Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Large-scale k-mer-based analysis of the informational properties of genomes, comparative genomics and taxonomy.

ABSTRACT: Information theoretic approaches are ubiquitous and effective in a wide variety of bioinformatics applications. In comparative genomics, alignment-free methods, based on short DNA words, or k-mers, are particularly powerful. We evaluated the utility of varying k-mer lengths for genome comparisons by analyzing their sequence space coverage of 5805 genomes in the KEGG GENOME database. In subsequent analyses on four k-mer lengths spanning the relevant range (11, 21, 31, 41), hierarchical clustering of 1634 genus-level representative genomes using pairwise 21- and 31-mer Jaccard similarities best recapitulated a phylogenetic/taxonomic tree of life with clear boundaries for superkingdom domains and high subtree similarity for named taxons at lower levels (family through phylum). By analyzing ~14.2M prokaryotic genome comparisons by their lowest-common-ancestor taxon levels, we detected many potential misclassification errors in a curated database, further demonstrating the need for wide-scale adoption of quantitative taxonomic classifications based on whole-genome similarity.

SUBMITTER: Bussi Y

PROVIDER: S-EPMC8516232 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Atlas of group A streptococcal vaccine candidates compiled using large-scale comparative genomics.

Project description:Group A Streptococcus (GAS; Streptococcus pyogenes) is a bacterial pathogen for which a commercial vaccine for humans is not available. Employing the advantages of high-throughput DNA sequencing technology to vaccine design, we have analyzed 2,083 globally sampled GAS genomes. The global GAS population structure reveals extensive genomic heterogeneity driven by homologous recombination and overlaid with high levels of accessory gene plasticity. We identified the existence of more than 290 clinically associated genomic phylogroups across 22 countries, highlighting challenges in designing vaccines of global utility. To determine vaccine candidate coverage, we investigated all of the previously described GAS candidate antigens for gene carriage and gene sequence heterogeneity. Only 15 of 28 vaccine antigen candidates were found to have both low naturally occurring sequence variation and high (>99%) coverage across this diverse GAS population. This technological platform for vaccine coverage determination is equally applicable to prospective GAS vaccine antigens identified in future studies.

| S-EPMC6650292 | biostudies-literature

Diversity and relationships of cocirculating modern human rotaviruses revealed using large-scale comparative genomics.

Project description:Group A rotaviruses (RVs) are 11-segmented, double-stranded RNA viruses and are primary causes of gastroenteritis in young children. Despite their medical relevance, the genetic diversity of modern human RVs is poorly understood, and the impact of vaccine use on circulating strains remains unknown. In this study, we report the complete genome sequence analysis of 58 RVs isolated from children with severe diarrhea and/or vomiting at Vanderbilt University Medical Center (VUMC) in Nashville, TN, during the years spanning community vaccine implementation (2005 to 2009). The RVs analyzed include 36 G1P[8], 18 G3P[8], and 4 G12P[8] Wa-like genogroup 1 strains with VP6-VP1-VP2-VP3-NSP1-NSP2-NSP3-NSP4-NSP5/6 genotype constellations of I1-R1-C1-M1-A1-N1-T1-E1-H1. By constructing phylogenetic trees, we identified 2 to 5 subgenotype alleles for each gene. The results show evidence of intragenogroup gene reassortment among the cocirculating strains. However, several isolates from different seasons maintained identical allele constellations, consistent with the notion that certain RV clades persisted in the community. By comparing the genes of VUMC RVs to those of other archival and contemporary RV strains for which sequences are available, we defined phylogenetic lineages and verified that the diversity of the strains analyzed in this study reflects that seen in other regions of the world. Importantly, the VP4 and VP7 proteins encoded by VUMC RVs and other contemporary strains show amino acid changes in or near neutralization domains, which might reflect antigenic drift of the virus. Thus, this large-scale, comparative genomic study of modern human RVs provides significant insight into how this pathogen evolves during its spread in the community.

| S-EPMC3416154 | biostudies-literature

k mdiff, large-scale and user-friendly differential k-mer analyses.

Project description:SummaryGenome wide association studies elucidate links between genotypes and phenotypes. Recent studies point out the interest of conducting such experiments using k-mers as the base signal instead of single-nucleotide polymorphisms. We propose a tool, kmdiff, that performs differential k-mer analyses on large sequencing cohorts in an order of magnitude less time and memory than previously possible.Availabilityand implementationhttps://github.com/tlemane/kmdiff.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC9750116 | biostudies-literature

Algorithm for large-scale clustering across multiple genomes.

Project description:Identifying genomic regions that descended from a common ancestor helps us study the gene function and genome evolution. In distantly related genomes, clusters of homologous gene pairs are evidently used in function prediction, operon detection, etc. Currently, there are many kinds of computational methods that have been proposed defining gene clusters to identify gene families and operons. However, most of those algorithms are only available on a data set of small size. We developed an efficient gene clustering algorithm that can be applied on hundreds of genomes at the same time. This approach allows for large-scale study of evolutionary relationships of gene clusters and study of operon formation and destruction. An analysis of proposed algorithms shows that more biological insight can be obtained by analyzing gene clusters across hundreds of genomes, which can help us understand operon occurrences, gene orientations and gene rearrangements.

| S-EPMC3218420 | biostudies-other

Structural characterization of genomes by large scale sequence-structure threading: application of reliability analysis in structural genomics.

Project description:BackgroundWe establish that the occurrence of protein folds among genomes can be accurately described with a Weibull function. Systems which exhibit Weibull character can be interpreted with reliability theory commonly used in engineering analysis. For instance, Weibull distributions are widely used in reliability, maintainability and safety work to model time-to-failure of mechanical devices, mechanisms, building constructions and equipment.ResultsWe have found that the Weibull function describes protein fold distribution within and among genomes more accurately than conventional power functions which have been used in a number of structural genomic studies reported to date. It has also been found that the Weibull reliability parameter beta for protein fold distributions varies between genomes and may reflect differences in rates of gene duplication in evolutionary history of organisms.ConclusionsThe results of this work demonstrate that reliability analysis can provide useful insights and testable predictions in the fields of comparative and structural genomics.

| S-EPMC499543 | biostudies-literature

Ontology-based annotations and semantic relations in large-scale (epi)genomics data.

Project description:Public repositories of large-scale biological data currently contain hundreds of thousands of experiments, including high-throughput sequencing and microarray data. The potential of using these resources to assemble data sets combining samples previously not associated is vastly unexplored. This requires the ability to associate samples with clear annotations and to relate experiments matched with different annotation terms. In this study, we illustrate the semantic annotation of Gene Expression Omnibus samples metadata using concepts from biomedical ontologies, focusing on the association of thousands of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) samples with a given target, tissue and disease state. Next, we demonstrate the feasibility of quantitatively measuring the semantic similarity between different samples, with the aim of combining experiments associated with the same or similar semantic annotations, thus allowing the generation of large data sets without the need of additional experiments. We compared tools based on Unified Medical Language System with tools that use topic-specific ontologies, showing that the second approach outperforms the first both in the annotation process and in the computation of semantic similarity measures. Finally, we demonstrated the potential of this approach by identifying semantically homogeneous groups of ChIP-seq samples targeting the Myc transcription factor, and expanding this data set with semantically coherent epigenetic samples. The semantic information of these data sets proved to be coherent with the ChIP-seq signal and with the current knowledge about this transcription factor.

| S-EPMC5429001 | biostudies-literature

Large-scale comparative genomic ranking of taxonomically restricted genes (TRGs) in bacterial and archaeal genomes.

Project description:BackgroundLineage-specific, or taxonomically restricted genes (TRGs), especially those that are species and strain-specific, are of special interest because they are expected to play a role in defining exclusive ecological adaptations to particular niches. Despite this, they are relatively poorly studied and little understood, in large part because many are still orphans or only have homologues in very closely related isolates. This lack of homology confounds attempts to establish the likelihood that a hypothetical gene is expressed and, if so, to determine the putative function of the protein.Methodology/principal findingsWe have developed "QIPP" ("Quality Index for Predicted Proteins"), an index that scores the "quality" of a protein based on non-homology-based criteria. QIPP can be used to assign a value between zero and one to any protein based on comparing its features to other proteins in a given genome. We have used QIPP to rank the predicted proteins in the proteomes of Bacteria and Archaea. This ranking reveals that there is a large amount of variation in QIPP scores, and identifies many high-scoring orphans as potentially "authentic" (expressed) orphans. There are significant differences in the distributions of QIPP scores between orphan and non-orphan genes for many genomes and a trend for less well-conserved genes to have lower QIPP scores.ConclusionsThe implication of this work is that QIPP scores can be used to further annotate predicted proteins with information that is independent of homology. Such information can be used to prioritize candidates for further analysis. Data generated for this study can be found in the OrphanMine at http://www.genomics.ceh.ac.uk/orphan_mine.

| S-EPMC1824705 | biostudies-literature

Multilevel Genomics-Based Taxonomy of Renal Cell Carcinoma.

Project description:On the basis of multidimensional and comprehensive molecular characterization (including DNA methalylation and copy number, RNA, and protein expression), we classified 894 renal cell carcinomas (RCCs) of various histologic types into nine major genomic subtypes. Site of origin within the nephron was one major determinant in the classification, reflecting differences among clear cell, chromophobe, and papillary RCC. Widespread molecular changes associated with TFE3 gene fusion or chromatin modifier genes were present within a specific subtype and spanned multiple subtypes. Differences in patient survival and in alteration of specific pathways (including hypoxia, metabolism, MAP kinase, NRF2-ARE, Hippo, immune checkpoint, and PI3K/AKT/mTOR) could further distinguish the subtypes. Immune checkpoint markers and molecular signatures of T cell infiltrates were both highest in the subtype associated with aggressive clear cell RCC. Differences between the genomic subtypes suggest that therapeutic strategies could be tailored to each RCC disease subset.

| S-EPMC4794376 | biostudies-literature

Towards next-generation diagnostics for tuberculosis: identification of novel molecular targets by large-scale comparative genomics.

Project description:Motivation: Tuberculosis (TB) remains one of the main causes of death worldwide. The long and cumbersome process of culturing Mycobacterium tuberculosis complex (MTBC) bacteria has encouraged the development of specific molecular tools for detecting the pathogen. Most of these tools aim to become novel TB diagnostics, and big efforts and resources are invested in their development, looking for the endorsement of the main public health agencies. Surprisingly, no study has been conducted where the vast amount of genomic data available is used to identify the best MTBC diagnostic markers.Results: In this work, we used large-scale comparative genomics to identify 40 MTBC-specific loci. We assessed their genetic diversity and physiological features to select 30 that are good targets for diagnostic purposes. Some of these markers could be used to assess the physiological status of the bacilli. Remarkably, none of the most used MTBC markers is in our catalog. Illustrating the translational potential of our work, we develop a specific qPCR assay for quantification and identification of MTBC DNA. Our rational design of targeted molecular assays for TB could be used in many other fields of clinical and basic research.Availability and implementation: The database of non-tuberculous mycobacteria assemblies can be accessed at: 10.5281/zenodo.3374377.Supplementary information: Supplementary data are available at Bioinformatics online.

| S-EPMC7703747 | biostudies-literature

Sequencing-based large-scale genomics approaches with small numbers of isolated maize meiocytes.

Project description:High-throughput sequencing has become the large-scale approach of choice to study global gene expression and the distribution of specific chromatin marks and features. However, the limited availability of large amounts of purified cells made it very challenging to apply sequencing-based techniques in plant meiosis research in the past. In this paper, we describe a method to isolate meiocytes from maize anthers and detailed protocols to successfully perform RNA-seq, smRNA-seq, H3K4me3-ChIP-seq, and DNA bisulfite conversion sequencing with 5000-30,000 isolated maize male meiotic cells. These methods can be adjusted for other flowering plant species as well.

| S-EPMC3933774 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data