Michael Hackenberg

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/.

miRanalyzer: an update on the detection and analysis of microRNAs in high-throughput sequencing experiments

We present a new version of miRanalyzer, a web server and stand-alone tool for the detection of known and prediction of new microRNAs in high-throughput sequencing experiments. The new version has been notably improved regarding speed, scope and available features. Alignments are now based on the ultrafast short-read aligner Bowtie (granting also colour space support, allowing mismatches and improving speed) and 31 genomes, including 6 plant genomes, can now be analysed (previous version contained only 7). Differences between plant and animal microRNAs have been taken into account for the prediction models and differential expression of both, known and predicted microRNAs, between two conditions can be calculated. Additionally, consensus sequences of predicted mature and precursor microRNAs can be obtained from multiple samples, which increases the reliability of the predicted microRNAs. Finally, a stand-alone version of the miRanalyzer that is based on a local and easily customized database is also available; this allows the user to have more control on certain parameters as well as to use specific data such as unpublished assemblies or other libraries that are not available in the web server. miRanalyzer is available at http://bioinfo2.ugr.es/miRanalyzer/miRanalyzer.php.

CpGcluster: a distance-based algorithm for CpG-island detection

BackgroundDespite their involvement in the regulation of gene expression and their importance as genomic markers for promoter prediction, no objective standard exists for defining CpG islands (CGIs), since all current approaches rely on a large parameter space formed by the thresholds of length, CpG fraction and G+C content.ResultsGiven the higher frequency of CpG dinucleotides at CGIs, as compared to bulk DNA, the distance distributions between neighboring CpGs should differ for bulk and island CpGs. A new algorithm (CpGcluster) is presented, based on the physical distance between neighboring CpGs on the chromosome and able to predict directly clusters of CpGs, while not depending on the subjective criteria mentioned above. By assigning a p-value to each of these clusters, the most statistically significant ones can be predicted as CGIs. CpGcluster was benchmarked against five other CGI finders by using a test sequence set assembled from an experimental CGI library. CpGcluster reached the highest overall accuracy values, while showing the lowest rate of false-positive predictions. Since a minimum-length threshold is not required, CpGcluster can find short but fully functional CGIs usually missed by other algorithms. The CGIs predicted by CpGcluster present the lowest degree of overlap with Alu retrotransposons and, simultaneously, the highest overlap with vertebrate Phylogenetic Conserved Elements (PhastCons). CpGclusters CGIs overlapping with the Transcription Start Site (TSS) show the highest statistical significance, as compared to the islands in other genome locations, thus qualifying CpGcluster as a valuable tool in discriminating functional CGIs from the remaining islands in the bulk genome.ConclusionCpGcluster uses only integer arithmetic, thus being a fast and computationally efficient algorithm able to predict statistically significant clusters of CpG dinucleotides. Another outstanding feature is that all predicted CGIs start and end with a CpG dinucleotide, which should be appropriate for a genomic feature whose functionality is based precisely on CpG dinucleotides. The only search parameter in CpGcluster is the distance between two consecutive CpGs, in contrast to previous algorithms. Therefore, none of the main statistical properties of CpG islands (neither G+C content, CpG fraction nor length threshold) are needed as search parameters, which may lead to the high specificity and low overlap with spurious Alu elements observed for CpGcluster predictions.

sRNAtoolbox: an integrated collection of small RNA research tools

Small RNA research is a rapidly growing field. Apart from microRNAs, which are important regulators of gene expression, other types of functional small RNA molecules have been reported in animals and plants. MicroRNAs are important in host-microbe interactions and parasite microRNAs might modulate the innate immunity of the host. Furthermore, small RNAs can be detected in bodily fluids making them attractive non-invasive biomarker candidates. Given the general broad interest in small RNAs, and in particular microRNAs, a large number of bioinformatics aided analysis types are needed by the scientific community. To facilitate integrated sRNA research, we developed sRNAtoolbox, a set of independent but interconnected tools for expression profiling from high-throughput sequencing data, consensus differential expression, target gene prediction, visual exploration in a genome context as a function of read length, gene list analysis and blast search of unmapped reads. All tools can be used independently or for the exploration and downstream analysis of sRNAbench results. Workflows like the prediction of consensus target genes of parasite microRNAs in the host followed by the detection of enriched pathways can be easily established. The web-interface interconnecting all these tools is available at http://bioinfo5.ugr.es/srnatoolbox

IsoFinder: computational prediction of isochores in genome sequences

Isochores are long genome segments homogeneous in G+C. Here, we describe an algorithm (IsoFinder) running on the web (http://bioinfo2.ugr.es/IsoF/isofinder.html) able to predict isochores at the sequence level. We move a sliding pointer from left to right along the DNA sequence. At each position of the pointer, we compute the mean G+C values to the left and to the right of the pointer. We then determine the position of the pointer for which the difference between left and right mean values (as measured by the t-statistic) reaches its maximum. Next, we determine the statistical significance of this potential cutting point, after filtering out short-scale heterogeneities below 3 kb by applying a coarse-graining technique. Finally, the program checks whether this significance exceeds a probability threshold. If so, the sequence is cut at this point into two subsequences; otherwise, the sequence remains undivided. The procedure continues recursively for each of the two resulting subsequences created by each cut. This leads to the decomposition of a chromosome sequence into long homogeneous genome regions (LHGRs) with well-defined mean G+C contents, each significantly different from the G+C contents of the adjacent LHGRs. Most LHGRs can be identified with Bernardis isochores, given their correlation with biological features such as gene density, SINE and LINE (short, long interspersed repetitive elements) densities, recombination rate or single nucleotide polymorphism variability. The resulting isochore maps are available at our web site (http://bioinfo2.ugr.es/isochores/), and also at the UCSC Genome Browser (http://genome.cse.ucsc.edu/).

A Comprehensive Expression Profile of MicroRNAs and Other Classes of Non-Coding Small RNAs in Barley Under Phosphorous-Deficient and -Sufficient Conditions

Phosphorus (P) is essential for plant growth. MicroRNAs (miRNAs) play a key role in phosphate homeostasis. However, little is known about P effect on miRNA expression in barley (Hordeum vulgare L.). In this study, we used Illuminas next-generation sequencing technology to sequence small RNAs (sRNAs) in barley grown under P-deficient and P-sufficient conditions. We identified 221 conserved miRNAs and 12 novel miRNAs, of which 55 were only present in P-deficient treatment while 32 only existed in P-sufficient treatment. Total 47 miRNAs were significantly differentially expressed between the two P treatments (|log2| > 1). We also identified many other classes of sRNAs, including sense and antisense sRNAs, repeat-associated sRNAs, transfer RNA (tRNA)-derived sRNAs and chloroplast-derived sRNAs, and some of which were also significantly differentially expressed between the two P treatments. Of all the sRNAs identified, antisense sRNAs were the most abundant sRNA class in both P treatments. Surprisingly, about one-fourth of sRNAs were derived from the chloroplast genome, and a chloroplast-encoded tRNA-derived sRNA was the most abundant sRNA of all the sRNAs sequenced. Our data provide valuable clues for understanding the properties of sRNAs and new insights into the potential roles of miRNAs and other classes of sRNAs in the control of phosphate homeostasis.

Differential expression of microRNAs and other small RNAs in barley between water and drought conditions

Drought is a major constraint to crop production, and microRNAs (miRNAs) play an important role in plant drought tolerance. Analysis of miRNAs and other classes of small RNAs (sRNAs) in barley grown under water and drought conditions reveals that drought selectively regulates expression of miRNAs and other classes of sRNAs. Low-expressed miRNAs and all repeat-associated siRNAs (rasiRNAs) tended towards down-regulation, while tRNA-derived sRNAs (tsRNAs) had the tendency to be up-regulated, under drought. Antisense sRNAs (putative siRNAs) did not have such a tendency under drought. In drought-tolerant transgenic barley overexpressing DREB transcription factor, most of the low-expressed miRNAs were also down-regulated. In contrast, tsRNAs, rasiRNAs and other classes of sRNAs were not consistently expressed between the drought-treated and transgenic plants. The differential expression of miRNAs and siRNAs was further confirmed by Northern hybridization and quantitative real-time PCR (qRT-PCR). Targets of the drought-regulated miRNAs and siRNAs were predicted, identified by degradome libraries and confirmed by qRT-PCR. Their functions are diverse, but most are involved in transcriptional regulation. Our data provide insight into the expression profiles of miRNAs and other sRNAs, and their relationship under drought, thereby helping understand how miRNAs and sRNAs respond to drought stress in cereal crops.

Isochore chromosome maps of the human genome

The human genome is a mosaic of isochores, which are long DNA segments (z.Gt;300 kbp) relatively homogeneous in G+C. Human isochores were first identified by density-gradient ultracentrifugation of bulk DNA, and differ in important features, e.g. genes are found predominantly in the GC-richest isochores. Here, we use a reliable segmentation method to partition the longest contigs in the human genome draft sequence into long homogeneous genome regions (LHGRs), thereby revealing the isochore structure of the human genome. The advantages of the isochore maps presented here are: (1) sequence heterogeneities at different scales are shown in the same plot; (2) pair-wise compositional differences between adjacent regions are all statistically significant; (3) isochore boundaries are accurately defined to single base pair resolution; and (4) both gradual and abrupt isochore boundaries are simultaneously revealed. Taking advantage of the wide sample of genome sequence analyzed, we investigate the correspondence between LHGRs and true human isochores revealed through DNA centrifugation. LHGRs show many of the typical isochore features, mainly size distribution, G+C range, and proportions of the isochore classes. The relative density of genes, Alu and long interspersed nuclear element repeats and the different types of single nucleotide polymorphisms on LHGRs also coincide with expectations in true isochores. Potential applications of isochore maps range from the improvement of gene-finding algorithms to the prediction of linkage disequilibrium levels in association studies between marker genes and complex traits. The coordinates for the LHGRs identified in all the contigs longer than 2 Mb in the human genome sequence are available at the online resource on isochore mapping: http://bioinfo2.ugr.es/isochores.

Characterization of phosphorus-regulated miR399 and miR827 and their isomirs in barley under phosphorus-sufficient and phosphorus-deficient conditions

BackgroundmiR399 and miR827 are both involved in conserved phosphorus (P) deficiency signalling pathways. miR399 targets the PHO2 gene encoding E2 enzyme that negatively regulates phosphate uptake and root-to-shoot allocation, while miR827 targets SPX-domain-containing genes that negatively regulate other P-responsive genes. However, the response of miR399 and miR827 to P conditions in barley has not been investigated.ResultsIn this study, we investigated the expression profiles of miR399 and miR827 in barley (Hordeum vulagre L.) under P-deficient and P-sufficient conditions. We identified 10 members of the miR399 family and one miR827 gene in barley, all of which were significantly up-regulated under deficient P. In addition, we found many isomirs of the miR399 family and miR827, most of which were also significantly up-regulated under deficient P. Several isomirs of miR399 members were found to be able to cleave their predicted targets in vivo. Surprisingly, a few small RNAs (sRNAs) derived from the single-stranded loops of the hairpin structures of MIR399b and MIR399e-1 were also found to be able to cleave their predicted targets in vivo. Many antisense sRNAs of miR399 and a few for miR827 were also detected, but they did not seem to be regulated by P. Intriguingly, the lowest expressed member, hvu-miR399k, had four-fold more antisense sRNAs than sense sRNAs, and furthermore under P sufficiency, the antisense sRNAs are more frequent than the sense sRNAs. We identified a potential regulatory network among miR399, its target HvPHO2 and target mimics HvIPS1 and HvIPS2 in barley under P-deficient and P-sufficient conditions.ConclusionsOur data provide an important insight into the mechanistic regulation and function of miR399, miR827 and their isomirs in barley under different P conditions.

A Systems Level Analysis Reveals Transcriptomic and Proteomic Complexity in Ixodes Ricinus Midgut and Salivary Glands During Early Attachment and Feeding

Although pathogens are usually transmitted within the first 24–48 h of attachment of the castor bean tick Ixodes ricinus, little is known about the ticks biological responses at these earliest phases of attachment. Tick midgut and salivary glands are the main tissues involved in tick blood feeding and pathogen transmission but the limited genomic information for I. ricinus delays the application of high-throughput methods to study their physiology. We took advantage of the latest advances in the fields of Next Generation RNA-Sequencing and Label-free Quantitative Proteomics to deliver an unprecedented, quantitative description of the gene expression dynamics in the midgut and salivary glands of this disease vector upon attachment to the vertebrate host. A total of 373 of 1510 identified proteins had higher expression in the salivary glands, but only 110 had correspondingly high transcript levels in the same tissue. Furthermore, there was midgut-specific expression of 217 genes at both the transcriptome and proteome level. Tissue-dependent transcript, but not protein, accumulation was revealed for 552 of 885 genes. Moreover, we discovered the enrichment of tick salivary glands in proteins involved in gene transcription and translation, which agrees with the secretory role of this tissue; this finding also agrees with our finding of lower tick t-RNA representation in the salivary glands when compared with the midgut. The midgut, in turn, is enriched in metabolic components and proteins that support its mechanical integrity in order to accommodate and metabolize the ingested blood. Beyond understanding the physiological events that support hematophagy by arthropod ectoparasites, we discovered more than 1500 proteins located at the interface between ticks, the vertebrate host, and the tick-borne pathogens. Thus, our work significantly improves the knowledge of the genetics underlying the transmission lifecycle of this tick species, which is an essential step for developing alternative methods to better control tick-borne diseases.