ARGO: a web system for the detection of degenerate motifs and large-scale recognition of eukaryotic promoters

Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.

The context signals of mitochondrial miRNAs (mitomiRs) of mammals

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the post-transcriptional level in the cytoplasm and play an important role in a wide range of biological processes. Recent studies have found that the miRNA sequences are presented not only in the cytoplasm, but also in the mitochondria. These miRNAs (the so-called mitomiRs) may be the sequences of nuclear or mitochondrial origin; some of them are involved in regulation of the mitochondrial gene functions, while the role of others is still unknown. The identification of nucleotide signals, which are unique to mitomiRs, may help to determine this role. We formed a dataset that combined the experimentally discovered mitomiRs in human, rat and mouse. To isolate signals that may be responsible for the mitomiRs' functions or for their translocation from or into mitochondria a context analysis was carried out for the sequences. For three species in the group mitomiRs/non-mitomiRs and the group of all miRNAs from the miRBase database statistically overrepresented 8-letter motifs were identified (p-value < 0.01 with Bonferroni correction for multiple comparisons), for these motifs the patterns of the localization in functionally important regions for different types of miRNAs were found. Also, for the group mitomiRs/non-mitomiRs we found the statistically significant features of the miRNA nucleotide context near the Dicer and Drosha cleavage sites (Pearson's χ2 test of independence for the first three positions of the miRNA, p-value < 0.05). The observed nucleotide frequencies may indicate a more homogeneous pri-miRNA cleavage by the Drosha complex during the formation of the 5' end of mitomiRs. The obtained results can help to determine the role of the nucleotide signals in the origin, processing, and functions of the mitomiRs.

Advances in the Bioinformatics Knowledge of mRNA Polyadenylation in Baculovirus Genes

Baculoviruses are a group of insect viruses with large circular dsDNA genomes exploited in numerous biotechnological applications, such as the biological control of agricultural pests, the expression of recombinant proteins or the gene delivery of therapeutic sequences in mammals, among others. Their genomes encode between 80 and 200 proteins, of which 38 are shared by all reported species. Thanks to multi-omic studies, there is remarkable information about the baculoviral proteome and the temporality in the virus gene expression. This allows some functional elements of the genome to be very well described, such as promoters and open reading frames. However, less information is available about the transcription termination signals and, consequently, there are still imprecisions about what are the limits of the transcriptional units present in the baculovirus genomes and how is the processing of the 3′ end of viral mRNA. Regarding to this, in this review we provide an update about the characteristics of DNA signals involved in this process and we contribute to their correct prediction through an exhaustive analysis that involves bibliography information, data mining, RNA structure and a comprehensive study of the core gene 3′ ends from 180 baculovirus genomes.

Argo_CUDA: Exhaustive GPU based approach for motif discovery in large DNA datasets

The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top "peak" ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites.

Searching maximal degenerate motifs guided by a compact suffix tree

Compared to a mismatched consensus motif, a degenerate consensus motif is more suitable for modeling position-specific variations within motifs. In the literature, the state-of-art methods using degenerate consensus motifs for de novo motif finding use a naïve enumeration algorithm, which is far from efficient. In this paper, we propose an efficient algorithm to extract maximal degenerate consensus motifs from a set of sequences based on a compact suffix tree. Our algorithm achieved a time complexity about [Formula: see text] times lower than that of a naïve enumeration, where [Formula: see text] is the average length of source sequences. To demonstrate the efficiency and effectiveness of our proposed algorithm, we applied it to finding transcription factor binding sites. It is validated on a popular benchmark proposed by Tompa. The executable files of our algorithm can be accessed through http://hpc.cs.tsinghua.edu.cn/bioinfo.

The importance and identification of regulatory polymorphisms and their mechanisms of action

The search for the genetic variations underlying all human phenotypes is in its infancy but must be one of the long term goals of the scientific community. There is evidence that most, if not all human phenotypes, including illnesses are influenced by the genetic makeup of the individual. There are an estimated 11 million human genetic polymorphisms with a minor allele frequency >1% and possibly many times that number of rare sequence variants. The proportion of these sequence variants which have any functional effect is unknown but it is likely that the majority of those which influence illness lie outside of the amino acid coding regions of genes, and affect the regulation of gene expression--these are called rSNPs. Recent research suggests that about 50% of genes have one or more common rSNPs associated with them and probably most if not all genes have an rSNP within the human population. In the long term, determining which polymorphisms are potentially functional must be done bio-informatically using algorithms based upon experimental data. However, at the current time, the limited data that has been obtained does not allow the creation of such an algorithm. In vitro studies suggest that a large proportion of rSNPs lie within the core and proximal promoter regions of genes but it is not clear how the majority of these influence transcription, as they do not appear to be within any known transcription factor binding sites. However, promoter regions possess a number of sequence-dependent characteristics which make them distinct from the rest of the genome, namely stability, curvature and flexibility. Subtle changes to these features may underlie the mechanisms by which many polymorphisms exert their function.