SDSE: A software package to simulate the evolution of a pair of DNA sequences

MrBayes is a popular software package for Bayesian phylogenetic inference, which uses an iterative approach to derive an evolutionary tree for a collection of species whose DNA sequences are known. Computationally, MrBayes is characterized by a large number of iterations, each composed of a set of tasks that isolated are not very time-consuming, but are globally computationally demanding. To accelerate the latest MrBayes 3.2, this paper presents MrBayes sMC3, which relies on the computational power of an heterogeneous CPU+GPU platform. For this, MrBayes sMC3 exploits both task and data-level parallelism while minimizing the overheads associated with kernel launches and CPU-GPU data transfers. Experimental results indicate that the proposed parallel approach, together with the proposed set of optimizations, allow for an application acceleration of up to 10× regarding the original MrBayes, and up to 3× regarding the Beagle Library. Furthermore, by analyzing the convergence rate of MrBayes sMC3 with that of the state-of-the-art approaches, a significant reduction in execution time is observed.

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Ribovore: ribosomal RNA sequence analysis for GenBank submissions and database curation

BMC Bioinformatics ◽

10.1186/s12859-021-04316-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Alejandro A. Schäffer ◽

Richard McVeigh ◽

Barbara Robbertse ◽

Conrad L. Schoch ◽

Anjanette Johnston ◽

...

Keyword(s):

Sequence Analysis ◽

Ribosomal Rna ◽

Dna Sequences ◽

Software Package ◽

Rrna Gene ◽

Ssu Rrna ◽

Rrna Sequence ◽

Ssu Rrna Gene ◽

Taxonomic Groups ◽

Rrna Sequences

Abstract Background The DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron. Results To improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The and programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. Nine freely available rRNA databases created and maintained with Ribovore are used for checking incoming GenBank submissions and used by the browser interface at NCBI. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8350 taxa. Conclusion Ribovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank.

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Ribovore: ribosomal RNA sequence analysis for GenBank submissions and database curation

10.1101/2021.02.11.430762 ◽

2021 ◽

Author(s):

Alejandro A. Schäffer ◽

Richard McVeigh ◽

Barbara Robbertse ◽

Conrad L. Schoch ◽

Anjanette Johnston ◽

...

Keyword(s):

Sequence Analysis ◽

Ribosomal Rna ◽

Dna Sequences ◽

Software Package ◽

Rrna Gene ◽

Ssu Rrna ◽

Rrna Sequence ◽

Ssu Rrna Gene ◽

Taxonomic Groups ◽

Rrna Sequences

AbstractBackgroundThe DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron.ResultsTo improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The ribotyper and ribosensor programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The ribodbmaker program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. At least nine freely available blastn rRNA databases created and maintained with Ribovore are used either for checking incoming GenBank submissions or by the blastn browser interface at NCBI or both. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8,350 taxa.ConclusionRibovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank.

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PolyCRACKER, a robust method for the unsupervised partitioning of polyploid subgenomes by signatures of repetitive DNA evolution

10.1101/484832 ◽

2018 ◽

Author(s):

Sean P. Gordon ◽

Joshua J. Levy ◽

John P. Vogel

Keyword(s):

Repetitive Dna ◽

Dna Sequences ◽

Related Species ◽

Software Package ◽

Gc Content ◽

Individual Species ◽

Closely Related Species ◽

As Species ◽

Pooled Dna ◽

Species Specific

AbstractExisting methods for assigning sequences to individual species from pooled DNA samples rely on differences in genome properties like GC content or sequences from related species. These approaches do not work for closely related species where gross features are indistinguishable and related genomes are lacking. We describe a method and associated software package that uses rapidly evolving repetitive DNA to circumvent these limitations. By using short, repetitive, DNA sequences as species-specific signals we separated closely related genomes without any prior knowledge. This approach is ideal for separating the subgenomes of polyploid species with unsequenced or unknown progenitor genomes.

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HamHeat: A fast and simple package for calculating Hamming distance from multiple sequence data for heatmap visualization

10.1101/2020.03.26.009258 ◽

2020 ◽

Author(s):

Alexey V. Rakov ◽

Dieter M. Schifferli ◽

Shu-Lin Liu ◽

Emilio Mastriani

Keyword(s):

Dna Sequences ◽

Software Package ◽

Hamming Distance ◽

Sequence Data ◽

Ease Of Use ◽

Reference Sequence ◽

Multiple Sequence ◽

Fast Calculation ◽

Frequent Variant ◽

Additional Sequence

AbstractThe problem of fast calculation of Hamming distance inferred from many sequence datasets is still not a trivial task. Here, we present HamHeat, as a new software package to efficiently calculate Hamming distance for hundreds of aligned protein or DNA sequences of a large number of residues or nucleotides, respectively. HamHeat uses a unique algorithm with many advantages, including its ease of use and the execution of fast runs for large amounts of data. The package consists of three consecutive modules. In the first module, the software ranks the sequences from the most to the least frequent variant. The second module uses the most common variant as the reference sequence to calculate the Hamming distance of each additional sequence based on the number of residue or nucleotide changes. A final module formats all the results in a comprehensive table that displays the sequence ranks and Hamming distances.Availability and implementationHamHeat is based on Python 3 and AWK, runs on Linux system and is available under the MIT License at: https://github.com/alexeyrakov/[email protected]

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Quanitative aspects of electron diffraction using electron holography

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100139457 ◽

1995 ◽

Vol 53 ◽

pp. 616-617

Author(s):

E. Völkl ◽

L.F. Allard ◽

B. Frost ◽

T.A. Nolan

Keyword(s):

Electron Beam ◽

Electron Diffraction ◽

Software Package ◽

Spatial Coherence ◽

Electron Holography ◽

Image Intensity ◽

Interference Fringes ◽

Complex Image ◽

The Difference ◽

Recorded Image

Off-axis electron holography has the well known ability to preserve the complex image wave within the final, recorded image. This final image described by I(x,y) = I(r) contains contributions from the image intensity of the elastically scattered electrons IeI (r) = |A(r) exp (iΦ(r)) |, the contributions from the inelastically scattered electrons IineI (r), and the complex image wave Ψ = A(r) exp(iΦ(r)) as:(1) I(r) = IeI (r) + Iinel (r) + μ A(r) cos(2π Δk r + Φ(r))where the constant μ describes the contrast of the interference fringes which are related to the spatial coherence of the electron beam, and Φk is the resulting vector of the difference of the wavefront vectors of the two overlaping beams. Using a software package like HoloWorks, the complex image wave Ψ can be extracted.

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Transcription factor/DNA interactions visualized by electron spectroscopic imaging

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100122654 ◽

1992 ◽

Vol 50 (1) ◽

pp. 450-451

Author(s):

David P. Bazett-Jones ◽

Mark L. Brown

Keyword(s):

Transcription Factor ◽

Dna Sequences ◽

Transcription Initiation ◽

Molecular Mechanisms ◽

Phosphorus Content ◽

Spectroscopic Imaging ◽

Electron Spectroscopic Imaging ◽

Dna Backbone ◽

Two Parameters ◽

High Level

A multisubunit RNA polymerase enzyme is ultimately responsible for transcription initiation and elongation of RNA, but recognition of the proper start site by the enzyme is regulated by general, temporal and gene-specific trans-factors interacting at promoter and enhancer DNA sequences. To understand the molecular mechanisms which precisely regulate the transcription initiation event, it is crucial to elucidate the structure of the transcription factor/DNA complexes involved. Electron spectroscopic imaging (ESI) provides the opportunity to visualize individual DNA molecules. Enhancement of DNA contrast with ESI is accomplished by imaging with electrons that have interacted with inner shell electrons of phosphorus in the DNA backbone. Phosphorus detection at this intermediately high level of resolution (≈lnm) permits selective imaging of the DNA, to determine whether the protein factors compact, bend or wrap the DNA. Simultaneously, mass analysis and phosphorus content can be measured quantitatively, using adjacent DNA or tobacco mosaic virus (TMV) as mass and phosphorus standards. These two parameters provide stoichiometric information relating the ratios of protein:DNA content.

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DNA sequence mapping in interphase and metaphase chromosomes by fluorescence in situ hybridization

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100122885 ◽

1992 ◽

Vol 50 (1) ◽

pp. 496-497

Author(s):

Barbara Trask ◽

Susan Allen ◽

Anne Bergmann ◽

Mari Christensen ◽

Anne Fertitta ◽

...

Keyword(s):

In Situ Hybridization ◽

Dna Sequence ◽

Dna Sequences ◽

Dual Band ◽

Nick Translation ◽

Metaphase Chromosomes ◽

Band Pass ◽

Texas Red ◽

Fluorescent Spot

Using fluorescence in situ hybridization (FISH), the positions of DNA sequences can be discretely marked with a fluorescent spot. The efficiency of marking DNA sequences of the size cloned in cosmids is 90-95%, and the fluorescent spots produced after FISH are ≈0.3 μm in diameter. Sites of two sequences can be distinguished using two-color FISH. Different reporter molecules, such as biotin or digoxigenin, are incorporated into DNA sequence probes by nick translation. These reporter molecules are labeled after hybridization with different fluorochromes, e.g., FITC and Texas Red. The development of dual band pass filters (Chromatechnology) allows these fluorochromes to be photographed simultaneously without registration shift.

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Computer programs for the calculation of x-ray intensities emitted by elements in multi-layer structures

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100134685 ◽

1990 ◽

Vol 48 (2) ◽

pp. 216-217

Author(s):

G.F. Bastin ◽

H.J.M. Heijligers ◽

J.M. Dijkstra

Keyword(s):

Software Package ◽

Light Element ◽

Matrix Correction ◽

Excellent Performance ◽

Element Analysis ◽

X Ray ◽

Know How ◽

Accurate Knowledge ◽

Layer Structures ◽

Bulk Matrix

For the calculation of X-ray intensities emitted by elements present in multi-layer systems it is vital to have an accurate knowledge of the x-ray ionization vs. mass-depth (ϕ(ρz)) curves as a function of accelerating voltage and atomic number of films and substrate. Once this knowledge is available the way is open to the analysis of thin films in which both the thicknesses as well as the compositions can usually be determined simultaneously.Our bulk matrix correction “PROZA” with its proven excellent performance for a wide variety of applications (e.g., ultra-light element analysis, extremes in accelerating voltage) has been used as the basis for the development of the software package discussed here. The PROZA program is based on our own modifications of the surface-centred Gaussian ϕ(ρz) model, originally introduced by Packwood and Brown. For its extension towards thin film applications it is required to know how the 4 Gaussian parameters α, β, γ and ϕ(o) for each element in each of the films are affected by the film thickness and the presence of other layers and the substrate.

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Three-Dimensional Structure of Cloned T3 Connector Protein at 1.6nm Resolution

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100180161 ◽

1990 ◽

Vol 48 (1) ◽

pp. 282-283

Author(s):

José L. Carrascosa ◽

José M. Valpuesta ◽

Hisao Fujisawa

Keyword(s):

Dna Sequences ◽

Expression Vector ◽

Three Dimensional ◽

Deae Cellulose ◽

Dna Packaging ◽

Dimensional Structure ◽

Two Dimensional ◽

Freezing And Thawing ◽

Three Dimensional Structure ◽

Dimensional Reconstruction

The head to tail connector of bacteriophages plays a fundamental role in the assembly of viral heads and DNA packaging. In spite of the absence of sequence homology, the structure of connectors from different viruses (T4, Ø29, T3, P22, etc) share common morphological features, that are most clearly revealed in their three-dimensional structure. We have studied the three-dimensional reconstruction of the connector protein from phage T3 (gp 8) from tilted view of two dimensional crystals obtained from this protein after cloning and purification.DNA sequences including gene 8 from phage T3 were cloned, into Bam Hl-Eco Rl sites down stream of lambda promotor PL, in the expression vector pNT45 under the control of cI857. E R204 (pNT89) cells were incubated at 42°C for 2h, harvested and resuspended in 20 mM Tris HC1 (pH 7.4), 7mM 2 mercaptoethanol, ImM EDTA. The cells were lysed by freezing and thawing in the presence of lysozyme (lmg/ml) and ligthly sonicated. The low speed supernatant was precipitated by ammonium sulfate (60% saturated) and dissolved in the original buffer to be subjected to gel nitration through Sepharose 6B, followed by phosphocellulose colum (Pll) and DEAE cellulose colum (DE52). Purified gp8 appeared at 0.3M NaCl and formed crystals when its concentration increased above 1.5 mg/ml.

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