scholarly journals Analyzing Secondary Structure Patterns in DNA Aptamers Identified via CompELS

Molecules ◽  
2019 ◽  
Vol 24 (8) ◽  
pp. 1572 ◽  
Author(s):  
Richard Sullivan ◽  
Mary Catherine Adams ◽  
Rajesh R. Naik ◽  
Valeria T. Milam
Keyword(s):  
Secondary Structure ◽  
Dna Sequences ◽  
High Throughput Sequencing ◽  
Large Population ◽  
Binding Activity ◽  
Global Alignment ◽  
Dna Aptamers ◽  
Secondary Structure Analysis ◽  
Screening Platform ◽  
Analytical Tools

In contrast to sophisticated high-throughput sequencing tools for genomic DNA, analytical tools for comparing secondary structure features between multiple single-stranded DNA sequences are less developed. For single-stranded nucleic acid ligands called aptamers, secondary structure is widely thought to play a pivotal role in driving recognition-based binding activity between an aptamer sequence and its specific target. Here, we employ a competition-based aptamer screening platform called CompELS to identify DNA aptamers for a colloidal target. We then analyze predicted secondary structures of the aptamers and a large population of random sequences to identify sequence features and patterns. Our secondary structure analysis identifies patterns ranging from position-dependent score matrixes of individual structural elements to position-independent consensus domains resulting from global alignment.

scholarly journals Secondary Structure Analysis of Adenovirus Tripartite Leader

1989 ◽  
Vol 264 (18) ◽  
pp. 10679-10684
Author(s):  
Y Zhang ◽  
P J Dolph ◽  
R J Schneider
Keyword(s):  
Secondary Structure ◽  
Structure Analysis ◽  
Secondary Structure Analysis

Sequence of the Kluyveromyces lactis β-galactosidase: comparison with prokaryotic enzymes and secondary structure analysis

Gene ◽  
1992 ◽  
Vol 118 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Olivier Poch ◽  
Hervé L'Hôte ◽  
Vincent Dallery ◽  
Françoise Debeaux ◽  
Reinhard Fleer ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Structure Analysis ◽  
Kluyveromyces Lactis ◽  
Secondary Structure Analysis

Periphyton diversity in two different Antarctic lakes assessed using metabarcoding

2021 ◽  
pp. 1-9
Author(s):  
Paulo E.A.S. Câmara ◽  
Láuren M.D. De Souza ◽  
Otávio Henrique Bezerra Pinto ◽  
Peter Convey ◽  
Eduardo T. Amorim ◽  
...  
Keyword(s):  
Dna Sequences ◽  
High Throughput Sequencing ◽  
Shannon Index ◽  
South Shetland Islands ◽  
King George Island ◽  
Deception Island ◽  
Maritime Antarctic ◽  
Shetland Islands ◽  
Antarctic Lakes ◽  
Significant Difference

Abstract Antarctic lakes have generally simple periphyton communities when compared with those of lower latitudes. To date, assessment of microbial diversity in Antarctica has relied heavily on traditional direct observation and cultivation methods. In this study, sterilized cotton baits were left submerged for two years in two lakes on King George Island and Deception Island, South Shetland Islands (Maritime Antarctic), followed by assessment of diversity by metabarcoding using high-throughput sequencing. DNA sequences of 44 taxa belonging to four kingdoms and seven phyla were found. Thirty-six taxa were detected in Hennequin Lake on King George Island and 20 taxa were detected in Soto Lake on Deception Island. However, no significant difference in species composition was detected between the two assemblages (Shannon index). Our data suggest that metabarcoding provides a suitable method for the assessment of periphyton biodiversity in oligotrophic Antarctic lakes.

Engineering DNA aptamers and DNA enzymes with fluorescence-signaling properties

2004 ◽  
Vol 76 (7-8) ◽  
pp. 1547-1561 ◽  
Author(s):  
R. Nutiu ◽  
Shirley Mei ◽  
Zhongjie Liu ◽  
Y. Li
Keyword(s):  
Dna Sequences ◽  
Rational Design ◽  
In Vitro Selection ◽  
Random Sequence ◽  
Pair Potential ◽  
Dna Aptamers ◽  
Dna Molecules ◽  
Dna Enzymes ◽  
Fluorescence Signaling

Single-stranded DNA molecules with ligand-binding ability and catalytic function, referred to as DNA aptamers and DNA enzymes, respectively, are special DNA sequences isolated from random-sequence DNA libraries by “in vitro selection”. These two new classes of artificial DNA molecules have the potential of being used as molecular tools in a variety of innovative applications ranging from biosensing to gene regulation. Our laboratory is interested in engineering fluorescence-signaling DNA aptamers and DNA enzymes that can be widely exploited for detection-directed applications. In this article, we will first discuss our recent efforts on the rational design of a new class of signaling aptamers denoted “structure- switching signaling aptamers”, which report target binding by switching structures from DNA/DNA duplex to DNA/target complex. We will then describe the in vitro selection of fluorescence-signaling DNA enzymes that exhibit a synchronized catalysis-signaling capability by cleaving a chimeric RNA/DNA substrate at the lone RNA linkage surrounded by closely spaced fluorophore-quencher pair. Potential utilities of these signaling DNA molecules will also be discussed.

scholarly journals miR-Explore: Predicting MicroRNA Precursors by Class Grouping and Secondary Structure Positional Alignment

2013 ◽  
Vol 7 ◽  
pp. BBI.S10758 ◽  
Author(s):  
Bram Sebastian ◽  
Samuel E. Aggrey
Keyword(s):  
Secondary Structure ◽  
Comparative Method ◽  
High Specificity ◽  
Computational Prediction ◽  
Training Data ◽  
Structure Alignment ◽  
Global Alignment ◽  
Gene Expressions ◽  
Small Noncoding Rnas ◽  
Prediction Approach

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expressions by targeting the mRNAs especially in the 3′UTR regions. The identification of miRNAs has been done by biological experiment and computational prediction. The computational prediction approach has been done using two major methods: comparative and noncomparative. The comparative method is dependent on the conservation of the miRNA sequences and secondary structure. The noncomparative method, on the other hand, does not rely on conservation. We hypothesized that each miRNA class has its own unique set of features; therefore, grouping miRNA by classes before using them as training data will improve sensitivity and specificity. The average sensitivity was 88.62% for miR-Explore, which relies on within miRNA class alignment, and 70.82% for miR-abela, which relies on global alignment. Compared with global alignment, grouping miRNA by classes yields a better sensitivity with very high specificity for pre-miRNA prediction even when a simple positional based secondary and primary structure alignment are used.

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