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26 results for “codon bias”
Vibrio cholerae codon biased genes list
<p>Files called top25: For each codon, 25% of genes with highest differential codon usage are listed. </p> <p>Files called top: For each codon, top genes with highest differential codon usage are listed, as indicated by violin plots in pdf files. </p> <p>Excel sheet with assigned codon usage for each codon and each gene.</p> <p>Whole genome of Vibrio cholerae N16961</p>
Data from: Antibody production relies on the tRNA inosine wobble modification to meet biased codon demand
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Data from: Antagonistic relationships between intron content and codon usage bias of genes in three mosquito species: functional and evolutionary implications
Genome biology of mosquitoes holds potential in developing knowledge-based control strategies against vector-borne diseases such as malaria, dengue, West Nile Virus and others. Although the genomes of three major vector mosquitoes have been sequenced, attempts to elucidate the relationship between intron and codon usage bias across species in phylogenetic contexts are limited. In this study, we investigated the relationship between intron content and codon bias of orthologous genes among three vector mosquito species. We found an antagonistic relationship between codon usage bias and the intron number of genes in each mosquito species. The pattern is further evident among the intronless and the intron-containing orthologous genes associated with either low or high codon bias among the three species. Furthermore, the co-variance between codon bias and intron number has a directional component associated with the species phylogeny when compared with other non-mosquito insects. By applying a maximum likelihood based continuous regression method, we show that codon bias and intron content of genes vary among the insects in a phylogeny dependent manner but with no evidence of adaptive radiation or species-specific adaptation. We discuss the functional and evolutionary significance of antagonistic relationships between intron content and codon bias.
Data from: Mitochondrial phylogenomics of early land plants: mitigating the effects of saturation, compositional heterogeneity, and codon-usage bias
Phylogenetic analyses using concatenation of genomic-scale data have been seen as the panacea to resolving the incongruences among inferences from few or single genes. However, phylogenomics may also suffer from systematic errors, due to the, perhaps cumulative, effects of saturation, among-taxa compositional (GC content) heterogeneity, or codon-usage bias plaguing the individual nucleotide loci that are concatenated. Here we provide an example of how these factors affect the inferences of the phylogeny of early land plants based on mitochondrial genomic data. Mitochondrial sequences evolve slowly in plants and hence are thought to be suitable for resolving deep relationships. We newly assembled mitochondrial genomes from 20 bryophytes, complemented these with 40 other streptophytes (land plants plus algal outgroups), compiling a data matrix of 60 taxa and 41 mitochondrial genes. Homogeneous analyses of the concatenated nucleotide data resolve mosses as sister-group to the remaining land plants. However, the corresponding translated amino acid data support the liverwort lineage in this position. Both results receive weak to moderate support in maximum likelihood analyses, but strong support in Bayesian inferences. Tests of alternative hypotheses using either nucleotide or amino-acid data provide implicit support for the respective optimal topologies. By analyzing the nucleotide data, we found that the 3rd codon positions are more saturated than the 1st and 2nd codon positions, and excluding these from the analyses leads to a topology congruent with that obtained using amino-acid data. Further, we determined that land plant lineages differ in their nucleotide composition, and in their usage of synonymous codon variants. Composition heterogeneous Bayesian analyses employing a non-stationary model that accounts for variation in among-lineage composition, and inferences from degenerated nucleotide data that avoids the effects of synonymous mutations that underlie codon-usage bias, again recovered liverworts being sister to the remaining land plants. These analyses indicate that the discrepancy between the nucleotide-based and the amino acid-based trees is caused by the lineage specific, parallel compositional bias, or synonymous mutations driving codon-usage bias, as well as saturation in the 3rd codon positions. While genomic data may generate highly supported phylogenetic trees, these inferences may be artifacts. We suggest that phylogenomic analyses should assess the possible impact of potential biases through comparisons of protein coding gene data and their amino-acids translations, by analyzing data modeling compositional bias, and by excluding nucleotide noisy signals due to saturation or codon-usage bias. We caution against relying on any one presentation of the data (nucleotide or amino acid) or any one type of analysis even when analyzing large-scale data sets, no matter how well-supported, without fully exploring the effects of substitution models.
Variability in codon usage in Coronaviruses is mainly driven by mutational bias and selective constraints on CpG dinucleotide
<p>Supplementary Figures and Tables for the article called: " Variability in codon usage in Coronaviruses<em> </em>is mainly driven by mutational bias and selective constraints on CpG dinucleotide<sup>"</sup></p>
Data from: Mitochondrial phylogenomics of early land plants: mitigating the effects of saturation, compositional heterogeneity, and codon-usage bias
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Data from: Serine codon-usage bias in deep phylogenomics: pancrustacean relationships as a case study
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Data from: Antagonistic relationships between intron content and codon usage bias of genes in three mosquito species: functional and evolutionary implications
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A snoRNA–tRNA modification network governs codon-biased cellular states [RMseq]
GEO Series GSE234599. Homo sapiens. 12 samples. Type: Other.
Causal signals between codon bias, mRNA structure and the efficiency of translation and elongation
GEO Series GSE63789. Saccharomyces cerevisiae. 10 samples. Type: Expression profiling by high throughput sequencing; Other.
Deciphering a secondary genetic code in neurons: the role of codon bias in regulating neuronal protein levels and implications for Elongator-mediated neurological disease
GEO Series GSE80130. Mus musculus. 8 samples. Type: Expression profiling by array.
A snoRNA–tRNA modification network governs codon-biased cellular states [PARIS2-seq]
GEO Series GSE234598. Homo sapiens. 9 samples. Type: Other.
A snoRNA–tRNA modification network governs codon-biased cellular states [RNAseq & Riboseq]
GEO Series GSE234687. Homo sapiens; Mus musculus. 48 samples. Type: Expression profiling by high throughput sequencing; Other; Non-coding RNA profiling by high throughput sequencing.
Native CFTR codon bias controls translation rate to balance off-pathway aggregation and channel function by conformational imprinting
GEO Series GSE305005. Homo sapiens. 14 samples. Type: Other.
A snoRNA–tRNA modification network governs codon-biased cellular states
GEO Series GSE234689. Mus musculus; Homo sapiens. 69 samples. Type: Other; Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Queuosine-tRNA promotes sex-dependent learning and memory formation by maintaining codon-biased translation elongation speed.
GEO Series GSE180766. Mus musculus. 20 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Threonine fuels glioblastoma through YRDC-mediated codon-biased translational reprogramming (Ribosome profiling)
GEO Series GSE229672. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing; Other.
Threonine fuels glioblastoma through YRDC-mediated codon-biased translational reprogramming (tRNA-Seq)
GEO Series GSE245043. Homo sapiens. 9 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Threonine fuels glioblastoma through YRDC-mediated codon-biased translational reprogramming (RNA-Seq)
GEO Series GSE229671. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Chemotherapeutic agents and leucine deprivation induce codon-biased aberrant protein production in cancer
GEO Series GSE276695. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.