Inferring transcription factor complexes from ChIP-seq data

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) allows researchers to determine the genome-wide binding locations of individual transcription factors (TFs) at high resolution. This information can be interrogated to study various aspects of TF behaviour, including the mechanisms that control TF binding. Physical interaction between TFs comprises one important aspect of TF binding in eukaryotes, mediating tissue-specific gene expression. We have developed an algorithm, spaced motif analysis (SpaMo), which is able to infer physical interactions between the given TF and TFs bound at neighbouring sites at the DNA interface. The algorithm predicts TF interactions in half of the ChIP-seq data sets we test, with the majority of these predictions supported by direct evidence from the literature or evidence of homodimerization. High resolution motif spacing information obtained by this method can facilitate an improved understanding of individual TF complex structures. SpaMo can assist researchers in extracting maximum information relating to binding mechanisms from their TF ChIP-seq data. SpaMo is available for download and interactive use as part of the MEME Suite (http://meme.nbcr.net)

A code for transcription initiation in mammalian genomes

Genome-wide detection of transcription start sites (TSSs) has revealed that RNA Polymerase II transcription initiates at millions of positions in mammalian genomes. Most core promoters do not have a single TSS, but an array of closely located TSSs with different rates of initiation. As a rule, genes have more than one such core promoter; however, defining the boundaries between core promoters is not trivial. These discoveries prompt a re-evaluation of our models for transcription initiation. We describe a new framework for understanding the organization of transcription initiation. We show that initiation events are clustered on the chromosomes at multiple scales-clusters within clusters-indicating multiple regulatory processes. Within the smallest of such clusters, which can be interpreted as core promoters, the local DNA sequence predicts the relative transcription start usage of each nucleotide with a remarkable 91% accuracy, implying the existence of a DNA code that determines TSS selection. Conversely, the total expression strength of such clusters is only partially determined by the local DNA sequence. Thus, the overall control of transcription can be understood as a combination of large- and small-scale effects; the selection of transcription start sites is largely governed by the local DNA sequence, whereas the transcriptional activity of a locus is regulated at a different level; it is affected by distal features or events such as enhancers and chromatin remodeling

Gentle Masking of Low-Complexity Sequences Improves Homology Search

Detection of sequences that are homologous, i.e. descended from a common ancestor, is a fundamental task in computational biology. This task is confounded by low-complexity tracts (such as atatatatatat), which arise frequently and independently, causing strong similarities that are not homologies. There has been much research on identifying low-complexity tracts, but little research on how to treat them during homology search. We propose to find homologies by aligning sequences with “gentle” masking of low-complexity tracts. Gentle masking means that the match score involving a masked letter is , where is the unmasked score. Gentle masking slightly but noticeably improves the sensitivity of homology search (compared to “harsh” masking), without harming specificity. We show examples in three useful homology search problems: detection of NUMTs (nuclear copies of mitochondrial DNA), recruitment of metagenomic DNA reads to reference genomes, and pseudogene detection. Gentle masking is currently the best way to treat low-complexity tracts during homology search

Dynamic usage of transcription start sites within core promoters

BACKGROUND: Mammalian promoters do not initiate transcription at single, well defined base pairs, but rather at multiple, alternative start sites spread across a region. We previously characterized the static structures of transcription start site usage within promoters at the base pair level, based on large-scale sequencing of transcript 5' ends. RESULTS: In the present study we begin to explore the internal dynamics of mammalian promoters, and demonstrate that start site selection within many mouse core promoters varies among tissues. We also show that this dynamic usage of start sites is associated with CpG islands, broad and multimodal promoter structures, and imprinting. CONCLUSION: Our results reveal a new level of biologic complexity within promoters - fine-scale regulation of transcription starting events at the base pair level. These events are likely to be related to epigenetic transcriptional regulation

RECLU:a pipeline to discover reproducible transcriptional start sites and their alternative regulation using capped analysis of gene expression (CAGE)

BACKGROUND: Next generation sequencing based technologies are being extensively used to study transcriptomes. Among these, cap analysis of gene expression (CAGE) is specialized in detecting the most 5’ ends of RNA molecules. After mapping the sequenced reads back to a reference genome CAGE data highlights the transcriptional start sites (TSSs) and their usage at a single nucleotide resolution. RESULTS: We propose a pipeline to group the single nucleotide TSS into larger reproducible peaks and compare their usage across biological states. Importantly, our pipeline discovers broad peaks as well as the fine structure of individual transcriptional start sites embedded within them. We assess the performance of our approach on a large CAGE datasets including 156 primary cell types and two cell lines with biological replicas. We demonstrate that genes have complicated structures of transcription initiation events. In particular, we discover that narrow peaks embedded in broader regions of transcriptional activity can be differentially used even if the larger region is not. CONCLUSIONS: By examining the reproducible fine scaled organization of TSS we can detect many differentially regulated peaks undetected by previous approaches

Incorporating sequence quality data into alignment improves DNA read mapping

New DNA sequencing technologies have achieved breakthroughs in throughput, at the expense of higher error rates. The primary way of interpreting biological sequences is via alignment, but standard alignment methods assume the sequences are accurate. Here, we describe how to incorporate the per-base error probabilities reported by sequencers into alignment. Unlike existing tools for DNA read mapping, our method models both sequencer errors and real sequence differences. This approach consistently improves mapping accuracy, even when the rate of real sequence difference is only 0.2%. Furthermore, when mapping Drosophila melanogaster reads to the Drosophila simulans genome, it increased the amount of correctly mapped reads from 49 to 66%. This approach enables more effective use of DNA reads from organisms that lack reference genomes, are extinct or are highly polymorphic

Clusters of internally primed transcripts reveal novel long noncoding RNAs

Non- protein- coding RNAs ( ncRNAs) are increasingly being recognized as having important regulatory roles. Although much recent attention has focused on tiny 22- to 25- nucleotide microRNAs, several functional ncRNAs are orders of magnitude larger in size. Examples of such macro ncRNAs include Xist and Air, which in mouse are 18 and 108 kilobases ( Kb), respectively. We surveyed the 102,801 FANTOM3 mouse cDNA clones and found that Air and Xist were present not as single, full- length transcripts but as a cluster of multiple, shorter cDNAs, which were unspliced, had little coding potential, and were most likely primed from internal adenine- rich regions within longer parental transcripts. We therefore conducted a genome- wide search for regional clusters of such cDNAs to find novel macro ncRNA candidates. Sixty- six regions were identified, each of which mapped outside known protein- coding loci and which had a mean length of 92 Kb. We detected several known long ncRNAs within these regions, supporting the basic rationale of our approach. In silico analysis showed that many regions had evidence of imprinting and/ or antisense transcription. These regions were significantly associated with microRNAs and transcripts from the central nervous system. We selected eight novel regions for experimental validation by northern blot and RT- PCR and found that the majority represent previously unrecognized noncoding transcripts that are at least 10 Kb in size and predominantly localized in the nucleus. Taken together, the data not only identify multiple new ncRNAs but also suggest the existence of many more macro ncRNAs like Xist and Air

The Abundance of Short Proteins in the Mammalian Proteome

Short proteins play key roles in cell signalling and other processes, but their abundance in the mammalian proteome is unknown. Current catalogues of mammalian proteins exhibit an artefactual discontinuity at a length of 100 aa, so that protein abundance peaks just above this length and falls off sharply below it. To clarify the abundance of short proteins, we identify proteins in the FANTOM collection of mouse cDNAs by analysing synonymous and non-synonymous substitutions with the computer program CRITICA. This analysis confirms that there is no real discontinuity at length 100. Roughly 10% of mouse proteins are shorter than 100 aa, although the majority of these are variants of proteins longer than 100 aa. We identify many novel short proteins, including a “dark matter” subset containing ones that lack detectable homology to other known proteins. Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway