Literature DB >> 27587674

Optimization of signal-to-noise ratio for efficient microarray probe design.

Olga V Matveeva1, Yury D Nechipurenko2, Evgeniy Riabenko3, Chikako Ragan4, Nafisa N Nazipova5, Aleksey Y Ogurtsov6, Svetlana A Shabalina6.   

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.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27587674      PMCID: PMC5939967          DOI: 10.1093/bioinformatics/btw451

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  29 in total

1.  Base pair interactions and hybridization isotherms of matched and mismatched oligonucleotide probes on microarrays.

Authors:  Hans Binder; Stephan Preibisch; Toralf Kirsten
Journal:  Langmuir       Date:  2005-09-27       Impact factor: 3.882

2.  Short oligonucleotide probes containing G-stacks display abnormal binding affinity on Affymetrix microarrays.

Authors:  Chunlei Wu; Haitao Zhao; Keith Baggerly; Roberto Carta; Li Zhang
Journal:  Bioinformatics       Date:  2007-05-30       Impact factor: 6.937

3.  Improved nearest-neighbor parameters for predicting DNA duplex stability.

Authors:  J SantaLucia; H T Allawi; P A Seneviratne
Journal:  Biochemistry       Date:  1996-03-19       Impact factor: 3.162

4.  G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration.

Authors:  Mario Fasold; Peter F Stadler; Hans Binder
Journal:  BMC Bioinformatics       Date:  2010-04-27       Impact factor: 3.169

Review 5.  From DNA sequence to transcriptional behaviour: a quantitative approach.

Authors:  Eran Segal; Jonathan Widom
Journal:  Nat Rev Genet       Date:  2009-07       Impact factor: 53.242

6.  Transcriptome-wide prediction of miRNA targets in human and mouse using FASTH.

Authors:  Chikako Ragan; Nicole Cloonan; Sean M Grimmond; Michael Zuker; Mark A Ragan
Journal:  PLoS One       Date:  2009-05-29       Impact factor: 3.240

7.  Mismatch and G-stack modulated probe signals on SNP microarrays.

Authors:  Hans Binder; Mario Fasold; Torsten Glomb
Journal:  PLoS One       Date:  2009-11-17       Impact factor: 3.240

8.  G-spots cause incorrect expression measurement in Affymetrix microarrays.

Authors:  Graham Jg Upton; William B Langdon; Andrew P Harrison
Journal:  BMC Genomics       Date:  2008-12-18       Impact factor: 3.969

9.  Computational models with thermodynamic and composition features improve siRNA design.

Authors:  Svetlana A Shabalina; Alexey N Spiridonov; Aleksey Y Ogurtsov
Journal:  BMC Bioinformatics       Date:  2006-02-12       Impact factor: 3.169

10.  Expression patterns of protein kinases correlate with gene architecture and evolutionary rates.

Authors:  Aleksey Y Ogurtsov; Leonardo Mariño-Ramírez; Gibbes R Johnson; David Landsman; Svetlana A Shabalina; Nikolay A Spiridonov
Journal:  PLoS One       Date:  2008-10-31       Impact factor: 3.240

View more
  4 in total

1.  Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes.

Authors:  Olga V Matveeva; Aleksey Y Ogurtsov; Nafisa N Nazipova; Svetlana A Shabalina
Journal:  PLoS One       Date:  2018-06-21       Impact factor: 3.240

2.  Ultraconserved element (UCE) probe set design: Base genome and initial design parameters critical for optimization.

Authors:  Grey T Gustafson; Alana Alexander; John S Sproul; James M Pflug; David R Maddison; Andrew E Z Short
Journal:  Ecol Evol       Date:  2019-06-11       Impact factor: 2.912

3.  A decision-theoretic approach to the evaluation of machine learning algorithms in computational drug discovery.

Authors:  Oliver P Watson; Isidro Cortes-Ciriano; Aimee R Taylor; James A Watson
Journal:  Bioinformatics       Date:  2019-11-01       Impact factor: 6.937

4.  Understanding off-target effects through hybridization kinetics and thermodynamics.

Authors:  Nafisa N Nazipova; Svetlana A Shabalina
Journal:  Cell Biol Toxicol       Date:  2019-12-10       Impact factor: 6.691

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.