RCAS: an RNA centric annotation system for transcriptome-wide regions of interest

In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de

HOT or not: examining the basis of high-occupancy target regions

High-occupancy target (HOT) regions are segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and consequently associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solemnly defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed 'hyper-ChIPable' regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers, enrichment of RNA-DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies

FisherMP: fully parallel algorithm for detecting combinatorial motifs from large ChIP-seq datasets.

Detecting binding motifs of combinatorial transcription factors (TFs) from chromatin immunoprecipitation sequencing (ChIP-seq) experiments is an important and challenging computational problem for understanding gene regulations. Although a number of motif-finding algorithms have been presented, most are either time consuming or have sub-optimal accuracy for processing large-scale datasets. In this article, we present a fully parallelized algorithm for detecting combinatorial motifs from ChIP-seq datasets by using Fisher combined method and OpenMP parallel design. Large scale validations on both synthetic data and 350 ChIP-seq datasets from the ENCODE database showed that FisherMP has not only super speeds on large datasets, but also has high accuracy when compared with multiple popular methods. By using FisherMP, we successfully detected combinatorial motifs of CTCF, YY1, MAZ, STAT3 and USF2 in chromosome X, suggesting that they are functional co-players in gene regulation and chromosomal organization. Integrative and statistical analysis of these TF-binding peaks clearly demonstrate that they are not only highly coordinated with each other, but that they are also correlated with histone modifications. FisherMP can be applied for integrative analysis of binding motifs and for predicting cis-regulatory modules from a large number of ChIP-seq datasets

A Protective Role Of Autophagy In A Drosophila Model Of Friedreich\u27s Ataxia (frda)

Friedreich’s ataxia (FRDA) is an inherited autosomal recessive neurodegenerative disease. It affects 1 in every 50,000 people in central Europe and North America. FRDA is caused by deficiency of Frataxin, an essential mitochondrial iron chaperone protein, and the associated oxidative stress damages. Autophagy, a housekeeping process responsible for the bulk degradation and turnover of long half-life proteins and organelles, is featured by the formation of double-membrane vacuoles and lysosomal degradation. Previous researches indicate that Danon’s disease, the inherited neural disorder disease that shares similar symptoms with FRDA, is due to the malfunction of autophagy. Based on this, we raise the question whether the autophagy activity is modified and what is its role in FRDA. Study has shown that oxidative stress may play a major role in the progression of neurodegenerative diseases by attacking the cytoplasmic molecules and organelles, and autophagy is the major pathway in reducing oxidative stress and removal of malfunctioned organelles. Additionally, autophagy has been closely related to cell apoptosis and organism remodeling. Mitochondrial Autophagy (mitophagy) is also the major turnover pathway for damaged mitochondria. Therefore, the dysfunctional autophagy in removing the malfunctioned mitochondria in FRDA may responsible for its pathogenesis. Since the mechanism of autophagy in the development of FRDA is still largely unknown, a systematic analysis of the status and function of autophagy pathway is needed. My thesis is targeting at four goals: (1) to construct FRDA fly model and characterize autophagy expression pattern in each stage; (2) to determine the effect of autophagy modification on the symptoms of the FRDA flies; (3) to identify the potential downstream events of autophagy; (4) to explore the possible upstream activities by examine whether the AMPK or SAPK stress response pathway is involved in FRDA flies. Our hypothesis is the up-regulation of autophagy occurs in the early stage of FRDA and may induce apoptosis or mitophagy. We identified that autophagy level is up-regulated in FRDA flies at both transcriptional and translational levels. Moreover, the overexpression of Frataxin also increases autophagy activity. The comparable Atg5 mRNA level in both Frataxin deficiency and overexpression flies indicates this induction of autophagy in FRDA flies is Atg5 independent. Autophagy inducer Methylene blue and rapamycin could partially prolong the longevity and restore the fertility of FRDA flies, but could not rescue the pupae lethal phenotype. When treated with the autophagy inhibitor chloroquine, FRDA KD flies showed reduced longevity and locomotor activity, implying the beneficial effect of autophagy in certain development stages. The FRDA KD flies also showed up-regulated caspases-3 and cytochrome C level, indicating enhanced apoptosis in cells with reduced Frataxin. We also attempt to apply the heart pacing assay to evaluate the FRDA Drosophila cardiac function. Although the results are inconclusive, the heart pacing assay appears to be a valuable tool for future research

Transcriptional Enhancer Activity of Biochemically Marked Genomic Elements

Functional genomics aspires to explain how a transcription factor (TF) and its measured biochemical occupancy relates to the enhancer activity of the underlying sequence elements. Tissue-specific TFs exhibit remarkable selectivity and reproducibility in the available genome-wide sequence motifs accessed. A consistent central conclusion is that, irrespective of the element selection criteria used, ~50% of candidate Enhancers score as transcriptionally active in both mouse and human cell types, while the remaining 50% of similarly biochemically marked regions are unable to activate transcription on their own. This finding is based on an integrated comparison of a group of functionally assayed elements containing TF-occupied elements, evolutionarily conserved elements, and TF agnostic elements with hallmark biochemical signatures of known enhancers. Quantitatively, the level of TF occupancy signal was the best predictor of the proportion of active enhancers detected, but overall (and contrary to expectation) it is a weak predictor of the magnitude of enhancer activity readout. In specific cell types, elements can display all of the hallmark signatures of enhancers, but can remain inactively poised prior to a stimulus that either activates them or releases a repressive factor. Against previous expectations these poised occupancy sites, once released, behave comparatively in magnitude of enhancer activity as their counterparts that are only directly accessed upon stimulation. Based on our findings, the vast majority of active enhancers in the genome, including some of the most individually powerful ones, are expected to display relatively modest biochemical signatures. Finally, the combined set of over a hundred genomic regions that lacked biochemical marks, even while containing the motifs known to be necessary to bind the relevant TFs, did not support significant enhancer function. We also found evidence that both enhancer orientation and combinations of relatively closely spaced candidate Enhancers, can yield additive functions, with possible fine tuning of the enhancer activity controlled by the type and the distance between individually accessed motifs. In special cases, these elements might cooperate to recruit stable complexes resulting in a synergistic transcriptional activation, suggesting that both local "super-enhancers" and recruited multi-element combinatorics are likely to play an important role in vivo. These findings provide an expectation for enhancer function in the comprehensive annotations provided by the new ENCODE encyclopedia and may help guide future efforts to define the mechanisms by which enhancer activity is achieved and conferred selectively to target genes. Surprisingly, elements that deeply sample the biochemical occupancy of complex loci, match a random population of selected elements remarkably well. Our findings also indicate that carefully designed and lower throughput approaches, rather than high numerical assays that focus on the outstanding features, will bring widely applicable answers to the remaining questions of how relative enhancers are tuned and how seemingly identical regions at a biochemical and motif level are selected for or against function