism in the BIM gene of IM-sensitive K562 CML cells. We generated subclones that were heterozygous or homozygous for the polymorphism, and confirmed a decreased E4/E3 ratio in these cells in a polymorphism-dosage-dependent manner. Polymorphism-containing cells exhibited decreased induction of E4-containing transcripts following IM exposure, as well as impaired upregulation of BIMEL protein, and diminished apoptotic cell death. As in KCL22 cells, ABT-737 enhanced the ability of IM to activate apoptosis in polymorphism-containing cells. Using an expanded East-Asian CML cohort (n=203), we found the polymorphism correlated with TKI resistance (defined as ‘failure' or ‘suboptimal' per ELN criteria) in CP patients treated with 400 mg IM daily (p=0.02). Further, patients with the polymorphism were more likely to have resistance in the absence of a KD mutation than those without (OR=2.24, 95% CI of 1.22–4.12). In sum, we have found an East-Asian polymorphism in BIM that is associated with intrinsic resistance to TKIs. Screening for this polymorphism may be useful in identifying patients at risk of TKI resistance; a resistance we show can be overcome by BH3 mimetics. Our findings may also apply to other cancers and proliferative disorders in which drug-sensitivity is BIM-dependent. Disclosures:No relevant conflicts of interest to declare.

Benefits of random-priming: Exhaustive survey of a cDNA library from lung tissue of a SARS patient

The severe acute respiratory syndrome (SARS) leads to severe injury in the lungs with multiple factors, though the pathogenesis is still largely unclear. This paper describes the particular analyses of the transcriptome of human lung tissue that was infected by SARS‐associated coronavirus (SARS‐CoV). Random primers were used to produce ESTs from total RNA samples of the lung tissue. The result showed a high diversity of the transcripts, covering much of the human genome, including loci which do not contain protein coding sequences. 10,801 ESTs were generated and assembled into 267 contigs plus 7,659 singletons. Sequences matching to SARS‐CoV RNAs and other pneumonia‐related microbes were found. The transcripts were well classified by functional annotation. Among the 7,872 assembled sequences that were identified as from human genome, 578 non‐coding genes were revealed by BLAST search. The transcripts were mapped to the human genome with the restriction of identity = 100%, which found a candidate pool of 448 novel transcriptional loci where EST transcriptional signal was never found before. Among these, 13 loci were never reported to be transcriptional by other detection methods such as gene chips, tiling arrays, and paired‐end ditags (PETs). The result showed that random‐priming cDNA library is valid for the investigation of transcript diversity in the virus‐infected tissue. The EST data could be a useful supplemental source for SARS pathology researches. J. Med. Virol. 83:574–586, 2011. © 2011 Wiley‐Liss, Inc.

Protein Kinase Target Discovery From Genome‐Wide Messenger RNA Expression Profiling

Genome-wide messenger RNA profiling provides a snapshot of the global state of the cell under different experimental conditions such as diseased versus normal cellular states. However, because measurements are in the form of quantitative changes in messenger RNA levels, such experimental data does not provide direct understanding of the regulatory molecular mechanisms responsible for the observed changes. Identifying potential cell signaling regulatory mechanisms responsible for changes in gene expression under different experimental conditions or in different tissues has been the focus of many computational systems biology studies. Most popular approaches include promoter analysis, gene ontology, or pathway enrichment analysis, as well as reverse engineering of networks from messenger RNA expression data. Here we present a rational approach for identifying and ranking protein kinases that are likely responsible for observed changes in gene expression. By combining promoter analysis; data from various chromatin immunoprecipitation studies such as chromatin immunoprecipitation sequencing, chromatin immunoprecipitation coupled with paired-end ditag, and chromatin immunoprecipitation-on-chip; protein-protein interactions; and kinase-protein phosphorylation reactions collected from the literature, we can identify and rank candidate protein kinases for knock-down, or other types of functional validations, based on genome-wide changes in gene expression. We describe how protein kinase candidate identification and ranking can be made robust by cross-validation with phosphoproteomics data as well as through a literature-based text-mining approach. In conclusion, data integration can produce robust candidate rankings for understanding cell regulation through identification of protein kinases responsible for gene expression changes, and thus rapidly advancing drug target discovery and unraveling drug mechanisms of action.

BioSpotlight

BioSpotlight

Finding genes in Schistosoma japonicum: annotating novel genomes with help of extrinsic evidence

We have developed a novel method for estimating the parameters of hidden Markov models for gene finding in newly sequenced species. Our approach does not rely on curated training data sets, but instead uses extrinsic evidence (including paired-end ditags that have not been used in gene finding previously) and iterative training. This new method is particularly suitable for annotation of species with large evolutionary distance to the closest annotated species. We have used our approach to produce an initial annotation of more than 16 000 genes in the newly sequenced Schistosoma japonicum draft genome. We established the high quality of our predictions by comparison to full-length cDNAs (withdrawn from the extrinsic evidence) and to CEGMA core genes. We also evaluated the effectiveness of the new training procedure on Caenorhabditis elegans genome. ExonHunter and the newest parametric files for S. japonicum genome are available for download at www.bioinformatics.uwaterloo.ca/downloads/exonhunter

Novel Applications of the Paired-End diTag (PET) Technology in Pharmacogenomics

Genomics is becoming the integral part of Pharmacogenomics, and the Paired-End diTag (PET) technology is creating a new paradigm in Genomics. The PET technology directly links the 5 terminal tags of cDNAs or genomic sequences with their corresponding 3 terminal tags to form PET ditags and concatenates them for efficient sequencing. The GIS (Gene Identification Signature)-PET analysis was developed for studying transcriptomes and pathway aberrations. It can precisely demarcate the alternative transcription start site (TSS) and the alternative polyadenylation site (PAS). The paired-end nature makes the identification of fusion genes, fusion transcripts, and pseudogenes very straightforward. Additionally, PET-associated genes can be correlated to pathway database to systematically reveal global pathway aberrations. Changes in metabolic and signal transduction pathways can be compared across different cell types. Later, the ChIP (Chromatin immunoprecipitation)-PET analysis was developed. This approach facilitates genome-wide mapping of transcription factor binding sites (TFBSs), as shown in the studies of p53, c-Myc, estrogen receptor, Oct4/Nanog/Sox2, STAT1, NFκB. In addition, study of trimethylations of lysine4 and lysine27 in H3 histone protein demonstrated the capability of ChIP-PET for genome-wide mapping of epigenetic modifications. Integration of all these PET data would produce a comprehensive picture of genetic and epigenetic cis-acting elements, gene expression and regulation, and pathway activities; and data can be analyzed and compared at molecular, gene, and pathway levels. This article reviews the advancement of the PET technology and discusses its potential applications in Pharmacogenomics.

The use of multiple displacement amplification to amplify complex DNA libraries.

Complex libraries for genomic DNA and cDNA sequencing analyses are typically amplified using bacterial propagation. To reduce biases, large numbers of colonies are plated and scraped from solid-surface agar. This process is time consuming, tedious and limits scaling up. At the same time, multiple displacement amplification (MDA) has been recently developed as a method for in vitro amplification of DNA. However, MDA has no selection function for the removal of ligation multimers. We developed a novel method of briefly introducing ligation reactions into bacteria to select single insert DNA clones followed by MDA to amplify. We applied these methods to a Gene Identification Signatures with Paired-End diTags (GIS-PET) library, which is a complex transcriptome library created by pairing short tags from the 5′ and 3′ ends of cDNA fragments together, and demonstrated that this selection and amplification strategy is unbiased and efficient.

Identification of Novel Transcriptional Consequences of Activation and Inactivation of TP53 in Multiple Myeloma.

The genetic lesions important in the pathogenesis and prognosis of multiple myeloma (MM) continue to be elucidated. TP53 is deleted in approximately 10% of cases and is associated with a poor prognosis in MM. As a transcription factor, TP53 regulates the expression of genes involved in a variety of cellular functions, including cell-cycle arrest, DNA repair, and apoptosis. In the current study, we identified novel TP53 target genes and demonstrated the clinical relevance of alterations in this signaling pathway in disease progression. First, we examined the expression of 122 genes that were identified as direct TP53 target genes by paired-end diTags (PET) analysis and whose p53-dependent expression had been validated. The target genes were profiled in a collection of 351 newly diagnosed MM samples using the Affymetrix U133Plus2.0 microarrays. In this set of tumors, TP53 expression in the lowest 10th percentile was associated with a significantly shorter event-free (P = 0.0004) and overall survival (P = 0.0001). However, expression of only a few of the previously identified TP53 target genes correlated with TP53 expression in MM cells. This suggested that TP53 may regulate a distinct set of genes in MM. To elucidate the TP53 regulatory networks in MM, we used lentiviral transduction to over express TP53 in four MM cell lines (OCI-MY5, JJN3, ARP-1 and Delta 47). An increase in steady-state TP53 level was confirmed by Western blot analysis 24 hours post lentiviral transduction and massive cell death occurred within 36 hours. Gene expression profiling revealed that a total of 85 genes were affected by TP53 expression: 50 were up-regulated and 35 were down-regulated 1.5-fold or greater in at least 3 of 4 MM cell lines. Expression analysis of primary MM revealed that the 85 genes also exhibited differential expression in comparison of those with the lowest relative to the highest TP53 expression, suggesting that TP53 may directly or indirectly regulate the expression of these genes. Of the 85 genes, 4 genes (ZMAT3, TNFRSF10B, TRIM22, and NOTCH1) were in the group of 122 P53 target genes identified by PET analysis. Consistent with known TP53 cellular functions, we found 69 of the 85 TP53 regulated genes in MM to be involved in apoptosis, cell cycle regulation, cell growth and differentiation, DNA repair and chromatin modification, and transcription regulation. Unsupervised hierarchical clustering of 351 newly diagnosed MM and 90 relapsed MM with the 85 TP53 associated genes identified 2 subgroups in each analysis. The subtype associated with lower TP53 expression had a significantly shorter EFS (P = 0.0006) and OS (P = 0.0010) in newly diagnosed MM and shorter post-relapse survival in relapsed disease (P < 0.0001). Thus we have identified MM-specific TP53 target genes by expression profiling in both cultured myeloma cells and primary tumors that correlate with clinical outcome. The identification and characterization of these pathways may lead to a better understanding of the critical role of TP53 loss in cancer.

Whole-Genome Mapping of Histone H3 Lys4 and 27 Trimethylations Reveals Distinct Genomic Compartments in Human Embryonic Stem Cells

Epigenetic modifications are crucial for proper lineage specification and embryo development. To explore the chromatin modification landscapes in human ES cells, we profiled two histone modifications, H3K4me3 and H3K27me3, by ChIP coupled with the paired-end ditags sequencing strategy. H3K4me3 was found to be a prevalent mark and occurred in close proximity to the promoters of two-thirds of total human genes. Among the H3K27me3 loci identified, 56% are associated with promoters and the vast majority of them are comodified by H3K4me3. By deep-transcript digital counting, 80% of H3K4me3 and 36% of comodified promoters were found to be transcribed. Remarkably, we observed that different combinations of histone methylations are associated with genes from distinct functional categories. These global histone methylation maps provide an epigenetic framework that enables the discovery of novel transcriptional networks and delineation of different genetic compartments of the pluripotent cell genome.

Paired‐End diTagging for Transcriptome and Genome Analysis

The Paired-End diTagging (PET) procedure enables one to obtain sequence information from both termini of any contiguous DNA fragment. This is achieved by a series of enzymatic manipulations that introduce MmeI sites directly flanking each DNA insert during the construction of a plasmid library. Subsequent MmeI digestion and self-ligation results in the production of covalently-linked paired-end ditags (PETs) that can be extracted and then concatenated for efficient sequencing. By mapping the PET sequences to assembled genomes, the original DNA fragments from which the PETs were derived can be precisely localized. This unit details two applications of PET technology. In GIS-PET, ditagging of mRNA converted to full-length cDNA enables whole-transcriptome analysis, including novel gene identification, gene prediction validation, and gene expression studies. In ChIP-PET, ditagging of chromatin immunoprecipitation-enriched genomic DNA fragments enables the global mapping of transcription factor binding sites. A recent innovation (Multiplex Sequencing of Paired-End ditags; MS-PET) enables PETs to be sequenced using high-throughput 454 sequencing, greatly increasing the amount of data that can be collected in each run.

Pathway aberrations of murine melanoma cells observed in Paired-End diTag transcriptomes

BackgroundMelanoma is the major cause of skin cancer deaths and melanoma incidence doubles every 10 to 20 years. However, little is known about melanoma pathway aberrations. Here we applied the robust Gene Identification Signature Paired End diTag (GIS-PET) approach to investigate the melanoma transcriptome and characterize the global pathway aberrations.MethodsGIS-PET technology directly links 5' mRNA signatures with their corresponding 3' signatures to generate, and then concatenate, PETs for efficient sequencing. We annotated PETs to pathways of KEGG database and compared the murine B16F1 melanoma transcriptome with three non-melanoma murine transcriptomes (Melan-a2 melanocytes, E14 embryonic stem cells, and E17.5 embryo). Gene expression levels as represented by PET counts were compared across melanoma and melanocyte libraries to identify the most significantly altered pathways and investigate the expression levels of crucial cancer genes.ResultsMelanin biosynthesis genes were solely expressed in the cells of melanocytic origin, indicating the feasibility of using the PET approach for transcriptome comparison. The most significantly altered pathways were metabolic pathways, including upregulated pathways: purine metabolism, aminophosphonate metabolism, tyrosine metabolism, selenoamino acid metabolism, galactose utilization, nitrobenzene degradation, and bisphenol A degradation; and downregulated pathways: oxidative phosphorylation, ATPase synthesis, TCA cycle, pyruvate metabolism, and glutathione metabolism. The downregulated pathways concurrently indicated a slowdown of mitochondrial activities. Mitochondrial permeability was also significantly altered, as indicated by transcriptional activation of ATP/ADP, citrate/malate, Mg++, fatty acid and amino acid transporters, and transcriptional repression of zinc and metal ion transporters. Upregulation of cell cycle progression, MAPK, and PI3K/Akt pathways were more limited to certain region(s) of the pathway. Expression levels of c-Myc and Trp53 were also higher in melanoma. Moreover, transcriptional variants resulted from alternative transcription start sites or alternative polyadenylation sites were found in Ras and genes encoding adhesion or cytoskeleton proteins such as integrin, β-catenin, α-catenin, and actin.ConclusionThe highly correlated results unmistakably point to a systematic downregulation of mitochondrial activities, which we hypothesize aims to downgrade the mitochondria-mediated apoptosis and the dependency of cancer cells on angiogenesis. Our results also demonstrate the advantage of using the PET approach in conjunction with KEGG database for systematic pathway analysis.

Fusion transcripts and transcribed retrotransposed loci discovered through comprehensive transcriptome analysis using Paired-End diTags (PETs)

Identification of unconventional functional features such as fusion transcripts is a challenging task in the effort to annotate all functional DNA elements in the human genome. Paired-End diTag (PET) analysis possesses a unique capability to accurately and efficiently characterize the two ends of DNA fragments, which may have either normal or unusual compositions. This unique nature of PET analysis makes it an ideal tool for uncovering unconventional features residing in the human genome. Using the PET approach for comprehensive transcriptome analysis, we were able to identify fusion transcripts derived from genome rearrangements and actively expressed retrotransposed pseudogenes, which would be difficult to capture by other means. Here, we demonstrate this unique capability through the analysis of 865,000 individual transcripts in two types of cancer cells. In addition to the characterization of a large number of differentially expressed alternative 5' and 3' transcript variants and novel transcriptional units, we identified 70 fusion transcript candidates in this study. One was validated as the product of a fusion gene between BCAS4 and BCAS3 resulting from an amplification followed by a translocation event between the two loci, chr20q13 and chr17q23. Through an examination of PETs that mapped to multiple genomic locations, we identified 4055 retrotransposed loci in the human genome, of which at least three were found to be transcriptionally active. The PET mapping strategy presented here promises to be a useful tool in annotating the human genome, especially aberrations in human cancer genomes.

Computational analysis and modeling of genome-scale avidity distribution of transcription factor binding sites in chip-pet experiments.

Advances in high-throughput technologies, such as ChIP-chip and ChIP-PET (Chromatin Immuno-Precipitation Paired-End diTag), and the availability of human and mouse genome sequences now allow us to identify transcription factor binding sites (TFBS) and analyze mechanisms of gene regulation on the level of the entire genome. Here, we have developed a computational approach which uses ChIP-PET data and statistical modeling to assess experimental noise and identify reliable TFBS for c-Myc, STAT1 and p53 transcription factors in the human genome. We propose a mixture probabilistic model and develop computational programs for Monte Carlo simulation of ChIP-PET data to define the background noise of the sequence clustering and to identify the probability function of specific DNA-protein binding in the eukaryotic genome. Our approach demonstrates high reproducibility of the method and not only distinguishes bona fide TFBSs from non-specific TFBSs with a high specificity, but also provides algorithmic and computational basis for further optimization of experimental parameters of the ChIP-PET method.

High-Throughput Methods of Regulatory Element Discovery

With the number of organisms whose genomes have been sequenced, a vast amount of information concerning the genetic structure of an organism's genome has been collected. However, effective experiment means to study how this information is accessed have only recently been developed. In this review, three basic methods for identifying regions of protein-DNA interaction will be introduced. The first two, chromatin immunoprecipitation (ChIP)-chip and ChIP-PET (for paired-end ditag), rely on the enrichment provided by chromosomal immunoprecipitation to interrogate the genomic sequence for the interaction sites of a protein of interest. In contrast, protein microarrays allow the identification of DNA binding protein that interacts with a DNA sequence of interest. These complementary methods of exploring protein-DNA interactions will increase our fundamental knowledge of how the information contained within the genome sequence is accessed and processed.

PET-Tool: a software suite for comprehensive processing and managing of Paired-End diTag (PET) sequence data

BackgroundWe recently developed the Paired End diTag (PET) strategy for efficient characterization of mammalian transcriptomes and genomes. The paired end nature of short PET sequences derived from long DNA fragments raised a new set of bioinformatics challenges, including how to extract PETs from raw sequence reads, and correctly yet efficiently map PETs to reference genome sequences. To accommodate and streamline data analysis of the large volume PET sequences generated from each PET experiment, an automated PET data process pipeline is desirable.ResultsWe designed an integrated computation program package, PET-Tool, to automatically process PET sequences and map them to the genome sequences. The Tool was implemented as a web-based application composed of four modules: the Extractor module for PET extraction; the Examiner module for analytic evaluation of PET sequence quality; the Mapper module for locating PET sequences in the genome sequences; and the ProjectManager module for data organization. The performance of PET-Tool was evaluated through the analyses of 2.7 million PET sequences. It was demonstrated that PET-Tool is accurate and efficient in extracting PET sequences and removing artifacts from large volume dataset. Using optimized mapping criteria, over 70% of quality PET sequences were mapped specifically to the genome sequences. With a 2.4 GHz LINUX machine, it takes approximately six hours to process one million PETs from extraction to mapping.ConclusionThe speed, accuracy, and comprehensiveness have proved that PET-Tool is an important and useful component in PET experiments, and can be extended to accommodate other related analyses of paired-end sequences. The Tool also provides user-friendly functions for data quality check and system for multi-layer data management.

Multiplex sequencing of paired-end ditags (MS-PET): a strategy for the ultra-high-throughput analysis of transcriptomes and genomes

The paired-end ditagging (PET) technique has been shown to be efficient and accurate for large-scale transcriptome and genome analysis. However, as with other DNA tag-based sequencing strategies, it is constrained by the current efficiency of Sanger technology. A recently developed multiplex sequencing method (454-sequencing™) using picolitre-scale reactions has achieved a remarkable advance in efficiency, but suffers from short-read lengths, and a lack of paired-end information. To further enhance the efficiency of PET analysis and at the same time overcome the drawbacks of the new sequencing method, we coupled multiplex sequencing with paired-end ditagging (MS-PET) using modified PET procedures to simultaneously sequence 200 000 to 300 000 dimerized PET (diPET) templates, with an output of nearly half-a-million PET sequences in a single 4 h machine run. We demonstrate the utility and robustness of MS-PET by analyzing the transcriptome of human breast carcinoma cells, and by mapping p53 binding sites in the genome of human colorectal carcinoma cells. This combined sequencing strategy achieved an approximate 100-fold efficiency increase over the current standard for PET analysis, and furthermore enables the short-read-length multiplex sequencing procedure to acquire paired-end information from large DNA fragments.

Tracking the wily transcription factor

A 'paired-end ditag' (PET) strategy for pinpointing protein binding sites can reveal a wealth of information about transcription factors and other DNA-binding proteins.