RDL logo
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
​
​
Sign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2025 Raw Data Library. All rights reserved.
PrivacyTerms
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Widespread and Abundant CRISPR-Cas Systems in the Deep Ocean

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Preprint
en
2025

Widespread and Abundant CRISPR-Cas Systems in the Deep Ocean

0 Datasets

0 Files

en
2025
DOI: 10.1101/2025.05.26.656144

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Carlos M. Duarte
Carlos M. Duarte

King Abdullah University of Science and Technology

Verified
Takashi Gojobori
Susana Agustı́
Carlos M. Duarte
+11 more

Abstract

CRISPR-Cas systems have revolutionized modern biology. Most CRISPR-Cas systems in use for biotechnological applications derive from cultivated bacteria, but evidence suggests that environmental microbiomes harbor a large untapped diversity of these systems. Yet, our understanding of which environmental and biological factors drive the prevalence of CRISPR-Cas systems in the oceans remains limited. A search for CRISPR-Cas systems was conducted among 176 globally-distributed marine microbial metagenomes from the Malaspina expedition, which sampled both free-living and particle-attached microbiomes with emphasis on the deep ocean. We show that CRISPR-Cas systems are proportionally more abundant among microbiomes from the deep ocean than in the photic layers and among free-living microbes compared to those attached to particles, reflecting the higher concentrations of archaea and their viruses in these habitats. We identified 1,146 CRISPR-cas loci, some of which displayed unique loci architectures. From these loci, a total of 48 Cas9 proteins were identified, many of which are potentially novel. These discoveries expand the scope of CRISPR-Cas diversity and point at the deep-sea as a rich reservoir of these resources, which helps guide future bioprospecting efforts.

How to cite this publication

Takashi Gojobori, Susana Agustı́, Carlos M. Duarte, Francisco J. M. Mojica, Julián Cerón, Felipe H. Coutinho, Silvia G. Acinas, Pablo Sánchez, Marta Ferri-Peradalta, E. García, Raúl Ruiz, Belen Esquerra Ruvira, Josep M. Gasol, Dolors Vaqué (2025). Widespread and Abundant CRISPR-Cas Systems in the Deep Ocean. , DOI: https://doi.org/10.1101/2025.05.26.656144.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Preprint

Year

2025

Authors

14

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1101/2025.05.26.656144

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access