NGSView: an extensible open source editor for next-generation sequencing data.

Summary: High-throughput sequencing technologies introduce novel demands on tools available for data analysis. We have developed NGSView (Next Generation Sequence View), a generally applicable, flexible and extensible next-generation sequence alignment editor. The software allows for visualization and manipulation of millions of sequences simultaneously on a desktop computer, through a graphical interface.

Development of a high-throughput method for the systematic identification of human proteins nuclear translocation potential.

Background: Important clues to the function of novel and uncharacterized proteins can be obtained by identifying their ability to translocate in the nucleus. In addition, a comprehensive definition of the nuclear proteome undoubtedly represents a key step toward a better understanding of the biology of this organelle. Although several high-throughput experimental methods have been developed to explore the sub-cellular localization of proteins, these methods tend to focus on the predominant localizations of gene products and may fail to provide a complete catalog of proteins that are able to transiently locate into the nucleus.

SDRF2GRAPH: a visualization tool of a spreadsheet-based description of experimental processes.

Background: As larger datasets are produced with the development of genome-scale experimental techniques, it has become essential to explicitly describe the meta-data (information describing the data) generated by an experiment. The experimental process is a part of the meta-data required to interpret the produced data, and SDRF (Sample and Data Relationship Format) supports its description in a spreadsheet or tab-delimited file. This format was primarily developed to describe microarray studies in MAGE-tab, and it is being applied in a broader context in ISA-tab.

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network.

Genome-wide investigation of in vivo EGR-1 binding sites in monocytic differentiation.

Background: Immediate early genes are considered to play important roles in dynamic gene regulatory networks following exposure to appropriate stimuli. One of the immediate early genes, early growth response gene 1 (EGR-1), has been implicated in differentiation of human monoblastoma cells along the monocytic commitment following treatment with phorbol ester. EGR-1 has been thought to work as a modifier of monopoiesis, but the precise function of EGR-1 in monocytic differentiation has not been fully elucidated.

The FANTOM web resource: from mammalian transcriptional landscape to its dynamic regulation.

In FANTOM4, an international collaborative research project, we collected a wide range of genome-scale data, including 24 million mRNA 5'-reads (CAGE tags) and microarray expression profiles along a differentiation time course of the human THP-1 cell line and under 52 systematic siRNA perturbations. In addition, data regarding chromatin status derived from ChIP-chip to elucidate the transcriptional regulatory interactions are included. Here we present these data to the research community as an integrated web resource.

FANTOM4 EdgeExpressDB: an integrated database of promoters, genes, microRNAs, expression dynamics and regulatory interactions.

EdgeExpressDB is a novel database and set of interfaces for interpreting biological networks and comparing large high-throughput expression datasets that requires minimal development for new data types and search patterns. The FANTOM4 EdgeExpress database http://fantom.gsc.

Identification of DNA regions and a set of transcriptional regulatory factors involved in transcriptional regulation of several human liver-enriched transcription factor genes.

Mammalian tissue- and/or time-specific transcription is primarily regulated in a combinatorial fashion through interactions between a specific set of transcriptional regulatory factors (TRFs) and their cognate cis-regulatory elements located in the regulatory regions. In exploring the DNA regions and TRFs involved in combinatorial transcriptional regulation, we noted that individual knockdown of a set of human liver-enriched TRFs such as HNF1A, HNF3A, HNF3B, HNF3G and HNF4A resulted in perturbation of the expression of several single TRF genes, such as HNF1A, HNF3G and CEBPA genes. We thus searched the potential binding sites for these five TRFs in the highly conserved genomic regions around these three TRF genes and found several putative combinatorial regulatory regions.

Non-coding RNA transcription: turning on neighbours.

Even though less than 2% of the mammalian genome encodes proteins, a significant fraction can be transcribed into non-coding RNAs. An elegant study identifies a function for non-coding RNA transcription in activating neighbouring genes.