TY - JOUR A1 - Böttcher, René A1 - Amberg, Ronny A1 - Ruzius, F. P. A1 - Guryev, V. A1 - Verhaegh, Wim F. J. A1 - Beyerlein, Peter A1 - van der Zaag, P. J. T1 - Using a priori knowledge to align sequencing reads to their exact genomic position JF - Nucleic Acids Research N2 - The use of a priori knowledge in the alignment of targeted sequencing data is investigated using computational experiments. Adapting a Needleman–Wunsch algorithm to incorporate the genomic position information from the targeted capture, we demonstrate that alignment can be done to just the target region of interest. When in addition use is made of direct string comparison, an improvement of up to a factor of 8 in alignment speed compared to the fastest conventional aligner (Bowtie) is obtained. This results in a total alignment time in targeted sequencing of around 7 min for aligning approximately 56 million captured reads. For conventional aligners such as Bowtie, BWA or MAQ, alignment to just the target region is not feasible as experiments show that this leads to an additional 88% SNP calls, the vast majority of which are false positives (∼92%). Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-6407 SN - 1362-4962 VL - 40 IS - 16 ER - TY - JOUR A1 - Hammer, Paul A1 - Banck, Michaela S. A1 - Amberg, Ronny A1 - Wang, Cheng A1 - Petznick, Gabriele A1 - Luo, Shujun A1 - Khrebtukova, Irina A1 - Schroth, Gary P. A1 - Beyerlein, Peter A1 - Beutler, Andreas S. T1 - mRNA-seq with agnostic splice site discovery for nervous system transcriptomics tested in chronic pain JF - Genome Research N2 - mRNA-seq is a paradigm-shifting technology because of its superior sensitivity and dynamic range and its potential to capture transcriptomes in an agnostic fashion, i.e., independently of existing genome annotations. Implementation of the agnostic approach, however, has not yet been fully achieved. In particular, agnostic mapping of pre-mRNA splice sites has not been demonstrated. The present study pursued dual goals: (1) to advance mRNA-seq bioinformatics toward unbiased transcriptome capture and (2) to demonstrate its potential for discovery in neuroscience by applying the approach to an in vivo model of neurological disease. We have performed mRNA-seq on the L4 dorsal root ganglion (DRG) of rats with chronic neuropathic pain induced by spinal nerve ligation (SNL) of the neighboring (L5) spinal nerve. We found that 12.4% of known genes were induced and 7% were suppressed in the dysfunctional (but anatomically intact) L4 DRG 2 wk after SNL. These alterations persisted chronically (2 mo). Using a read cluster classifier with strong test characteristics (ROC area 97%), we discovered 10,464 novel exons. A new algorithm for agnostic mapping of pre-mRNA splice junctions (SJs) achieved a precision of 97%. Integration of information from all mRNA-seq read classes including SJs led to genome reannotations specifically relevant for the species used (rat), the anatomical site studied (DRG), and the neurological disease considered (pain); for example, a 64-exon coreceptor for the nociceptive transmitter substance P was identified, and 21.9% of newly discovered exons were shown to be dysregulated. Thus, mRNA-seq with agnostic analysis methods appears to provide a highly productive approach for in vivo transcriptomics in the nervous system. Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-6446 SN - 1549-5469 VL - 20 IS - 6 ER - TY - JOUR A1 - Munchel, Sarah A1 - Hoang, Yen A1 - Zhao, Yue A1 - Cottrell, Joseph A1 - Klotzle, Brandy A1 - Godwin, Andrew K. A1 - Koestler, Devin A1 - Beyerlein, Peter A1 - Fan, Jian-Bing A1 - Bibikova, Marina A1 - Chien, Jeremy T1 - Targeted or whole genome sequencing of formalin fixed tissue samples: potential applications in cancer genomics JF - Oncotarget N2 - Current genomic studies are limited by the poor availability of fresh-frozen tissue samples. Although formalin-fixed diagnostic samples are in abundance, they are seldom used in current genomic studies because of the concern of formalin-fixation artifacts. Better characterization of these artifacts will allow the use of archived clinical specimens in translational and clinical research studies. To provide a systematic analysis of formalin-fixation artifacts on Illumina sequencing, we generated 26 DNA sequencing data sets from 13 pairs of matched formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) tissue samples. The results indicate high rate of concordant calls between matched FF/FFPE pairs at reference and variant positions in three commonly used sequencing approaches (whole genome, whole exome, and targeted exon sequencing). Global mismatch rates and C·G > T·A substitutions were comparable between matched FF/FFPE samples, and discordant rates were low (<0.26%) in all samples. Finally, low-pass whole genome sequencing produces similar pattern of copy number alterations between FF/FFPE pairs. The results from our studies suggest the potential use of diagnostic FFPE samples for cancer genomic studies to characterize and catalog variations in cancer genomes. KW - cancer genomics KW - FFPE DNA KW - whole exome sequencing KW - whole genome sequencing KW - copy number alteration Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-6307 SN - 1949-2553 VL - 6 IS - 28 SP - 25943 EP - 25961 ER - TY - JOUR A1 - Graw, Stefan A1 - Meier, Richard A1 - Minn, Kay A1 - Bloomer, Clark A1 - Godwin, Andrew K. A1 - Fridley, Brooke A1 - Vlad, Anda A1 - Beyerlein, Peter A1 - Chien, Jeremy T1 - Robust gene expression and mutation analyses of RNA-sequencing of formalin-fixed diagnostic tumor samples JF - Scientific Reports N2 - Current genomic studies are limited by the availability of fresh tissue samples. Here, we show that Illumina RNA sequencing of formalin-fixed diagnostic tumor samples produces gene expression that is strongly correlated with matched frozen tumor samples (r > 0.89). In addition, sequence variations identified from FFPE RNA show 99.67% concordance with that from exome sequencing of matched frozen tumor samples. Because FFPE is a routine diagnostic sample preparation, the feasibility results reported here will facilitate the setup of large-scale research and clinical studies in medical genomics that are currently limited by the availability of fresh frozen samples. Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-6319 SN - 2045-2322 VL - 5 ER - TY - JOUR A1 - Mitrović, Jelena A1 - Siewert, Christin A1 - Duduk, Bojan A1 - Hecht, Jochen A1 - Mölling, Karin A1 - Broecker, Felix A1 - Beyerlein, Peter A1 - Büttner, Carmen A1 - Bertaccini, Assunta A1 - Kube, Michael T1 - Generation and Analysis of Draft Sequences of 'Stolbur' Phytoplasma from Multiple Displacement Amplification Templates JF - Journal of Molecular Microbiology and Biotechnology N2 - Phytoplasma-associated diseases are reported for more than 1,000 plant species worldwide. Only a few genome sequences are available in contrast to the economical importance of these bacterial pathogens. A new strategy was used to retrieve phytoplasma strain-specific genome data. Multiple displacement amplification was performed on DNA obtained from <3 g of plant tissue from tobacco and parsley samples infected with ‘stolbur' strains. Random hexamers and Phi29 polymerase were evaluated with and without supplementation by group-assigned oligonucleotides providing templates for Illumina's sequencing approach. Metagenomic drafts derived from individual and pooled strain-specific de novo assemblies were analyzed. Supplementation of the Phi29 reaction with the group-assigned oligonucleotides resulted in an about 2-fold enrichment of the percentage of phytoplasma-assigned reads and thereby improved assembly results. The obtained genomic drafts represent the largest datasets available from ‘stolbur' phytoplasmas. Sequences of the two strains (558 kb, 448 proteins and 516 kb, 346 proteins, respectively) were annotated allowing the identification of prominent membrane proteins and reconstruction of core pathways. Analysis of a putative truncated sucrose phosphorylase provides hints on sugar degradation. Furthermore, it is shown that drafts obtained from repetitive-rich genomes allow only limited analysis on multicopy regions and genome completeness. Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-10959 SN - 1660-2412 VL - 24 IS - 1 SP - 1 EP - 11 ER - TY - JOUR A1 - Meier, Richard A1 - Graw, Stefan A1 - Beyerlein, Peter A1 - Koestler, Devin A1 - Molina, Julian R. A1 - Chien, Jeremy T1 - digit—a tool for detection and identification of genomic interchromosomal translocations JF - Nucleic Acids Research N2 - Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named digit that implements a novel measure of mapping ambiguity to discover interchromosomal SVs from mate-pair and pair-end sequencing data. The workflow robustly handles the high numbers of artifacts present in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity. In the simulated data set, our workflow recovered 96% of simulated SVs. It generates a self-updating library of common translocations and allows for the investigation of patient- or group-specific events, making it suitable for discovering and cataloging chromosomal translocations associated with specific groups, traits, diseases or population structures. Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9697 SN - 1362-4962 VL - 45 IS - 9 SP - e72 ER - TY - JOUR A1 - Schilling, Vincent A1 - Beyerlein, Peter A1 - Chien, Jeremy T1 - A Bioinformatics Analysis of Ovarian Cancer Data Using Machine Learning JF - Algorithms N2 - The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study, we propose a machine learning approach to predict ovarian cancer patients’ outcomes and platinum resistance status using publicly available gene expression data. Six classical machine-learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that correlated with the outcome and platinum resistance status of the patients and validated those using Kaplan–Meier plots. In comparison to similar approaches, the performance of the models was higher, and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are TMEFF2, ACSM3, SLC4A1, and ALDH4A1. KW - ovarian cancer KW - machine learning KW - SHAP KW - diagnostic biomarkers KW - platinum resistance Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-17751 VL - 16 IS - 7 PB - MDPI ER - TY - JOUR A1 - Kallabis, Conrad A1 - Beyerlein, Peter A1 - Lisdat, Fred T1 - Quantitative determination of dopamine in the presence of interfering substances supported by machine learning tools JF - Bioelectrochemistry N2 - In the field of neuroscience as well as in the clinical setting, the neurotransmitter dopamine (DA) is an analyte which is important for research as well as medical purposes. There are plenty of methods available to measure dopamine quantitatively, with voltammetric ones such as differential pulse voltammetry (DPV) being among the most convenient and simple ones. However, dopamine often occurs, either naturally or because of the requirements of involved enzymatic systems, alongside substances that can influence the signal it produces upon electrochemical conversion. An example for such substances is the magnesium ion, which itself is not electrochemically active in the potential range needed for DA oxidation, but influences the dopamine signal. We have characterized the properties of DPV signals subject to the interaction between DA and Mg2+ and show that, although these properties are changing in a nonlinear fashion when both concentrations are varying, relatively simple linear mathematical models can be used to determine dopamine concentrations quantitatively in the presence of magnesium ions. The focus of this study is thus, the mathematical treatment of experimental data in order to overcome an analytical problem and not the investigation of the chemical background of DA-Mg2+ interaction. KW - dopamine KW - voltammetric detection KW - interference KW - magnesium ion KW - multiple linear regression KW - Bayesian linear regression KW - multivariate calibration models Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-19277 SN - 1567-5394 VL - 157 IS - 108667 ER -