Partitioning circadian transcription by SIRT6 leads to segregated control of cellular metabolism.

Circadian rhythms are intimately linked to cellular metabolism. Specifically, the NAD(+)-dependent deacetylase SIRT1, the founding member of the sirtuin family, contributes to clock function. Whereas SIRT1 exhibits diversity in deacetylation targets and subcellular localization, SIRT6 is the only constitutively chromatin-associated sirtuin and is prominently present at transcriptionally active genomic loci. Comparison of the hepatic circadian transcriptomes reveals that SIRT6 and SIRT1 separately control transcriptional specificity and therefore define distinctly partitioned classes of circadian genes. SIRT6 interacts with CLOCK:BMAL1 and, differently from SIRT1, governs their chromatin recruitment to circadian gene promoters. Moreover, SIRT6 controls circadian chromatin recruitment of SREBP-1, resulting in the cyclic regulation of genes implicated in fatty acid and cholesterol metabolism. This mechanism parallels a phenotypic disruption in fatty acid metabolism in SIRT6 null mice as revealed by circadian metabolome analyses. Thus, genomic partitioning by two independent sirtuins contributes to differential control of circadian metabolism.

Retrotransposon profiling of RNA polymerase III initiation sites.

Although retroviruses are relatively promiscuous in choice of integration sites, retrotransposons can display marked integration specificity. In yeast and slime mold, some retrotransposons are associated with tRNA genes (tDNAs). In the Saccharomyces cerevisiae genome, the long terminal repeat retrotransposon Ty3 is found at RNA polymerase III (Pol III) transcription start sites of tDNAs. Ty1, 2, and 4 elements also cluster in the upstream regions of these genes. To determine the extent to which other Pol III-transcribed genes serve as genomic targets for Ty3, a set of 10,000 Ty3 genomic retrotranspositions were mapped using high-throughput DNA sequencing. Integrations occurred at all known tDNAs, two tDNA relics (iYGR033c and ZOD1), and six non-tDNA, Pol III-transcribed types of genes (RDN5, SNR6, SNR52, RPR1, RNA170, and SCR1). Previous work in vitro demonstrated that the Pol III transcription factor (TF) IIIB is important for Ty3 targeting. However, seven loci that bind the TFIIIB loader, TFIIIC, were not targeted, underscoring the unexplained absence of TFIIIB at those sites. Ty3 integrations also occurred in two open reading frames not previously associated with Pol III transcription, suggesting the existence of a small number of additional sites in the yeast genome that interact with Pol III transcription complexes.

MotifMap: integrative genome-wide maps of regulatory motif sites for model species.

BACKGROUND: A central challenge of biology is to map and understand gene regulation on a genome-wide scale. For any given genome, only a small fraction of the regulatory elements embedded in the DNA sequence have been characterized, and there is great interest in developing computational methods to systematically map all these elements and understand their relationships. Such computational efforts, however, are significantly hindered by the overwhelming size of non-coding regions and the statistical variability and complex spatial organizations of regulatory elements and interactions. Genome-wide catalogs of regulatory elements for all model species simply do not yet exist. RESULTS: The MotifMap system uses databases of transcription factor binding motifs, refined genome alignments, and a comparative genomic statistical approach to provide comprehensive maps of candidate regulatory elements encoded in the genomes of model species. The system is used to derive new genome-wide maps for yeast, fly, worm, mouse, and human. The human map contains 519,108 sites for 570 matrices with a False Discovery Rate of 0.1 or less. The new maps are assessed in several ways, for instance using high-throughput experimental ChIP-seq data and AUC statistics, providing strong evidence for their accuracy and coverage. The maps can be usefully integrated with many other kinds of omic data and are available at http://motifmap.igb.uci.edu/. CONCLUSIONS: MotifMap and its integration with other data provide a foundation for analyzing gene regulation on a genome-wide scale, and for automatically generating regulatory pathways and hypotheses. The power of this approach is demonstrated and discussed using the P53 apoptotic pathway and the Gli hedgehog pathways as examples.

Data structures and compression algorithms for high-throughput sequencing technologies.

BACKGROUND: High-throughput sequencing (HTS) technologies play important roles in the life sciences by allowing the rapid parallel sequencing of very large numbers of relatively short nucleotide sequences, in applications ranging from genome sequencing and resequencing to digital microarrays and ChIP-Seq experiments. As experiments scale up, HTS technologies create new bioinformatics challenges for the storage and sharing of HTS data. RESULTS: We develop data structures and compression algorithms for HTS data. A processing stage maps short sequences to a reference genome or a large table of sequences. Then the integers representing the short sequence absolute or relative addresses, their length, and the substitutions they may contain are compressed and stored using various entropy coding algorithms, including both old and new fixed codes (e.g Golomb, Elias Gamma, MOV) and variable codes (e.g. Huffman). The general methodology is illustrated and applied to several HTS data sets. Results show that the information contained in HTS files can be compressed by a factor of 10 or more, depending on the statistical properties of the data sets and various other choices and constraints. Our algorithms fair well against general purpose compression programs such as gzip, bzip2 and 7zip; timing results show that our algorithms are consistently faster than the best general purpose compression programs. CONCLUSIONS: It is not likely that exactly one encoding strategy will be optimal for all types of HTS data. Different experimental conditions are going to generate various data distributions whereby one encoding strategy can be more effective than another. We have implemented some of our encoding algorithms into the software package GenCompress which is available upon request from the authors. With the advent of HTS technology and increasingly new experimental protocols for using the technology, sequence databases are expected to continue rising in size. The methodology we have proposed is general, and these advanced compression techniques should allow researchers to manage and share their HTS data in a more timely fashion.

MotifMap: a human genome-wide map of candidate regulatory motif sites.

MOTIVATION: Achieving a comprehensive map of all the regulatory elements encoded in the human genome is a fundamental challenge of biomedical research. So far, only a small fraction of the regulatory elements have been characterized, and there is great interest in applying computational techniques to systematically discover these elements. Such efforts, however, have been significantly hindered by the overwhelming size of non-coding DNA regions and the statistical variability and complex spatial organizations of mammalian regulatory elements. RESULTS: Here we combine information from multiple mammalian genomes to derive the first fairly comprehensive map of regulatory elements in the human genome. We develop a procedure for identifying regulatory sites, with high levels of conservation across different species, using a new scoring scheme, the Bayesian branch length score (BBLS). Using BBLS, we predict 1.5 million regulatory sites, corresponding to 380 known regulatory motifs, with an estimated false discovery rate (FDR) of <50%. We demonstrate that the method is particularly effective for 155 motifs, for which 121 056 sites can be mapped with an estimated FDR of <10%. Over 28K SNPs are located in regions overlapping the 1.5 million predicted motif sites, suggesting potential functional implications for these SNPs. We have deposited these elements in a database and created a user-friendly web server for the retrieval, analysis and visualization of these elements. The initial map provides a systematic view of gene regulation in the genome, which will be refined as additional motifs become available.

A Genomic Analysis Pipeline and Its Application to Pediatric Cancers.

We present a cancer genomic analysis pipeline which takes as input sequencing reads for both germline and tumor genomes and outputs filtered lists of all genetic mutations in the form of short ranked list of the most affected genes in the tumor, using either the Complete Genomics or Illumina platforms. A novel reporting and ranking system has been developed that makes use of publicly available datasets and literature specific to each patient, including new methods for using publicly available expression data in the absence of proper control data. Previously implicated small and large variations (including gene fusions) are reported in addition to probable driver mutations. Relationships between cancer and the sequenced tumor genome are highlighted using a network-based approach that integrates known and predicted protein-protein, protein-TF, and protein-drug interaction data. By using an integrative approach, effects of genetic variations on gene expression are used to provide further evidence of driver mutations. This pipeline has been developed with the aim to be used in assisting in the analysis of pediatric tumors, as an unbiased and automated method for interpreting sequencing results along with identifying potentially therapeutic drugs and their targets. We present results that agree with previous literature and highlight specific findings in a few patients.