Discovering Motifs in Ranked Lists of DNA Sequences

Computational methods for discovery of sequence elements that are enriched in a target set compared with a background set are fundamental in molecular biology research. One example is the discovery of transcription factor binding motifs that are inferred from ChIP–chip (chromatin immuno-precipitation on a microarray) measurements. Several major challenges in sequence motif discovery still require consideration: (i) the need for a principled approach to partitioning the data into target and background sets; (ii) the lack of rigorous models and of an exact p-value for measuring motif enrichment; (iii) the need for an appropriate framework for accounting for motif multiplicity; (iv) the tendency, in many of the existing methods, to report presumably significant motifs even when applied to randomly generated data. In this paper we present a statistical framework for discovering enriched sequence elements in ranked lists that resolves these four issues. We demonstrate the implementation of this framework in a software application, termed DRIM (discovery of rank imbalanced motifs), which identifies sequence motifs in lists of ranked DNA sequences. We applied DRIM to ChIP–chip and CpG methylation data and obtained the following results. (i) Identification of 50 novel putative transcription factor (TF) binding sites in yeast ChIP–chip data. The biological function of some of them was further investigated to gain new insights on transcription regulation networks in yeast. For example, our discoveries enable the elucidation of the network of the TF ARO80. Another finding concerns a systematic TF binding enhancement to sequences containing CA repeats. (ii) Discovery of novel motifs in human cancer CpG methylation data. Remarkably, most of these motifs are similar to DNA sequence elements bound by the Polycomb complex that promotes histone methylation. Our findings thus support a model in which histone methylation and CpG methylation are mechanistically linked. Overall, we demonstrate that the statistical framework embodied in the DRIM software tool is highly effective for identifying regulatory sequence elements in a variety of applications ranging from expression and ChIP–chip to CpG methylation data. DRIM is publicly available at http://bioinfo.cs.technion.ac.il/drim

Genomic Profiling of Advanced-Stage, Metaplastic Breast Carcinoma by Next-Generation Sequencing Reveals Frequent, Targetable Genomic Abnormalities and Potential New Treatment Options

Context.— Metastatic metaplastic breast carcinoma (MPBC) is an uncommon, but aggressive, tumor resistant to conventional chemotherapy. Objective.— To learn whether next-generation sequencing could identify potential targets of therapy for patients with relapsed and metastatic MPBC. Design.— Hybridization capture of 3769 exons from 236 cancer-related genes and 47 introns of 19 genes commonly rearranged in cancer was applied to a minimum of 50 ng of DNA extracted from 20 MPBC formalin-fixed, paraffin-embedded specimens and sequenced to high uniform coverage. Results.— The 20 patients with MPBC had a median age of 62 years (range, 42–86 years). There were 9 squamous (45%), 9 chondroid (45%), and 2 spindle cell (10%) MPBCs, all of which were high grade. Ninety-three genomic alterations were identified, (range, 1–11) with 19 of the 20 cases (95%) harboring an alteration that could potentially lead to a targeted treatment option. The most-common alterations were in TP53 (n = 69; 75%), PIK3CA (n = 37; 40%), MYC (n = 28; 30%), MLL2 (n = 28; 30%), PTEN (n = 23; 25%), CDKN2A/B (n = 19; 20%), CCND3 (n = 14; 15%), CCNE1 (n = 9; 10%), EGFR (n = 9; 10%), and KDM6A (n = 9; 10%); AKT3, CCND1, CCND2, CDK4, FBXW7, FGFR1, HRAS, NF1, PIK3R1, and SRC were each altered in a single case. All 16 MPBCs (100%) that were negative for ERBB2 (HER2) overexpression by immunohistochemistry and/or ERBB2 (HER2) amplification by fluorescence in situ hybridization were also uniformly (100%) negative for ERBB2 amplification by next-generation sequencing–based copy-number assessment. Conclusions.— Our results indicate that genomic profiling using next-generation sequencing can identify clinically meaningful alterations that have the potential to guide targeted treatment decisions in most patients with metastatic MPBC

A Novel Translocation Breakpoint within the BPTF Gene Is Associated with a Pre-Malignant Phenotype

Partial gain of chromosome arm 17q is an abundant aberrancy in various cancer types such as lung and prostate cancer with a prominent occurrence and prognostic significance in neuroblastoma – one of the most common embryonic tumors. The specific genetic element/s in 17q responsible for the cancer-promoting effect of these aberrancies is yet to be defined although many genes located in 17q have been proposed to play a role in malignancy. We report here the characterization of a naturally-occurring, non-reciprocal translocation der(X)t(X;17) in human lung embryonal-derived cells following continuous culturing. This aberrancy was strongly correlated with an increased proliferative capacity and with an acquired ability to form colonies in vitro. The breakpoint region was mapped by fluorescence in situ hybridization (FISH) to the 17q24.3 locus. Further characterization by a custom-made comparative genome hybridization array (CGH) localized the breakpoint within the Bromodomain PHD finger Transcription Factor gene (BPTF), a gene involved in transcriptional regulation and chromatin remodeling. Interestingly, this translocation led to elevation in the mRNA levels of the endogenous BPTF. Knock-down of BPTF restricted proliferation suggesting a role for BPTF in promoting cellular growth. Furthermore, the BPTF chromosomal region was found to be amplified in various human tumors, especially in neuroblastomas and lung cancers in which 55% and 27% of the samples showed gain of 17q24.3, respectively. Additionally, 42% percent of the cancer cell lines comprising the NCI-60 had an abnormal BPTF locus copy number. We suggest that deregulation of BPTF resulting from the translocation may confer the cells with the observed cancer-promoting phenotype and that our cellular model can serve to establish causality between 17q aberrations and carcinogenesis

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

<p>Abstract</p> <p>Background</p> <p>Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results.</p> <p>Results</p> <p><it>GOrilla </it>is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). <it>GOrilla </it>employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the <it>top </it>of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, <it>GOrilla </it>computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms.</p> <p>Conclusion</p> <p><it>GOrilla </it>is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. <it>GOrilla</it>'s unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. <it>GOrilla </it>is publicly available at: <url>http://cbl-gorilla.cs.technion.ac.il</url></p

Protocol Dependence of Sequencing-Based Gene Expression Measurements

RNA Seq provides unparalleled levels of information about the transcriptome including precise expression levels over a wide dynamic range. It is essential to understand how technical variation impacts the quality and interpretability of results, how potential errors could be introduced by the protocol, how the source of RNA affects transcript detection, and how all of these variations can impact the conclusions drawn. Multiple human RNA samples were used to assess RNA fragmentation, RNA fractionation, cDNA synthesis, and single versus multiple tag counting. Though protocols employing polyA RNA selection generate the highest number of non-ribosomal reads and the most precise measurements for coding transcripts, such protocols were found to detect only a fraction of the non-ribosomal RNA in human cells. PolyA RNA excludes thousands of annotated and even more unannotated transcripts, resulting in an incomplete view of the transcriptome. Ribosomal-depleted RNA provides a more cost-effective method for generating complete transcriptome coverage. Expression measurements using single tag counting provided advantages for assessing gene expression and for detecting short RNAs relative to multi-read protocols. Detection of short RNAs was also hampered by RNA fragmentation. Thus, this work will help researchers choose from among a range of options when analyzing gene expression, each with its own advantages and disadvantages

Comprehensive Genomic Profiling of Pancreatic Acinar Cell Carcinomas

significantly enriched for genomic alterations (GAs) causing inactivation of DNA repair genes (45%); these GAs have been associated with sensitivity to platinum-based therapies and PARP inhibitors. Collectively, these results identify potentially actionable GAs in the majority of PACCs, and provide a rationale for using personalized therapies in this disease. Statement of Significance PACC is genomically distinct from other pancreatic cancers. Fusions in RAF genes and mutually exclusive inactivation of DNA repair genes represent novel potential therapeutic targets that are altered in over two-thirds of these tumors

Optimization Problems in Design of Oligonucleotides for

This research thesis was done under the supervision of Dr. Zohar Yakhini in th

Melatonin for treatment of sundowning in elderly persons with dementia - a preliminary study. Arch Gerontol Geriatr 2000; 31

Abstract This pilot study investigated the impact of melatonin administration as a clinical intervention for improving sleep and alleviating sundowning in 11 elderly nursing home residents who suffer from dementia. Melatonin is a hormone produced and secreted by the pineal gland in response to darkness, which plays a major role in the induction and regulation of sleep. Melatonin production decreases with age. Age-related sleep disorders are frequently associated with disruption of circadian cycle rhythms, and sometimes with &apos;sundowning&apos;. Sundowning refers to the manifestation of agitation and/or confusion in the evening hours. Agitation has been linked to sleep disorders. Analysis revealed a significant decrease in agitated behaviors in all three shifts, and a significant decrease in daytime sleepiness. There was a nonsignificant decrease in latency (time to fall asleep) during the evening shift and no significant changes were reported in night-time sleep ratings. The results of this study are important, because finding ways of decreasing sundowning in elderly persons may improve their well being, alleviate the burden of the caregivers, and even enable caregiving in a less restrictive environment