scholarly journals Detecting large deletions at base pair level by combining split read and paired read data

2017 ◽  
Vol 18 (S12) ◽  
Author(s):  
Matthew Hayes ◽  
Jeremy S. Pearson
Keyword(s):  
Base Pair ◽  
Large Deletions ◽  
Split Read ◽  
Paired Read ◽  
Pair Level

scholarly journals Modeling DNA structure, elasticity, and deformations at the base-pair level

2003 ◽  
Vol 68 (2) ◽  
Author(s):  
Boris Mergell ◽  
Mohammad R. Ejtehadi ◽  
Ralf Everaers
Keyword(s):  
Base Pair ◽  
Dna Structure ◽  
Pair Level

scholarly journals Shift and adapt: the costs and benefits of karyotype variations

2015 ◽  
Author(s):  
Aleeza C Gerstein ◽  
Judith Berman
Keyword(s):  
Chromosome Number ◽  
Base Pair ◽  
Homologous Chromosome ◽  
Molecular Mechanisms ◽  
Costs And Benefits ◽  
Wild Type ◽  
Genomic Variants ◽  
Karyotypic Variation ◽  
Type Chromosome ◽  
Pair Level

Variation is the spice of life or, in the case of evolution, variation is the necessary material on which selection can act to enable adaptation. Karyotypic variation in ploidy (the number of homologous chromosome sets) and aneuploidy (imbalance in the number of chromosomes) are fundamentally different than other types of genomic variants. Karyotypic variation emerges through different molecular mechanisms than other mutational events, and unlike mutations that alter the genome at the base pair level, rapid reversion to the wild type chromosome number is often possible. Although karyotypic variation has long been noted and discussed by biologists, interest in the importance of karyotypic variants in evolutionary processes has spiked in recent years, and much remains to be discovered about how karyotypic variants are produced and subsequently selected.

scholarly journals A molecular view of DNA flexibility

2021 ◽  
Vol 54 ◽  
Author(s):  
Alberto Marin-Gonzalez ◽  
J. G. Vilhena ◽  
Ruben Perez ◽  
Fernando Moreno-Herrero
Keyword(s):  
Mechanical Properties ◽  
Single Molecule ◽  
Base Pair ◽  
Molecular Mechanisms ◽  
Cytosine Methylation ◽  
Persistence Length ◽  
Dna Dynamics ◽  
Dna Mechanics ◽  
Future Design ◽  
Pair Level

Abstract DNA dynamics can only be understood by taking into account its complex mechanical behavior at different length scales. At the micrometer level, the mechanical properties of single DNA molecules have been well-characterized by polymer models and are commonly quantified by a persistence length of 50 nm (~150 bp). However, at the base pair level (~3.4 Å), the dynamics of DNA involves complex molecular mechanisms that are still being deciphered. Here, we review recent single-molecule experiments and molecular dynamics simulations that are providing novel insights into DNA mechanics from such a molecular perspective. We first discuss recent findings on sequence-dependent DNA mechanical properties, including sequences that resist mechanical stress and sequences that can accommodate strong deformations. We then comment on the intricate effects of cytosine methylation and DNA mismatches on DNA mechanics. Finally, we review recently reported differences in the mechanical properties of DNA and double-stranded RNA, the other double-helical carrier of genetic information. A thorough examination of the recent single-molecule literature permits establishing a set of general ‘rules’ that reasonably explain the mechanics of nucleic acids at the base pair level. These simple rules offer an improved description of certain biological systems and might serve as valuable guidelines for future design of DNA and RNA nanostructures.

Fluctuations at the Base Pair Level Effecting Charge Transfer in DNA†

2009 ◽  
Vol 113 (16) ◽  
pp. 3955-3962 ◽  
Author(s):  
Sairam S. Mallajosyula ◽  
Ashutosh Gupta ◽  
Swapan K. Pati
Keyword(s):  
Charge Transfer ◽  
Base Pair ◽  
Charge Transfer In Dna ◽  
Pair Level

scholarly journals unCOVERApp: an interactive graphical application for clinical assessment of sequence coverage at the base-pair level

2020 ◽  
Author(s):  
Emanuela Iovino ◽  
Marco Seri ◽  
Tommaso Pippucci
Keyword(s):  
Allele Frequency ◽  
Clinical Assessment ◽  
Base Pair ◽  
Quality Parameters ◽  
Sequencing Data ◽  
Sequence Coverage ◽  
Bioinformatic Tools ◽  
Clinical Annotation ◽  
Clinical Consequences ◽  
Pair Level

AbstractMotivationNext Generation Sequencing (NGS) is increasingly adopted in the clinical practice largely thanks to concurrent advancements in bioinformatic tools for variant detection and annotation. Despite improvements in available approaches, the need to assess sequencing quality down to the base-pair level still poses challenges for diagnostic accuracy. One of the most popular quality parameters of diagnostic NGS is the percentage of targeted bases characterized by low depth of coverage (DoC). These regions potentially hide a clinically-relevant variant, but no annotation is usually returned for them.However, visualizing low-DoC data with their potential functional and clinical consequences may be useful to prioritize inspection of specific regions before re-sequencing all coverage gaps or making assertions about completeness of the diagnostic test.To meet this need we have developed unCOVERApp, an interactive application for graphical inspection and clinical annotation of low-DoC genomic regions containing genes.ResultsunCOVERApp is a suite of graphical and statistical tools to support clinical assessment of low-DoC regions. Its interactive plots allow to display gene sequence coverage down to the base-pair level, and functional and clinical annotations of sites below a user-defined DoC threshold can be downloaded in a user-friendly spreadsheet format. Moreover, unCOVERApp provides a simple statistical framework to evaluate if DoC is sufficient for the detection of somatic variants, where the usual 20x DoC threshold used for germline variants is not adequate. A maximum credible allele frequency calculator is also available allowing users to set allele frequency cut-offs based on assumptions about the genetic architecture of the disease instead of applying a general one (e.g. 5%). In conclusion, unCOVERApp is an original tool designed to identify sites of potential clinical interest that may be hidden in diagnostic sequencing data.AvailabilityunCOVERApp is a freely available application written in R and developed with Shiny packages and available in GitHub.

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