Evidence map›Paper›PMID 42550352›Full record

ReviewAdvanced biotechnology2026

Engineering monosex and sterile fish for food production: from conventional methods to CRISPR-based precision.

Yue Min, Fei Sun, Joey Wong, May Lee, Gen Hua Yue

Abstract readReview
In one paragraph

Review in Advanced biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yue MinTemasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, SG, 117604, Singapore.
Fei SunTemasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, SG, 117604, Singapore.
Joey WongTemasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, SG, 117604, Singapore.
May LeeTemasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, SG, 117604, Singapore.
Gen Hua YueTemasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, SG, 117604, Singapore. genhua@tll.org.sg.ORCID http://orcid.org/0000-0002-3537-2248

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monosex and sterile fish populations are increasingly recognized as essential tools for enhancing aquaculture productivity while safeguarding ecosystems from genetic introgression and uncontrolled reproduction. Conventional approaches such as hormonal manipulation and triploidy have demonstrated utility but face persistent limitations in efficiency, welfare, and regulatory acceptance. Recent breakthroughs in CRISPR-based genome editing and germ cell transplantation now enable heritable, scalable, and biocontained control of sex and fertility, offering transformative potential for sustainable aquaculture. This paper synthesizes advances across finfish and crustaceans, critically evaluates technical and regulatory bottlenecks, and highlights convergent solutions integrating automation, artificial intelligence, and governance frameworks. By positioning reproductive programming as a cornerstone of climate-resilient and sustainable aquatic food systems, we propose a roadmap toward commercial adoption that balances biological precision, ecological safety, and societal acceptance.

Indexed as

Genome editingGerm cell transplantationMonosex productionReproductive biocontainmentSustainable aquaculture

Identifiers

PMID42550352
PMCPMC13438497

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.