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Matveeva OV, Ogurtsov AY, Nazipova NN, Shabalina SA. Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes. PLoS One 2018; 13:e0199162. [PMID: 29928000 PMCID: PMC6013149 DOI: 10.1371/journal.pone.0199162] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 06/02/2018] [Indexed: 12/20/2022] Open
Abstract
Off-target oligoprobe's interaction with partially complementary nucleotide sequences represents a problem for many bio-techniques. The goal of the study was to identify oligoprobe sequence characteristics that control the ratio between on-target and off-target hybridization. To understand the complex interplay between specific and genome-wide off-target (cross-hybridization) signals, we analyzed a database derived from genomic comparison hybridization experiments performed with an Affymetrix tiling array. The database included two types of probes with signals derived from (i) a combination of specific signal and cross-hybridization and (ii) genomic cross-hybridization only. All probes from the database were grouped into bins according to their sequence characteristics, where both hybridization signals were averaged separately. For selection of specific probes, we analyzed the following sequence characteristics: vulnerability to self-folding, nucleotide composition bias, numbers of G nucleotides and GGG-blocks, and occurrence of probe's k-mers in the human genome. Increases in bin ranges for these characteristics are simultaneously accompanied by a decrease in hybridization specificity-the ratio between specific and cross-hybridization signals. However, both averaged hybridization signals exhibit growing trends along with an increase of probes' binding energy, where the hybridization specific signal increases significantly faster in comparison to the cross-hybridization. The same trend is evident for the S function, which serves as a combined evaluation of probe binding energy and occurrence of probe's k-mers in the genome. Application of S allows extracting a larger number of specific probes, as compared to using only binding energy. Thus, we showed that high values of specific and cross-hybridization signals are not mutually exclusive for probes with high values of binding energy and S. In this study, the application of a new set of sequence characteristics allows detection of probes that are highly specific to their targets for array design and other bio-techniques that require selection of specific probes.
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Affiliation(s)
- Olga V. Matveeva
- Biopolymer Design LLC, Acton, Massachusetts, United States of America
- * E-mail: (OVM); (SAS)
| | - Aleksey Y. Ogurtsov
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Nafisa N. Nazipova
- Institute of Mathematical Problems of Biology, RAS – the Branch of Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Pushchino, Moscow Region, Russia
| | - Svetlana A. Shabalina
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (OVM); (SAS)
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Matveeva OV, Nechipurenko YD, Riabenko E, Ragan C, Nazipova NN, Ogurtsov AY, Shabalina SA. Optimization of signal-to-noise ratio for efficient microarray probe design. Bioinformatics 2017; 32:i552-i558. [PMID: 27587674 DOI: 10.1093/bioinformatics/btw451] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Target-specific hybridization depends on oligo-probe characteristics that improve hybridization specificity and minimize genome-wide cross-hybridization. Interplay between specific hybridization and genome-wide cross-hybridization has been insufficiently studied, despite its crucial role in efficient probe design and in data analysis. RESULTS In this study, we defined hybridization specificity as a ratio between oligo target-specific hybridization and oligo genome-wide cross-hybridization. A microarray database, derived from the Genomic Comparison Hybridization (GCH) experiment and performed using the Affymetrix platform, contains two different types of probes. The first type of oligo-probes does not have a specific target on the genome and their hybridization signals are derived from genome-wide cross-hybridization alone. The second type includes oligonucleotides that have a specific target on the genomic DNA and their signals are derived from specific and cross-hybridization components combined together in a total signal. A comparative analysis of hybridization specificity of oligo-probes, as well as their nucleotide sequences and thermodynamic features was performed on the database. The comparison has revealed that hybridization specificity was negatively affected by low stability of the fully-paired oligo-target duplex, stable probe self-folding, G-rich content, including GGG motifs, low sequence complexity and nucleotide composition symmetry. CONCLUSION Filtering out the probes with defined 'negative' characteristics significantly increases specific hybridization and dramatically decreasing genome-wide cross-hybridization. Selected oligo-probes have two times higher hybridization specificity on average, compared to the probes that were filtered from the analysis by applying suggested cutoff thresholds to the described parameters. A new approach for efficient oligo-probe design is described in our study. CONTACT shabalin@ncbi.nlm.nih.gov or olga.matveeva@gmail.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Olga V Matveeva
- Biopolymer Design LLC, Acton, MA 01721, USA Engelhardt Institute of Molecular Biology, Moscow 119991, Russia
| | | | - Evgeniy Riabenko
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia
| | - Chikako Ragan
- Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072 Australia
| | - Nafisa N Nazipova
- Institute of Mathematical Problems of Biology, Pushchino, Moscow Region, 142290, Russia
| | - Aleksey Y Ogurtsov
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Svetlana A Shabalina
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
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Fasold M, Binder H. Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data. MICROARRAYS 2014; 3:322-39. [PMID: 27600351 PMCID: PMC4979052 DOI: 10.3390/microarrays3040322] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Revised: 09/30/2014] [Accepted: 12/08/2014] [Indexed: 01/03/2023]
Abstract
The great utility of microarrays for genome-scale expression analysis is challenged by the widespread presence of batch effects, which bias expression measurements in particular within large data sets. These unwanted technical artifacts can obscure biological variation and thus significantly reduce the reliability of the analysis results. It is largely unknown which are the predominant technical sources leading to batch effects. We here quantitatively assess the prevalence and impact of several known technical effects on microarray expression results. Particularly, we focus on important factors such as RNA degradation, RNA quantity, and sequence biases including multiple guanine effects. We find that the common variation of RNA quality and RNA quantity can not only yield low-quality expression results, but that both factors also correlate with batch effects and biological characteristics of the samples.
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Affiliation(s)
- Mario Fasold
- Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany.
- ecSeq Bioinformatics, Brandvorwerkstrasse 43, 04275 Leipzig, Germany.
| | - Hans Binder
- Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany.
- Leipzig Research Center for Civilization Diseases, Universität Leipzig, Philipp-Rosenthal-Straße 27, 04103 Leipzig, Germany.
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Vieregg J, Nelson HM, Stoltz BM, Pierce NA. Selective nucleic acid capture with shielded covalent probes. J Am Chem Soc 2013; 135:9691-9. [PMID: 23745667 PMCID: PMC3703666 DOI: 10.1021/ja4009216] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2013] [Indexed: 11/29/2022]
Abstract
Nucleic acid probes are used for diverse applications in vitro, in situ, and in vivo. In any setting, their power is limited by imperfect selectivity (binding of undesired targets) and incomplete affinity (binding is reversible, and not all desired targets bound). These difficulties are fundamental, stemming from reliance on base pairing to provide both selectivity and affinity. Shielded covalent (SC) probes eliminate the longstanding trade-off between selectivity and durable target capture, achieving selectivity via programmable base pairing and molecular conformation change, and durable target capture via activatable covalent cross-linking. In pure and mixed samples, SC probes covalently capture complementary DNA or RNA oligo targets and reject two-nucleotide mismatched targets with near-quantitative yields at room temperature, achieving discrimination ratios of 2-3 orders of magnitude. Semiquantitative studies with full-length mRNA targets demonstrate selective covalent capture comparable to that for RNA oligo targets. Single-nucleotide DNA or RNA mismatches, including nearly isoenergetic RNA wobble pairs, can be efficiently rejected with discrimination ratios of 1-2 orders of magnitude. Covalent capture yields appear consistent with the thermodynamics of probe/target hybridization, facilitating rational probe design. If desired, cross-links can be reversed to release the target after capture. In contrast to existing probe chemistries, SC probes achieve the high sequence selectivity of a structured probe, yet durably retain their targets even under denaturing conditions. This previously incompatible combination of properties suggests diverse applications based on selective and stable binding of nucleic acid targets under conditions where base-pairing is disrupted (e.g., by stringent washes in vitro or in situ, or by enzymes in vivo).
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Affiliation(s)
- Jeffrey
R. Vieregg
- Department
of Bioengineering, Department of Chemistry, Department of Computing and Mathematical Sciences, California Institute of Technology,
Pasadena, California 91125, United States
| | - Hosea M. Nelson
- Department
of Bioengineering, Department of Chemistry, Department of Computing and Mathematical Sciences, California Institute of Technology,
Pasadena, California 91125, United States
| | - Brian M. Stoltz
- Department
of Bioengineering, Department of Chemistry, Department of Computing and Mathematical Sciences, California Institute of Technology,
Pasadena, California 91125, United States
| | - Niles A. Pierce
- Department
of Bioengineering, Department of Chemistry, Department of Computing and Mathematical Sciences, California Institute of Technology,
Pasadena, California 91125, United States
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Harrison A, Binder H, Buhot A, Burden CJ, Carlon E, Gibas C, Gamble LJ, Halperin A, Hooyberghs J, Kreil DP, Levicky R, Noble PA, Ott A, Pettitt BM, Tautz D, Pozhitkov AE. Physico-chemical foundations underpinning microarray and next-generation sequencing experiments. Nucleic Acids Res 2013; 41:2779-96. [PMID: 23307556 PMCID: PMC3597649 DOI: 10.1093/nar/gks1358] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Hybridization of nucleic acids on solid surfaces is a key process involved in high-throughput technologies such as microarrays and, in some cases, next-generation sequencing (NGS). A physical understanding of the hybridization process helps to determine the accuracy of these technologies. The goal of a widespread research program is to develop reliable transformations between the raw signals reported by the technologies and individual molecular concentrations from an ensemble of nucleic acids. This research has inputs from many areas, from bioinformatics and biostatistics, to theoretical and experimental biochemistry and biophysics, to computer simulations. A group of leading researchers met in Ploen Germany in 2011 to discuss present knowledge and limitations of our physico-chemical understanding of high-throughput nucleic acid technologies. This meeting inspired us to write this summary, which provides an overview of the state-of-the-art approaches based on physico-chemical foundation to modeling of the nucleic acids hybridization process on solid surfaces. In addition, practical application of current knowledge is emphasized.
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Affiliation(s)
- Andrew Harrison
- University of Essex-Mathematical Sciences, Colchester CO4 3SQ, Essex, United Kingdom
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Dietz A, Wichmann G. [Translational research in head and neck cancer. Biological characteristics and general aspects]. HNO 2012; 59:874-84. [PMID: 21861150 DOI: 10.1007/s00106-011-2361-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Translational research in head and neck oncology is subject to the same laws as all other solid tumors. It is based on the one hand on a solid framework of well prepared clinical studies and / or workflows according to consensus criteria with comparable documentation of clinical outcomes, while on the other on methodolgically solid and reproducible laboratory research within an effeciently interacting network. Translationally applicable single molecular markers from basic research [with the exception of p16(INK4a) as a surrogate marker for human papillomavirus (HPV)] have not found their way into clinical routine in head and neck squamous cell carcinoma (HNSCC). "Correlated gene sets" and "metagenes", including genetic profiling (omics) within clinically characterized patient groups, play an increasing role in the translational research of HNSCC. Although methodological problems currently hinder clinical oncological research, increasing focus on translational research can be observed.
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Affiliation(s)
- A Dietz
- Klinik und Poliklinik für HNO-Erkrankungen, Universitätsklinikum Leipzig, Liebigstr. 10-14, 04103, Leipzig, Deutschland.
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Fasold M, Stadler PF, Binder H. G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration. BMC Bioinformatics 2010; 11:207. [PMID: 20423484 PMCID: PMC2884167 DOI: 10.1186/1471-2105-11-207] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2010] [Accepted: 04/27/2010] [Indexed: 02/02/2023] Open
Abstract
Background The brightness of the probe spots on expression microarrays intends to measure the abundance of specific mRNA targets. Probes with runs of at least three guanines (G) in their sequence show abnormal high intensities which reflect rather probe effects than target concentrations. This G-bias requires correction prior to downstream expression analysis. Results Longer runs of three or more consecutive G along the probe sequence and in particular triple degenerated G at its solution end ((GGG)1-effect) are associated with exceptionally large probe intensities on GeneChip expression arrays. This intensity bias is related to non-specific hybridization and affects both perfect match and mismatch probes. The (GGG)1-effect tends to increase gradually for microarrays of later GeneChip generations. It was found for DNA/RNA as well as for DNA/DNA probe/target-hybridization chemistries. Amplification of sample RNA using T7-primers is associated with strong positive amplitudes of the G-bias whereas alternative amplification protocols using random primers give rise to much smaller and partly even negative amplitudes. We applied positional dependent sensitivity models to analyze the specifics of probe intensities in the context of all possible short sequence motifs of one to four adjacent nucleotides along the 25meric probe sequence. Most of the longer motifs are adequately described using a nearest-neighbor (NN) model. In contrast, runs of degenerated guanines require explicit consideration of next nearest neighbors (GGG terms). Preprocessing methods such as vsn, RMA, dChip, MAS5 and gcRMA only insufficiently remove the G-bias from data. Conclusions Positional and motif dependent sensitivity models accounts for sequence effects of oligonucleotide probe intensities. We propose a positional dependent NN+GGG hybrid model to correct the intensity bias associated with probes containing poly-G motifs. It is implemented as a single-chip based calibration algorithm for GeneChips which can be applied in a pre-correction step prior to standard preprocessing.
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Affiliation(s)
- Mario Fasold
- Interdisciplinary Centre for Bioinformatics, University Leipzig, Germany
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Wong G, Leckie C, Gorringe KL, Haviv I, Campbell IG, Kowalczyk A. Exploiting sequence similarity to validate the sensitivity of SNP arrays in detecting fine-scaled copy number variations. ACTA ACUST UNITED AC 2010; 26:1007-14. [PMID: 20189937 DOI: 10.1093/bioinformatics/btq088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
MOTIVATION High-density single nucleotide polymorphism (SNP) genotyping arrays are efficient and cost effective platforms for the detection of copy number variation (CNV). To ensure accuracy in probe synthesis and to minimize production costs, short oligonucleotide probe sequences are used. The use of short probe sequences limits the specificity of binding targets in the human genome. The specificity of these short probeset sequences has yet to be fully analysed against a normal reference human genome. Sequence similarity can artificially elevate or suppress copy number measurements, and hence reduce the reliability of affected probe readings. For the purpose of detecting narrow CNVs reliably down to the width of a single probeset, sequence similarity is an important issue that needs to be addressed. RESULTS We surveyed the Affymetrix Human Mapping SNP arrays for probeset sequence similarity against the reference human genome. Utilizing sequence similarity results, we identified a collection of fine-scaled putative CNVs between gender from autosomal probesets whose sequence matches various loci on the sex chromosomes. To detect these variations, we utilized our statistical approach, Detecting REcurrent Copy number change using rank-order Statistics (DRECS), and showed that its performance was superior and more stable than the t-test in detecting CNVs. Through the application of DRECS on the HapMap population datasets with multi-matching probesets filtered, we identified biologically relevant SNPs in aberrant regions across populations with known association to physical traits, such as height, covered by the span of a single probe. This provided empirical confirmation of the existence of naturally occurring narrow CNVs as well as the sensitivity of the Affymetrix SNP array technology in detecting them. AVAILABILITY The MATLAB implementation of DRECS is available at http://ww2.cs.mu.oz.au/ approximately gwong/DRECS/index.html.
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Affiliation(s)
- Gerard Wong
- Victoria Research Laboratory, National ICT Australia, Department of Computer Science and Software Engineering, University of Melbourne, Australia.
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