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      Accelerated, high-quality photolithographic synthesis of RNA microarrays in situ

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          Abstract

          Nucleic acid photolithography is the only microarray fabrication process that has demonstrated chemical versatility accommodating any type of nucleic acid. The current approach to RNA microarray synthesis requires long coupling and photolysis times and suffers from unavoidable degradation postsynthesis. In this study, we developed a series of RNA phosphoramidites with improved chemical and photochemical protection of the 2′- and 5′-OH functions. In so doing, we reduced the coupling time by more than half and the photolysis time by a factor of 4. Sequence libraries that would otherwise take over 6 hours to synthesize can now be prepared in half the time. Degradation is substantially lowered, and concomitantly, hybridization signals can reach over seven times those of the previous state of the art. Under those conditions, high-density RNA microarrays and RNA libraries can now be synthesized at greatly accelerated rates. We also synthesized fluorogenic RNA Mango aptamers on microarrays and investigated the effect of sequence mutations on their fluorogenic properties.

          Abstract

          An improved set of RNA building blocks allows for better, faster fabrication of high-density RNA microarrays.

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          Most cited references64

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          Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

          Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. Conclusions/Significance We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.
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            Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities.

            The genetic code-the binding specificity of all transfer-RNAs--defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the approximately 1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.
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              Microarrays, deep sequencing and the true measure of the transcriptome

              Microarrays first made the analysis of the transcriptome possible, and have produced much important information. Today, however, researchers are increasingly turning to direct high-throughput sequencing - RNA-Seq - which has considerable advantages for examining transcriptome fine structure - for example in the detection of allele-specific expression and splice junctions. In this article, we discuss the relative merits of the two techniques, the inherent biases in each, and whether all of the vast body of array work needs to be revisited using the newer technology. We conclude that microarrays remain useful and accurate tools for measuring expression levels, and RNA-Seq complements and extends microarray measurements.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - review & editing
                Role: Data curationRole: InvestigationRole: MethodologyRole: Validation
                Role: Data curationRole: InvestigationRole: Visualization
                Role: Data curationRole: InvestigationRole: Visualization
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - original draftRole: Writing - review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Journal
                Sci Adv
                Sci Adv
                sciadv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                02 August 2024
                31 July 2024
                : 10
                : 31
                : eado6762
                Affiliations
                [ 1 ]Institute of Inorganic Chemistry, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
                [ 2 ]IBMM, University of Montpellier, CNRS, ENSCM, Montpellier, France.
                Author notes
                [* ]Corresponding author. Email: jory.lietard@ 123456univie.ac.at
                Author information
                https://orcid.org/0000-0002-9340-7402
                https://orcid.org/0000-0002-1052-4540
                https://orcid.org/0000-0003-3422-3926
                https://orcid.org/0000-0003-4523-6001
                Article
                ado6762
                10.1126/sciadv.ado6762
                11290486
                39083603
                7286b8cd-9b88-4cfd-9058-cfa0ee56ebdb
                Copyright © 2024 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 February 2024
                : 26 June 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-20-CE91-0004-01
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: I4923
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: P34284
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: P36203
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: TAI687
                Categories
                Research Article
                Physical and Materials Sciences
                SciAdv r-articles
                Biochemistry
                Chemistry
                Chemistry
                Custom metadata
                Nova Morabe

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