Christina Backes

GeneTrail—advanced gene set enrichment analysis

We present a comprehensive and efficient gene set analysis tool, called ‘GeneTrail’ that offers a rich functionality and is easy to use. Our web-based application facilitates the statistical evaluation of high-throughput genomic or proteomic data sets with respect to enrichment of functional categories. GeneTrail covers a wide variety of biological categories and pathways, among others KEGG, TRANSPATH, TRANSFAC, and GO. Our web server provides two common statistical approaches, ‘Over-Representation Analysis’ (ORA) comparing a reference set of genes to a test set, and ‘Gene Set Enrichment Analysis’ (GSEA) scoring sorted lists of genes. Besides other newly developed features, GeneTrails statistics module includes a novel dynamic-programming algorithm that improves the P-value computation of GSEA methods considerably. GeneTrail is freely accessible at http://genetrail.bioinf.uni-sb.de

New insights into the Tyrolean Iceman's origin and phenotype as inferred by whole-genome sequencing

The Tyrolean Iceman, a 5,300-year-old Copper age individual, was discovered in 1991 on the Tisenjoch Pass in the Italian part of the Ötztal Alps. Here we report the complete genome sequence of the Iceman and show 100% concordance between the previously reported mitochondrial genome sequence and the consensus sequence generated from our genomic data. We present indications for recent common ancestry between the Iceman and present-day inhabitants of the Tyrrhenian Sea, that the Iceman probably had brown eyes, belonged to blood group O and was lactose intolerant. His genetic predisposition shows an increased risk for coronary heart disease and may have contributed to the development of previously reported vascular calcifications. Sequences corresponding to ~60% of the genome of Borrelia burgdorferi are indicative of the earliest human case of infection with the pathogen for Lyme borreliosis.

A blood based 12-miRNA signature of Alzheimer disease patients.

BackgroundAlzheimer disease (AD) is the most common form of dementia but the identification of reliable, early and non-invasive biomarkers remains a major challenge. We present a novel miRNA-based signature for detecting AD from blood samples.ResultsWe apply next-generation sequencing to miRNAs from blood samples of 48 AD patients and 22 unaffected controls, yielding a total of 140 unique mature miRNAs with significantly changed expression levels. Of these, 82 have higher and 58 have lower abundance in AD patient samples. We selected a panel of 12 miRNAs for an RT-qPCR analysis on a larger cohort of 202 samples, comprising not only AD patients and healthy controls but also patients with other CNS illnesses. These included mild cognitive impairment, which is assumed to represent a transitional period before the development of AD, as well as multiple sclerosis, Parkinson disease, major depression, bipolar disorder and schizophrenia. miRNA target enrichment analysis of the selected 12 miRNAs indicates an involvement of miRNAs in nervous system development, neuron projection, neuron projection development and neuron projection morphogenesis. Using this 12-miRNA signature, we differentiate between AD and controls with an accuracy of 93%, a specificity of 95% and a sensitivity of 92%. The differentiation of AD from other neurological diseases is possible with accuracies between 74% and 78%. The differentiation of the other CNS disorders from controls yields even higher accuracies.ConclusionsThe data indicate that deregulated miRNAs in blood might be used as biomarkers in the diagnosis of AD or other neurological diseases.

Distribution of miRNA expression across human tissues.

We present a human miRNA tissue atlas by determining the abundance of 1997 miRNAs in 61 tissue biopsies of different organs from two individuals collected post-mortem. One thousand three hundred sixty-four miRNAs were discovered in at least one tissue, 143 were present in each tissue. To define the distribution of miRNAs, we utilized a tissue specificity index (TSI). The majority of miRNAs (82.9%) fell in a middle TSI range i.e. were neither specific for single tissues (TSI > 0.85) nor housekeeping miRNAs (TSI < 0.5). Nonetheless, we observed many different miRNAs and miRNA families that were predominantly expressed in certain tissues. Clustering of miRNA abundances revealed that tissues like several areas of the brain clustered together. Considering -3p and -5p mature forms we observed miR-150 with different tissue specificity. Analysis of additional lung and prostate biopsies indicated that inter-organism variability was significantly lower than inter-organ variability. Tissue-specific differences between the miRNA patterns appeared not to be significantly altered by storage as shown for heart and lung tissue. MiRNAs TSI values of human tissues were significantly (P = 10−8) correlated with those of rats; miRNAs that were highly abundant in certain human tissues were likewise abundant in according rat tissues. We implemented a web-based repository enabling scientists to access and browse the data (https://ccb-web.cs.uni-saarland.de/tissueatlas).

Altered microRNA expression profiles of human spermatozoa in patients with different spermatogenic impairments

OBJECTIVE To determine whether microRNAs are differentially expressed in men with normal versus impaired spermatogenesis, and to find a biomarker for accurate diagnosis of male infertility. DESIGN Microarray with real-time polymerase chain reaction (RT-PCR) validation. SETTING University research and clinical institutes. PATIENT(S) Male partner of selected couples (n = 27) who were undergoing assisted reproduction techniques for infertility treatment. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) Statistically significantly altered microRNA expression profiles in normozoospermic versus asthenozoospermic and oligoasthenozoospermic men. RESULT(S) There were 50 miRNAs up-regulated and 27 miRNAs down-regulated in asthenozoospermic males. In oligoasthenozoospermic males, 42 miRNAs were up-regulated and 44 miRNAs down-regulated when compared with normozoospermic males. The miRNAs that exhibited the highest fold changes and area under the receiver operating characteristic curve were miR-34b, miR-122, and miR-1973 in samples from asthenozoospermic men and miR-34b, miR-34b*, miR-15b, miR-34c-5p, miR-122, miR-449a, miR-1973, miR-16, and miR-19a in samples from oligoasthenozoospermic men. Furthermore, quantitative RT-PCR assays on specific miRNAs, including miR-141, miR-200a, miR-122, miR-34b, miR-34c-5p, and miR-16, yielded results that were largely consistent with the microarray data. CONCLUSION(S) Our results reveal an extended number of miRNAs that were differentially expressed in asthenozoospermic and oligoasthenozoospermic males compared with normozoospermic males. These data provide evidence for analysis of miRNA profiles as a future diagnosing tool for male infertility.

GraBCas: a bioinformatics tool for score-based prediction of Caspase- and Granzyme B-cleavage sites in protein sequences

Caspases and granzyme B are proteases that share the primary specificity to cleave at the carboxyl terminal of aspartate residues in their substrates. Both, caspases and granzyme B are enzymes that are involved in fundamental cellular processes and play a central role in apoptotic cell death. Although various targets are described, many substrates still await identification and many cleavage sites of known substrates are not identified or experimentally verified. A more comprehensive knowledge of caspase and granzyme B substrates is essential to understand the biological roles of these enzymes in more detail. The relatively high variability in cleavage site recognition sequence often complicates the identification of cleavage sites. As of yet there is no software available that allows identification of caspase and/or granzyme with cleavage sites differing from the consensus sequence. Here, we present a bioinformatics tool ‘GraBCas’ that provides score-based prediction of potential cleavage sites for the caspases 1–9 and granzyme B including an estimation of the fragment size. We tested GraBCas on already known substrates and showed its usefulness for protein sequence analysis. GraBCas is available at .

GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments

BackgroundHigh-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline.ResultsHere, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms.ConclusionOur gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

A dictionary on microRNAs and their putative target pathways

While in the last decade mRNA expression profiling was among the most popular research areas, over the past years the study of non-coding RNAs, especially microRNAs (miRNAs), has gained increasing interest. For almost 900 known human miRNAs hundreds of pretended targets are known. However, there is only limited knowledge about putative systemic effects of changes in the expression of miRNAs and their regulatory influence. We determined for each known miRNA the biochemical pathways in the KEGG and TRANSPATH database and the Gene Ontology categories that are enriched with respect to its target genes. We refer to these pathways and categories as target pathways of the corresponding miRNA. Investigating target pathways of miRNAs we found a strong relation to disease-related regulatory pathways, including mitogen-activated protein kinase (MAPK) signaling cascade, Transforming growth factor (TGF)-beta signaling pathway or the p53 network. Performing a sophisticated analysis of differentially expressed genes of 13 cancer data sets extracted from gene expression omnibus (GEO) showed that targets of specific miRNAs were significantly deregulated in these sets. The respective miRNA target analysis is also a novel part of our gene set analysis pipeline GeneTrail. Our study represents a comprehensive theoretical analysis of the relationship between miRNAs and their predicted target pathways. Our target pathways analysis provides a ‘miRNA-target pathway’ dictionary, which enables researchers to identify target pathways of differentially regulated miRNAs.

Genome-wide miRNA signatures of human longevity

Little is known about the functions of miRNAs in human longevity. Here, we present the first genome‐wide miRNA study in long‐lived individuals (LLI) who are considered a model for healthy aging. Using a microarray with 863 miRNAs, we compared the expression profiles obtained from blood samples of 15 centenarians and nonagenarians (mean age 96.4 years) with those of 55 younger individuals (mean age 45.9 years). Eighty miRNAs showed aging‐associated expression changes, with 16 miRNAs being up‐regulated and 64 down‐regulated in the LLI relative to the younger probands. Seven of the eight selected aging‐related biomarkers were technically validated using quantitative RT‐PCR, confirming the microarray data. Three of the eight miRNAs were further investigated in independent samples of 15 LLI and 17 younger participants (mean age 101.5 and 36.9 years, respectively). Our screening confirmed previously published miRNAs of human aging, thus reflecting the utility of the applied approach. The hierarchical clustering analysis of the miRNA microarray expression data revealed a distinct separation between the LLI and the younger controls (P‐value < 10−5). The down‐regulated miRNAs appeared as a cluster and were more often reported in the context of diseases than the up‐regulated miRNAs. Moreover, many of the differentially regulated miRNAs are known to exhibit contrasting expression patterns in major age‐related diseases. Further in silico analyses showed enrichment of potential targets of the down‐regulated miRNAs in p53 and other cancer pathways. Altogether, synchronized miRNA–p53 activities could be involved in the prevention of tumorigenesis and the maintenance of genomic integrity during aging.

Comprehensive analysis of microRNA profiles in multiple sclerosis including next-generation sequencing

Background: MicroRNAs (miRNAs) are short, noncoding RNAs with gene regulatory functions whose expression profiles may serve as disease biomarkers. Objective: The objective of this study was to perform a comprehensive analysis of miRNA expression profiles in blood of patients with a clinically isolated syndrome (CIS) or relapsing–remitting multiple sclerosis (RRMS) including next-generation sequencing (NGS). Methods: miRNA expression was analyzed in whole blood samples from treatment-naïve patients with CIS (n = 25) or RRMS (n = 25) and 50 healthy controls by NGS, microarray analysis, and quantitative real-time polymerase chain reaction (qRT-PCR). Results: In patients with CIS/RRMS, NGS and microarray analysis identified 38 and eight significantly deregulated miRNAs, respectively. Three of these miRNAs were found to be significantly up- (hsa-miR-16-2-3p) or downregulated (hsa-miR-20a-5p, hsa-miR-7-1-3p) by both methods. Another five of the miRNAs significantly deregulated in the NGS screen showed the same direction of regulation in the microarray analysis. qRT-PCR confirmed the direction of regulation for all eight and was significant for three miRNAs. Conclusions: This study identifies a set of miRNAs deregulated in CIS/RRMS and reconfirms the previously reported underexpression of hsa-miR-20a-5p in MS. hsa-miR-20a-5p and the other validated miRNAs may represent promising candidates for future evaluation as biomarkers for MS and could be of relevance in the pathophysiology of this disease.