scholarly journals Origin and distribution of different retrotransposons in different taxa

2018 ◽  
Vol 2 (2) ◽  
pp. 13
Author(s):  
Buket Cakmak Guner ◽  
Nermin Gozukirmizi
Keyword(s):  
Human Genome ◽  
Population Studies ◽  
Genomic Data ◽  
Data Sets ◽  
Human Genetic Variation ◽  
Chain Reaction ◽  
Population Genomic ◽  
Genomic Studies ◽  
Polymerase Chain ◽  
Genome Analyses

Novel genome analysis technologies enable genomic studies of transposable elements (TEs) in different organisms. Population studies of human genome show thousands of individual TE insertions. These insertions are important source of natural human genetic variation. Researchers are beginning to develop population genomic data sets for evaluating the phenotypic impact of human TE polymorphisms. Because of the evidences of horizontal transfer of retrotransposons between different species genome, in this study we aimed to detect barley retrotransposons (Nikita and BAGY2) in the human genome. Inter retrotransposon amplified polymorphism polymerase chain reaction (IRAP PCR) were used to measure the distribution of Nikita and BAGY2 retroelements in the human genome. Analyses reveals that Nikita and BAGY2 are present in the human genome and show different distribution in the genome. The polymorphism ratios of retroelements suggest that Nikita and BAGY2 have been active retrotransposons in the human genome.

scholarly journals PRIMEval: Optimization and screening of multiplex oligonucleotide assays

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Rick Conzemius ◽  
Michaela Hendling ◽  
Stephan Pabinger ◽  
Ivan Barišić
Keyword(s):  
In Silico ◽  
Multiplex Polymerase Chain Reaction ◽  
Data Sets ◽  
Use Case ◽  
Chain Reaction ◽  
Experimental Conditions ◽  
Oligonucleotide Hybridization ◽  
Polymerase Chain ◽  
Derived Data ◽  
By Products

AbstractThe development of multiplex polymerase chain reaction and microarray assays is challenging due to primer dimer formation, unspecific hybridization events, the generation of unspecific by-products, primer depletion, and thus lower amplification efficiencies. We have developed a software workflow with three underlying algorithms that differ in their use case and specificity, allowing the complete in silico evaluation of such assays on user-derived data sets. We experimentally evaluated the method for the prediction of oligonucleotide hybridization events including resulting products and probes, self-dimers, cross-dimers and hairpins at different experimental conditions. The developed method allows explaining the observed artefacts through in silico WGS data and thermodynamic predictions. PRIMEval is available publicly at https://primeval.ait.ac.at.

Savitzky–Golay smoothing and differentiation for polymerase chain reaction quantification

2018 ◽  
Vol 96 (3) ◽  
pp. 380-389 ◽  
Author(s):  
Charles Gaudreault ◽  
Joanny Salvas ◽  
Joël Sirois
Keyword(s):  
Relative Error ◽  
Logistic Model ◽  
Data Sets ◽  
Threshold Method ◽  
Chain Reaction ◽  
Quantification Method ◽  
Curve Modeling ◽  
Polymerase Chain ◽  
The Impact ◽  
Inter Assay Variation

In quantitative PCR (qPCR), replicates can minimize the impact of intra-assay variation; however, inter-assay variations must be minimized to obtain a robust quantification method. The method proposed in this study uses Savitzky–Golay smoothing and differentiation (SGSD) to identify a derivative-maximum-based cycle of quantification. It does not rely on curve modeling, as is the case with many existing techniques. PCR fluorescence data sets challenged for inter-assay variations (different thermocycler units, different reagents batches, different operators, different standard curves, and different labs) were used for the evaluation. The algorithm was compared with a four-parameter logistic model (4PLM) method, the Cy0 method, and the threshold method. The SGSD method compared favourably with all methods in terms of inter-assay variation. SGSD was statistically different from the 4PLM (P = 0.03), Cy0 (P = 0.05), and threshold (P = 0.004) methods on relative error comparison basis. For intra-assay variations, SGSD outperformed the threshold method (P = 0.005) and equalled the 4PLM and Cy0 methods (P > 0.05) on relative error basis. Our results demonstrate that the SGSD method could potentially be an alternative to sigmoid modeling based methods (4PLM and Cy0) when PCR data are challenged for inter-assay variations.

scholarly journals A new test suggests that balancing selection maintains hundreds of non-synonymous polymorphisms in the human genome

2021 ◽  
Author(s):  
Vivak Soni ◽  
Michiel Vos ◽  
Adam Eyre-Walker
Keyword(s):  
Genetic Diversity ◽  
Human Genome ◽  
Balancing Selection ◽  
Genomic Data ◽  
Demographic Changes ◽  
Simple Test ◽  
Direct Estimate ◽  
Population Genomic

AbstractThe role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here we introduce a new test, based on the McDonald-Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and conclude that more than a thousand non-synonymous polymorphisms are subject to balancing selection.

scholarly journals Longitudinal samples of bacterial genomes potentially bias evolutionary analyses

2017 ◽  
Author(s):  
B.J. Arnold ◽  
W.P. Hanage
Keyword(s):  
Genomic Data ◽  
Real Data ◽  
Sampling Bias ◽  
Bacterial Genomes ◽  
Clock Rate ◽  
Rare Mutations ◽  
Constant Size ◽  
Population Genomic ◽  
Genomic Studies ◽  
Longitudinal Sampling

AbstractSamples of bacteria collected over a period of time are attractive for several reasons, including the ability to estimate the molecular clock rate and to detect fluctuations in allele frequencies over time. However, longitudinal datasets are occasionally used in analyses that assume samples were collected contemporaneously. Using both simulations and genomic data from Neisseria gonorrhoeae, Streptococcus mutans, Campylobacter jejuni, and Helicobacter pylori, we show that longitudinal samples (spanning more than a decade in real data) may suffer from considerable bias that inflates estimates of recombination and the number of rare mutations in a sample of genomic sequences. While longitudinal data are frequently accounted for using the serial coalescent, many studies use other programs or metrics, such as Tajima’s D, that are sensitive to these sampling biases and contain genomic data collected across many years. Notably, longitudinal samples from a population of constant size may exhibit evidence of exponential growth. We suggest that population genomic studies of bacteria should routinely account for temporal diversity in samples or provide evidence that longitudinal sampling bias does not affect conclusions.

scholarly journals The Malmo polymorphism of factor IX: establishing the genotypes by rapid analysis of DNA

Blood ◽  
1989 ◽  
Vol 73 (8) ◽  
pp. 2104-2107 ◽  
Author(s):  
JB Graham ◽  
GR Kunkel ◽  
GS Tennyson ◽  
ST Lord ◽  
DM Fowlkes
Keyword(s):  
Population Studies ◽  
Coagulation Factor ◽  
Rapid Analysis ◽  
Factor Ix ◽  
Small Samples ◽  
Coding Region ◽  
Chain Reaction ◽  
X Ray ◽  
Polymerase Chain ◽  
Enzyme Recognition

Abstract A DNA polymorphism in the coding region of coagulation factor IX-- potentially valuable for carrier detection, prenatal diagnosis, and population studies--was described in 1985. It had been discovered with monoclonal antibodies that distinguish between threonine and alanine as the 148th residue of the peptide. Its use as a diagnostic tool has been limited because threonine-containing factor IX (Malmo A) is dominant to alanine-containing factor IX (Malmo B) in immunoassays of plasma; therefore, detection of Malmo heterozygotes is not possible in all instances. A DNA method for recognizing all heterozygotes has been developed, but it also has limitations. We report the development of another DNA procedure based on amplification of the relevant DNA with the polymerase chain reaction (PCR). This method is quick, avoids the use of isotopes and x-ray film, and specifically identifies all the Malmo genotypes: hemizygotes, homozygotes, and heterozygotes. The procedure can be performed satisfactorily on small samples of blood (less than 1 mL) as suggested by Kogan et al (N Engl J Med 317:985, 1987). The method described is applicable to any genetic polymorphism that overlaps a restriction enzyme recognition site.

scholarly journals Cancer Bioinformatic Methods to Infer Meaningful Data from Small-Size Cohorts

2015 ◽  
Vol 14 ◽  
pp. CIN.S32696 ◽  
Author(s):  
Nabila Bennani-Baiti ◽  
Idriss M. Bennani-Baiti
Keyword(s):  
Signaling Pathways ◽  
Drug Targets ◽  
Genomic Data ◽  
Molecular Diagnostic ◽  
Intratumor Heterogeneity ◽  
Data Sets ◽  
Prognosis Factors ◽  
Genome Analyses ◽  
Size Data ◽  
Meaningful Data

Whole-genome analyses have uncovered that most cancer-relevant genes cluster into 12 signaling pathways. Knowledge of the signaling pathways and associated gene signatures not only allows us to understand the mechanisms of oncogenesis inherent to specific cancers but also provides us with drug targets, molecular diagnostic and prognosis factors, as well as biomarkers for patient risk stratification and treatment. Publicly available genomic data sets constitute a wealth of gene mining opportunities for hypothesis generation and testing. However, the increasingly recognized genetic and epigenetic inter- and intratumor heterogeneity, combined with the preponderance of small-size cohorts, hamper reliable analysis and discovery. Here, we review two methods that are used to infer meaningful biological events from small-size data sets and discuss some of their applications and limitations.

scholarly journals NPARS—A Novel Approach to Address Accuracy and Reproducibility in Genomic Data Science

2021 ◽  
Vol 4 ◽  
Author(s):  
Li Ma ◽  
Erich A. Peterson ◽  
Ik Jae Shin ◽  
Jason Muesse ◽  
Katy Marino ◽  
...  
Keyword(s):  
High Throughput ◽  
Quantitative Methods ◽  
Data Science ◽  
High Throughput Sequencing ◽  
Genomic Data ◽  
Scientific Data ◽  
Genomic Research ◽  
Data Sets ◽  
Novel Approach ◽  
Genomic Studies

Background: Accuracy and reproducibility are vital in science and presents a significant challenge in the emerging discipline of data science, especially when the data are scientifically complex and massive in size. Further complicating matters, in the field of genomic-based science high-throughput sequencing technologies generate considerable amounts of data that needs to be stored, manipulated, and analyzed using a plethora of software tools. Researchers are rarely able to reproduce published genomic studies.Results: Presented is a novel approach which facilitates accuracy and reproducibility for large genomic research data sets. All data needed is loaded into a portable local database, which serves as an interface for well-known software frameworks. These include python-based Jupyter Notebooks and the use of RStudio projects and R markdown. All software is encapsulated using Docker containers and managed by Git, simplifying software configuration management.Conclusion: Accuracy and reproducibility in science is of a paramount importance. For the biomedical sciences, advances in high throughput technologies, molecular biology and quantitative methods are providing unprecedented insights into disease mechanisms. With these insights come the associated challenge of scientific data that is complex and massive in size. This makes collaboration, verification, validation, and reproducibility of findings difficult. To address these challenges the NGS post-pipeline accuracy and reproducibility system (NPARS) was developed. NPARS is a robust software infrastructure and methodology that can encapsulate data, code, and reporting for large genomic studies. This paper demonstrates the successful use of NPARS on large and complex genomic data sets across different computational platforms.

2. DNA

2016 ◽  
Author(s):  
Aysha Divan ◽  
Janice A. Royds
Keyword(s):  
Polymerase Chain Reaction ◽  
Dna Replication ◽  
Gene Cloning ◽  
Human Genome ◽  
Complete Sequence ◽  
Chain Reaction ◽  
Body Cell ◽  
Polymerase Chain ◽  
Significant Milestone

Another significant milestone was the publication in 2003 of the complete sequence of the human genome—the entire DNA contained within the forty-six chromosomes located in the nucleus of each human somatic (body) cell. Once this was published, further worldwide projects were launched to work out what the functions of these genes and other regions of the genome actually were. ‘DNA’ outlines the components of the human genome and their organization; DNA replication; mutations and correction mechanisms; polymorphisms; and new DNA technologies, including gene cloning, the polymerase chain reaction, and sequencing methods. Finally, bioinformatics and the subsequent issues of privacy and how this information could be used are discussed.

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