Two common profiles exist for genomic oligonucleotide frequencies.
Ontology highlight
ABSTRACT: Background
It was reported that there is a majority profile for trinucleotide frequencies among genomes. And further study has revealed that two common profiles, rather than one majority profile, exist for genomic trinucleotide frequencies. However, the origins of the common/majority profile remain elusive. Moreover, it is not clear whether the features of common profile may be extended to oligonucleotides other than trinucleotides.Findings
We analyzed 571 prokaryotic genomes (chromosomes) and some selected eukaryotic nuclear genomes as well as other genetic systems to study their compositional features. We found that there are also two common profiles for genomic oligonucleotide frequencies: one is from low-GC content genomes, and the other is from high-GC content genomes. Furthermore, each common profile is highly correlated to the average profile of random sequences with corresponding GC content and generated according to first-order symmetry.Conclusions
The causes for the existence of two common profiles would mainly be GC content variations and strand symmetry of genomic sequences. Therefore, both GC content and strand symmetry would play important roles in genome evolution.
SUBMITTER: Zhang SH
PROVIDER: S-EPMC3532236 | biostudies-literature | 2012 Nov
REPOSITORIES: biostudies-literature
Publications
Two common profiles exist for genomic oligonucleotide frequencies.
Zhang Shang-Hong SH Wang Lei L
BMC research notes 20121117
<h4>Background</h4>It was reported that there is a majority profile for trinucleotide frequencies among genomes. And further study has revealed that two common profiles, rather than one majority profile, exist for genomic trinucleotide frequencies. However, the origins of the common/majority profile remain elusive. Moreover, it is not clear whether the features of common profile may be extended to oligonucleotides other than trinucleotides.<h4>Findings</h4>We analyzed 571 prokaryotic genomes (ch ...[more]
Similar Datasets
Project description:BACKGROUND: DNA barcoding refers to the use of short DNA sequences for rapid identification of species. Genetic distance or character attributes of a particular barcode locus discriminate the species. We report an efficient approach to analyze short sequence data for discrimination between species. METHODOLOGY AND PRINCIPAL FINDINGS: A new approach, Oligonucleotide Frequency Range (OFR) of barcode loci for species discrimination is proposed. OFR of the loci that discriminates between species was characteristic of a species, i.e., the maxima and minima within a species did not overlap with that of other species. We compared the species resolution ability of different barcode loci using p-distance, Euclidean distance of oligonucleotide frequencies, nucleotide-character based approach and OFR method. The species resolution by OFR was either higher or comparable to the other methods. A short fragment of 126 bp of internal transcribed spacer region in ribosomal RNA gene was sufficient to discriminate a majority of the species using OFR. CONCLUSIONS/SIGNIFICANCE: Oligonucleotide frequency range of a barcode locus can discriminate between species. Ability to discriminate species using very short DNA fragments may have wider applications in forensic and conservation studies.
| S-EPMC2924895 | biostudies-literature
Project description:Constructing an accurate predictive model for clinical decision-making on the basis of a relatively small number of tumor samples with high-dimensional microarray data remains a very challenging problem. The validity of such models has been seriously questioned due to their failure in clinical validation using independent samples. Besides the statistical issues such as selection bias, some studies further implied the probable reason was improper sample selection that did not resemble the genomic space defined by the training population. Assuming that predictions would be more reliable for interpolation than extrapolation, we set to investigate the impact of applicability domain (AD) on model performance in microarray-based genomic research by evaluating and comparing model performance for samples with different extrapolation degrees. We found that the issue of applicability domain may not exist in microarray-based genomic research for clinical applications. Therefore, it is not practicable to improve model validity based on applicability domain.
| S-EPMC2883551 | biostudies-literature
Project description:BackgroundInsects have multiple hemocyte morphotypes with different functions as do vertebrates, however, their hematopoietic lineages are largely unexplored with the exception of Drosophila melanogaster.Methodology/principal findingsTo study the hematopoietic lineage of the silkworm, Bombyx mori, we investigated in vivo and in vitro differentiation of hemocyte precursors in the hematopoietic organ (HPO) into the four mature hemocyte subsets, namely, plasmatocytes, granulocytes, oenocytoids, and spherulocytes. Five days after implantation of enzymatically-dispersed HPO cells from a GFP-expressing transgenic line into the hemocoel of normal larvae, differentiation into plasmatocytes, granulocytes and oenocytoids, but not spherulocytes, was observed. When the HPO cells were cultured in vitro, plasmatocytes appeared rapidly, and oenocytoids possessing prophenol oxidase activity appeared several days later. HPO cells were also able to differentiate into a small number of granulocytes, but not into spherulocytes. When functionally mature plasmatocytes were cultured in vitro, oenocytoids were observed 10 days later. These results suggest that the hemocyte precursors in HPO first differentiate into plasmatocytes, which further change into oenocytoids.Conclusions/significanceFrom these results, we propose that B. mori hemocytes can be divided into two major lineages, a granulocyte lineage and a plasmatocyte-oenocytoid lineage. The origins of the spherulocytes could not be determined in this study. We construct a model for the hematopoietic lineages at the larval stage of B. mori.
| S-EPMC2911379 | biostudies-literature
Project description:Array-based comparative genomic hybridization (CGH) measures copy-number variations at multiple loci simultaneously, providing an important tool for studying cancer and developmental disorders and for developing diagnostic and therapeutic targets. Arrays for CGH based on PCR products representing assemblies of BAC or cDNA clones typically require maintenance, propagation, replication, and verification of large clone sets. Furthermore, it is difficult to control the specificity of the hybridization to the complex sequences that are present in each feature of such arrays. To develop a more robust and flexible platform, we created probe-design methods and assay protocols that make oligonucleotide microarrays synthesized in situ by inkjet technology compatible with array-based comparative genomic hybridization applications employing samples of total genomic DNA. Hybridization of a series of cell lines with variable numbers of X chromosomes to arrays designed for CGH measurements gave median ratios for X-chromosome probes within 6% of the theoretical values (0.5 for XY/XX, 1.0 for XX/XX, 1.4 for XXX/XX, 2.1 for XXXX/XX, and 2.6 for XXXXX/XX). Furthermore, these arrays detected and mapped regions of single-copy losses, homozygous deletions, and amplicons of various sizes in different model systems, including diploid cells with a chromosomal breakpoint that has been mapped and sequenced to a precise nucleotide and tumor cell lines with highly variable regions of gains and losses. Our results demonstrate that oligonucleotide arrays designed for CGH provide a robust and precise platform for detecting chromosomal alterations throughout a genome with high sensitivity even when using full-complexity genomic samples.
| S-EPMC535426 | biostudies-literature
Project description:BackgroundThe increasing number of sequenced prokaryotic genomes contains a wealth of genomic data that needs to be effectively analysed. A set of statistical tools exists for such analysis, but their strengths and weaknesses have not been fully explored. The statistical methods we are concerned with here are mainly used to examine similarities between archaeal and bacterial DNA from different genomes. These methods compare observed genomic frequencies of fixed-sized oligonucleotides with expected values, which can be determined by genomic nucleotide content, smaller oligonucleotide frequencies, or be based on specific statistical distributions. Advantages with these statistical methods include measurements of phylogenetic relationship with relatively small pieces of DNA sampled from almost anywhere within genomes, detection of foreign/conserved DNA, and homology searches. Our aim was to explore the reliability and best suited applications for some popular methods, which include relative oligonucleotide frequencies (ROF), di- to hexanucleotide zero'th order Markov methods (ZOM) and 2.order Markov chain Method (MCM). Tests were performed on distant homology searches with large DNA sequences, detection of foreign/conserved DNA, and plasmid-host similarity comparisons. Additionally, the reliability of the methods was tested by comparing both real and random genomic DNA.ResultsOur findings show that the optimal method is context dependent. ROFs were best suited for distant homology searches, whilst the hexanucleotide ZOM and MCM measures were more reliable measures in terms of phylogeny. The dinucleotide ZOM method produced high correlation values when used to compare real genomes to an artificially constructed random genome with similar %GC, and should therefore be used with care. The tetranucleotide ZOM measure was a good measure to detect horizontally transferred regions, and when used to compare the phylogenetic relationships between plasmids and hosts, significant correlation (R2 = 0.4) was found with genomic GC content and intra-chromosomal homogeneity.ConclusionThe statistical methods examined are fast, easy to implement, and powerful for a number of different applications involving genomic sequence comparisons. However, none of the measures examined were superior in all tests, and therefore the choice of the statistical method should depend on the task at hand.
| S-EPMC2289816 | biostudies-literature
Project description:MotivationOne of the most widespread methods used in taxonomy studies to distinguish between strains or taxa is the calculation of average nucleotide identity. It requires a computationally expensive alignment step and is therefore not suitable for large-scale comparisons. Short oligonucleotide-based methods do offer a faster alternative but at the expense of accuracy. Here, we aim to address this shortcoming by providing a software that implements a novel method based on short-oligonucleotide frequencies to compute inter-genomic distances.ResultsOur tetranucleotide and hexanucleotide implementations, which were optimized based on a taxonomically well-defined set of over 200 newly sequenced bacterial genomes, are as accurate as the short oligonucleotide-based method TETRA and average nucleotide identity, for identifying bacterial species and strains, respectively. Moreover, the lightweight nature of this method makes it applicable for large-scale analyses.Availability and implementationThe method introduced here was implemented, together with other existing methods, in a dependency-free software written in C, GenDisCal, available as source code from https://github.com/LM-UGent/GenDisCal. The software supports multithreading and has been tested on Windows and Linux (CentOS). In addition, a Java-based graphical user interface that acts as a wrapper for the software is also available.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC7178395 | biostudies-literature
Project description:BACKGROUND: The induction of genomic deletions by physical- or chemical- agents is an easy and inexpensive means to generate a genome-saturating collection of mutations. Different mutagens can be selected to ensure a mutant collection with a range of deletion sizes. This would allow identification of mutations in single genes or, alternatively, a deleted group of genes that might collectively govern a trait (e.g., quantitative trait loci, QTL). However, deletion mutants have not been widely used in functional genomics, because the mutated genes are not tagged and therefore, difficult to identify. Here, we present a microarray-based approach to identify deleted genomic regions in rice mutants selected from a large collection generated by gamma ray or fast neutron treatment. Our study focuses not only on the utility of this method for forward genetics, but also its potential as a reverse genetics tool through accumulation of hybridization data for a collection of deletion mutants harboring multiple genetic lesions. RESULTS: We demonstrate that hybridization of labeled genomic DNA directly onto the Affymetrix Rice GeneChip allows rapid localization of deleted regions in rice mutants. Deletions ranged in size from one gene model to approximately 500 kb and were predicted on all 12 rice chromosomes. The utility of the technique as a tool in forward genetics was demonstrated in combination with an allelic series of mutants to rapidly narrow the genomic region, and eventually identify a candidate gene responsible for a lesion mimic phenotype. Finally, the positions of mutations in 14 mutants were aligned onto the rice pseudomolecules in a user-friendly genome browser to allow for rapid identification of untagged mutations http://irfgc.irri.org/cgi-bin/gbrowse/IR64_deletion_mutants/. CONCLUSION: We demonstrate the utility of oligonucleotide arrays to discover deleted genes in rice. The density and distribution of deletions suggests the feasibility of a database saturated with deletions across the rice genome. This community resource can continue to grow with further hybridizations, allowing researchers to quickly identify mutants that harbor deletions in candidate genomic regions, for example, regions containing QTL of interest.
| S-EPMC2666768 | biostudies-literature
Project description:Array comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome.This paper presents a new probe selection algorithm (PanArray) that can tile multiple whole genomes using a minimal number of probes. Unlike arrays built on clustered gene families, PanArray uses an unbiased, probe-centric approach that does not rely on annotations, gene clustering, or multi-alignments. Instead, probes are evenly tiled across all sequences of the pan-genome at a consistent level of coverage. To minimize the required number of probes, probes conserved across multiple strains in the pan-genome are selected first, and additional probes are used only where necessary to span polymorphic regions of the genome. The viability of the algorithm is demonstrated by array designs for seven different bacterial pan-genomes and, in particular, the design of a 385,000 probe array that fully tiles the genomes of 20 different Listeria monocytogenes strains with overlapping probes at greater than twofold coverage.PanArray is an oligonucleotide probe selection algorithm for tiling multiple genome sequences using a minimal number of probes. It is capable of fully tiling all genomes of a species on a single microarray chip. These unique pan-genome tiling arrays provide maximum flexibility for the analysis of both known and uncharacterized strains.
| S-EPMC2753849 | biostudies-literature
Project description:BACKGROUND:A fundamental issue in elderly care is targeting those older people at risk and in need of care interventions. Frailty is widely used to capture variations in health risks but there is no general consensus on the conceptualization of frailty. Indeed, there is considerable heterogeneity in the group of older people characterized as frail. This research identifies frailty profiles based on the physical, psychological, social and cognitive domains of functioning and the severity of the problems within these domains. METHODS:This research was a secondary data-analysis of older persons derived from The Older Person and Informal Caregiver Minimum Dataset. Selected respondents were 60 years and older (n =?43,704; 59.6% female). The following variables were included: self-reported health, cognitive functioning, social functioning, mental health, morbidity status, and functional limitations. Using latent class analysis, the population was divided in subpopulations that were subsequently discussed in a focus group with older people for further validation. RESULTS:We distinguished six frailty profiles: relatively healthy; mild physically frail; psychologically frail; severe physically frail; medically frail and multi-frail. The relatively healthy had limited problems across all domains. In three profiles older people mostly had singular problems in either the physical or psychological domain and the severity of the problems differed. Two remaining profiles were multidimensional with a combination of problems that extended to the social and cognitive domains. CONCLUSIONS:Our research provides an empirical base for meaningful frailty profiles. The profiles showed specific patterns underlying the problems in different domains of functioning. The heterogeneous population of frail older people has differing needs and faces different health issues that should be considered to tailor care interventions. Evaluation research of these interventions should acknowledge the heterogeneity of frailty by profiling.
| S-EPMC5885355 | biostudies-literature
Project description:Cell surface heparan sulfate proteoglycans (HSPGs) serve as primary attachment receptors for human papillomaviruses (HPVs). To demonstrate that a biologically functional HPV-receptor interaction is restricted to a specific subset of HSPGs, we first explored the role of HSPG glucosaminoglycan side chain modifications. We demonstrate that HSPG O sulfation is essential for HPV binding and infection, whereas de-N-sulfated heparin interfered with VLP binding but not with HPV pseudoinfection. This points to differences in VLP-HSPG and pseudovirion-HSPG interactions. Interestingly, internalization kinetics of VLPs and pseudovirions, as measured by fluorescence-activated cell sorting analysis, also differ significantly with approximate half times of 3.5 and 7.5 h, respectively. These data suggest that differences in HSPG binding significantly influence postbinding events. We also present evidence that pseudovirions undergo a conformational change after cell attachment. A monoclonal antibody (H33.J3), which displays negligible effectiveness in preattachment neutralization assays, efficiently neutralizes cell-bound virions. However, no difference in H33.J3 binding to pseudovirions and VLPs was observed in enzyme-linked immunosorbent assay and virus capture assays. In contrast to antibody H33.B6, which displays equal efficiencies in pre- and postattachment neutralization assays, H33.J3 does not block VLP binding to heparin, demonstrating that it interferes with steps subsequent to virus binding. Our data strongly suggest that H33.J3 recognizes a conformation-dependent epitope in capsid protein L1, which undergoes a structural change after cell attachment.
| S-EPMC296061 | biostudies-other