scholarly journals In vivo generation of DNA sequence diversity for cellular barcoding

2014 ◽  
Vol 42 (16) ◽  
pp. e127-e127 ◽  
Author(s):  
Ian D. Peikon ◽  
Diana I. Gizatullina ◽  
Anthony M. Zador
Keyword(s):  
Dna Sequence ◽  
Sequence Diversity ◽  
Cellular Barcoding

scholarly journals In vivo generation of DNA sequence diversity for cellular barcoding

2014 ◽  
Author(s):  
Ian Peikon ◽  
Diana Gizatullina ◽  
Anthony Zador
Keyword(s):  
Dna Sequencing ◽  
Dna Sequence ◽  
Biological Samples ◽  
Biological Systems ◽  
Sequence Diversity ◽  
Bacterial Cells ◽  
Complete Understanding ◽  
Novel Method ◽  
Cellular Barcoding

Heterogeneity is a ubiquitous feature of biological systems. A complete understanding of such systems requires a method for uniquely identifying and tracking individual components and their interactions with each other. We have developed a novel method of uniquely tagging individual cells in vivo with a genetic 'barcode' that can be recovered by DNA sequencing. We demonstrate the feasibility of this technique in bacterial cells. This method should prove useful in tracking interactions of cells within a network, and/or heterogeneity within complex biological samples.

scholarly journals DNA thermodynamics shape chromosome organization and topology

2013 ◽  
Vol 41 (2) ◽  
pp. 548-553 ◽  
Author(s):  
Andrew A. Travers ◽  
Georgi Muskhelishvili
Keyword(s):  
Dna Sequence ◽  
Dna Sequences ◽  
Chromosome Organization ◽  
Topological Properties ◽  
Genetic Organization ◽  
And Topology ◽  
Dna Translocases

How much information is encoded in the DNA sequence of an organism? We argue that the informational, mechanical and topological properties of DNA are interdependent and act together to specify the primary characteristics of genetic organization and chromatin structures. Superhelicity generated in vivo, in part by the action of DNA translocases, can be transmitted to topologically sensitive regions encoded by less stable DNA sequences.

scholarly journals PLASTID DNA SEQUENCE DIVERSITY IN A WORLDWIDE SET OF GRAPEVINE CULTIVARS (VITIS VINIFERA L. SUBSP. VINIFERA)

2014 ◽  
pp. 609-616 ◽  
Author(s):  
T. Beridze ◽  
I. Pipia ◽  
J. Beck ◽  
S.-C. Hsu ◽  
B. Schaal ◽  
...  
Keyword(s):  
Vitis Vinifera ◽  
Dna Sequence ◽  
Plastid Dna ◽  
Sequence Diversity ◽  
Vitis Vinifera L

scholarly journals Aptardi predicts polyadenylation sites in sample-specific transcriptomes using high-throughput RNA sequencing and DNA sequence

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Lusk ◽  
Evan Stene ◽  
Farnoush Banaei-Kashani ◽  
Boris Tabakoff ◽  
Katerina Kechris ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Dna Sequence ◽  
Mammalian Species ◽  
Alternative Polyadenylation ◽  
Sequence Information ◽  
Rna Seq ◽  
Average Precision ◽  
Polyadenylation Sites ◽  
Dna Nucleotide Sequence

AbstractAnnotation of polyadenylation sites from short-read RNA sequencing alone is a challenging computational task. Other algorithms rooted in DNA sequence predict potential polyadenylation sites; however, in vivo expression of a particular site varies based on a myriad of conditions. Here, we introduce aptardi (alternative polyadenylation transcriptome analysis from RNA-Seq data and DNA sequence information), which leverages both DNA sequence and RNA sequencing in a machine learning paradigm to predict expressed polyadenylation sites. Specifically, as input aptardi takes DNA nucleotide sequence, genome-aligned RNA-Seq data, and an initial transcriptome. The program evaluates these initial transcripts to identify expressed polyadenylation sites in the biological sample and refines transcript 3′-ends accordingly. The average precision of the aptardi model is twice that of a standard transcriptome assembler. In particular, the recall of the aptardi model (the proportion of true polyadenylation sites detected by the algorithm) is improved by over three-fold. Also, the model—trained using the Human Brain Reference RNA commercial standard—performs well when applied to RNA-sequencing samples from different tissues and different mammalian species. Finally, aptardi’s input is simple to compile and its output is easily amenable to downstream analyses such as quantitation and differential expression.

scholarly journals APOBEC3H haplotypes and HIV-1 pro-viral vif DNA sequence diversity in early untreated human immunodeficiency virus–1 infection

2011 ◽  
Vol 72 (3) ◽  
pp. 207-212 ◽  
Author(s):  
P.A. Gourraud ◽  
A. Karaouni ◽  
J.M. Woo ◽  
T. Schmidt ◽  
J.R. Oksenberg ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Dna Sequence ◽  
Sequence Diversity ◽  
Immunodeficiency Virus ◽  
Hiv 1 ◽  
Human Immunodeficiency Virus 1

scholarly journals Functional diversity for REST (NRSF) is defined by in vivo binding affinity hierarchies at the DNA sequence level

2009 ◽  
Vol 19 (6) ◽  
pp. 994-1005 ◽  
Author(s):  
A. W. Bruce ◽  
A. J. Lopez-Contreras ◽  
P. Flicek ◽  
T. A. Down ◽  
P. Dhami ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Dna Sequence ◽  
Functional Diversity ◽  
In Vivo Binding

scholarly journals DISCo-microbe: design of an identifiable synthetic community of microbes

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8534 ◽  
Author(s):  
Dana L. Carper ◽  
Travis J. Lawrence ◽  
Alyssa A. Carrell ◽  
Dale A. Pelletier ◽  
David J. Weston
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
Dna Sequence ◽  
Sequence Alignment ◽  
Amplicon Sequencing ◽  
Ribosomal Database Project ◽  
Community Members ◽  
Dna Sequence Alignment ◽  
Diverse Community

Background Microbiomes are extremely important for their host organisms, providing many vital functions and extending their hosts’ phenotypes. Natural studies of host-associated microbiomes can be difficult to interpret due to the high complexity of microbial communities, which hinders our ability to track and identify individual members along with the many factors that structure or perturb those communities. For this reason, researchers have turned to synthetic or constructed communities in which the identities of all members are known. However, due to the lack of tracking methods and the difficulty of creating a more diverse and identifiable community that can be distinguished through next-generation sequencing, most such in vivo studies have used only a few strains. Results To address this issue, we developed DISCo-microbe, a program for the design of an identifiable synthetic community of microbes for use in in vivo experimentation. The program is composed of two modules; (1) create, which allows the user to generate a highly diverse community list from an input DNA sequence alignment using a custom nucleotide distance algorithm, and (2) subsample, which subsamples the community list to either represent a number of grouping variables, including taxonomic proportions, or to reach a user-specified maximum number of community members. As an example, we demonstrate the generation of a synthetic microbial community that can be distinguished through amplicon sequencing. The synthetic microbial community in this example consisted of 2,122 members from a starting DNA sequence alignment of 10,000 16S rRNA sequences from the Ribosomal Database Project. We generated simulated Illumina sequencing data from the constructed community and demonstrate that DISCo-microbe is capable of designing diverse communities with members distinguishable by amplicon sequencing. Using the simulated data we were able to recover sequences from between 97–100% of community members using two different post-processing workflows. Furthermore, 97–99% of sequences were assigned to a community member with zero sequences being misidentified. We then subsampled the community list using taxonomic proportions to mimic a natural plant host–associated microbiome, ultimately yielding a diverse community of 784 members. Conclusions DISCo-microbe can create a highly diverse community list of microbes that can be distinguished through 16S rRNA gene sequencing, and has the ability to subsample (i.e., design) the community for the desired number of members and taxonomic proportions. Although developed for bacteria, the program allows for any alignment input from any taxonomic group, making it broadly applicable. The software and data are freely available from GitHub (https://github.com/dlcarper/DISCo-microbe) and Python Package Index (PYPI).

scholarly journals Supercoiling DNA locates mismatches

2017 ◽  
Author(s):  
Andrew Dittmore ◽  
Sumitabha Brahmachari ◽  
Yasuhara Takagi ◽  
John F. Marko ◽  
Keir C. Neuman
Keyword(s):  
Dna Sequence ◽  
Base Pair ◽  
Dna Supercoiling ◽  
Magnetic Tweezers ◽  
Relative Probability ◽  
Base Pairs ◽  
Damage Sensing ◽  
Mismatched Base Pair ◽  
Monovalent Salt

We present a method of detecting sequence defects by supercoiling DNA with magnetic tweezers. The method is sensitive to a single mismatched base pair in a DNA sequence of several thousand base pairs. We systematically compare DNA molecules with 0 to 16 adjacent mismatches at 1 M monovalent salt and 3.5 pN force and show that, under these conditions, a single plectoneme forms and is stably pinned at the defect. We use these measurements to estimate the energy and degree of end-loop kinking at defects. From this, we calculate the relative probability of plectoneme pinning at the mismatch under physiologically relevant conditions. Based on this estimate, we propose that DNA supercoiling could contribute to mismatch and damage sensing in vivo.

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