Database Resources of the National Center for Biotechnology Information

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doi:10.1093/nar/gkw1071

Cited by 748 publications

(420 citation statements)

References 12 publications

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“…A BLASTN search with the command line parameters max_target_seqs 10000000 -dust no -word_size 8 was performed for the unique spacer set against the virus part (NCBI taxid 10,239) of the NR/NT nucleotide collection (83) and against the prokaryotic database described above. The hits with at least 95% sequence identity to a spacer and at least 95% sequence coverage (i.e., one or two mismatches were allowed) were accepted as protospacers.…”

Section: Methodsmentioning

confidence: 99%

The CRISPR Spacer Space Is Dominated by Sequences from Species-Specific Mobilomes

Shmakov

Sitnik

Makarova

et al. 2017

mBio

198

195

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Clustered regularly interspaced short palindromic repeats and CRISPRassociated protein (CRISPR-Cas) systems store the memory of past encounters with foreign DNA in unique spacers that are inserted between direct repeats in CRISPR arrays. For only a small fraction of the spacers, homologous sequences, called protospacers, are detectable in viral, plasmid, and microbial genomes. The rest of the spacers remain the CRISPR "dark matter." We performed a comprehensive analysis of the spacers from all CRISPR-cas loci identified in bacterial and archaeal genomes, and we found that, depending on the CRISPR-Cas subtype and the prokaryotic phylum, protospacers were detectable for 1% to about 19% of the spacers (~7% global average). Among the detected protospacers, the majority, typically 80 to 90%, originated from viral genomes, including proviruses, and among the rest, the most common source was genes that are integrated into microbial chromosomes but are involved in plasmid conjugation or replication. Thus, almost all spacers with identifiable protospacers target mobile genetic elements (MGE). The GC content, as well as dinucleotide and tetranucleotide compositions, of microbial genomes, their spacer complements, and the cognate viral genomes showed a nearly perfect correlation and were almost identical. Given the near absence of self-targeting spacers, these findings are most compatible with the possibility that the spacers, including the dark matter, are derived almost completely from the species-specific microbial mobilomes. IMPORTANCEThe principal function of CRISPR-Cas systems is thought to be protection of bacteria and archaea against viruses and other parasitic genetic elements. The CRISPR defense function is mediated by sequences from parasitic elements, known as spacers, that are inserted into CRISPR arrays and then transcribed and employed as guides to identify and inactivate the cognate parasitic genomes. However, only a small fraction of the CRISPR spacers match any sequences in the current databases, and of these, only a minority correspond to known parasitic elements. We show that nearly all spacers with matches originate from viral or plasmid genomes that are either free or have been integrated into the host genome. We further demonstrate that spacers with no matches have the same properties as those of identifiable origins, strongly suggesting that all spacers originate from mobile elements.KEYWORDS CRISPR-Cas, bacteriophages, mobilome, oligonucleotide composition, spacer acquisition C RISPR-Cas (clustered regularly interspaced palindromic repeats and CRISPRassociated proteins) systems are adaptive (acquired) immune systems of archaea and bacteria that store memory of past encounters with foreign DNA in unique spacer Citation Shmakov SA, Sitnik V, Makarova KS, Wolf YI, Severinov KV, Koonin EV. 2017. The CRISPR spacer space is dominated by sequences from species-specific mobilomes.

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Section: Methodsmentioning

confidence: 99%

The CRISPR Spacer Space Is Dominated by Sequences from Species-Specific Mobilomes

Shmakov

Sitnik

Makarova

et al. 2017

mBio

198

195

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“…Six genome scan methods were applied to detect selection signal, and the sequences of all the outlier SNPs were blasted on known annotated genes in the NCBI's nr database (NCBI Resource Coordinators, 2017). The blast analysis identified 30 sequences corresponding to genes.…”

Section: Methodsmentioning

confidence: 99%

Geographic isolation and larval dispersal shape seascape genetic patterns differently according to spatial scale

Dalongeville

Andrello

Mouillot

et al. 2018

Evolutionary Applications

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Genetic variation, as a basis of evolutionary change, allows species to adapt and persist in different climates and environments. Yet, a comprehensive assessment of the drivers of genetic variation at different spatial scales is still missing in marine ecosystems. Here, we investigated the influence of environment, geographic isolation, and larval dispersal on the variation in allele frequencies, using an extensive spatial sampling (47 locations) of the striped red mullet (Mullus surmuletus) in the Mediterranean Sea. Univariate multiple regressions were used to test the influence of environment (salinity and temperature), geographic isolation, and larval dispersal on single nucleotide polymorphism (SNP) allele frequencies. We used Moran's eigenvector maps (db‐MEMs) and asymmetric eigenvector maps (AEMs) to decompose geographic and dispersal distances in predictors representing different spatial scales. We found that salinity and temperature had only a weak effect on the variation in allele frequencies. Our results revealed the predominance of geographic isolation to explain variation in allele frequencies at large spatial scale (>1,000 km), while larval dispersal was the major predictor at smaller spatial scale (<1,000 km). Our findings stress the importance of including spatial scales to understand the drivers of spatial genetic variation. We suggest that larval dispersal allows to maintain gene flows at small to intermediate scale, while at broad scale, genetic variation may be mostly shaped by adult mobility, demographic history, or multigenerational stepping‐stone dispersal. These findings bring out important spatial scale considerations to account for in the design of a protected area network that would efficiently enhance protection and persistence capacity of marine species.

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“…The following resources are currently supported but other resources can be managed by the user by calling the functions mentioned above: Ensembl ( Zerbino et al , 2018): NCBI ( NCBI Resource Coordinators, 2017): Uniprot ( The UniProt Consortium, 2017): Clarivate Analytics MetaBase ® ( Clarivate Analytics, 2017): …”

Section: Methodsmentioning

confidence: 99%

BED: a Biological Entity Dictionary based on a graph data model

Godard

Eyll

2018

F1000Res

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The understanding of molecular processes involved in a specific biological system can be significantly improved by combining and comparing different data sets and knowledge resources. However, these information sources often use different identification systems and an identifier conversion step is required before any integration effort. Mapping between identifiers is often provided by the reference information resources and several tools have been implemented to simplify their use. However, most of these tools do not combine the information provided by individual resources to increase the completeness of the mapping process. Also, deprecated identifiers from former versions of databases are not taken into account. Finally, finding automatically the most relevant path to map identifiers from one scope to the other is often not trivial. The Biological Entity Dictionary (BED) addresses these three challenges by relying on a graph data model describing possible relationships between entities and their identifiers. This model has been implemented using Neo4j and an R package provides functions to query the graph but also to create and feed a custom instance of the database. This design combined with a local installation of the graph database and a cache system make BED very efficient to convert large lists of identifiers.

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Database Resources of the National Center for Biotechnology Information

Cited by 748 publications

References 12 publications

The CRISPR Spacer Space Is Dominated by Sequences from Species-Specific Mobilomes

The CRISPR Spacer Space Is Dominated by Sequences from Species-Specific Mobilomes

Geographic isolation and larval dispersal shape seascape genetic patterns differently according to spatial scale

BED: a Biological Entity Dictionary based on a graph data model

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