Evidence map›Paper›PMID 40021804›Full record

ArticleScientific reports2025

SHIP identifies genomic safe harbors in eukaryotic organisms using genomic general feature annotation.

Matheus de Castro Leitão, Letícia Sousa Cabral, Luiza Cesca Piva, Pedro Felipe de Sousa Queiroz, Taísa Godoy Gomes, Rosângela Vieira de Andrade, Ana Laura Alfonso Perez, Karen Letycia Rodrigues de Paiva, Sônia Nair Báo, Viviane Castelo Branco Reis and 6 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

16 authors.

Matheus de Castro LeitãoDepartment of Genetics and Morphology, University of Brasilia, Brasilia, Brazil.
Letícia Sousa CabralDepartment of Genetics and Morphology, University of Brasilia, Brasilia, Brazil.
Luiza Cesca PivaDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Pedro Felipe de Sousa QueirozDepartment of Genetics and Morphology, University of Brasilia, Brasilia, Brazil.
Taísa Godoy GomesDepartment of Microbiology, University of Brasilia, Brasilia, Brazil.
Rosângela Vieira de AndradeCatholic University of Brasilia, Brasilia, Brazil.
Ana Laura Alfonso PerezDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Karen Letycia Rodrigues de PaivaDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Sônia Nair BáoDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Viviane Castelo Branco ReisDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Lídia Maria Pepe MoraesDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Roberto Coiti TogawaGenetic Resources and Biotechnology, CENARGEN, Embrapa, Brasilia, Brazil.
Leila Maria Gomes BarrosGenetic Resources and Biotechnology, CENARGEN, Embrapa, Brasilia, Brazil.
Fernando Araripe Gonçalves TorresDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil.
Georgios Joannis Pappas JúniorDepartment of Cell Biology, University of Brasilia, Brasilia, Brazil. gpappas@unb.br.
Cíntia Marques CoelhoDepartment of Genetics and Morphology, University of Brasilia, Brasilia, Brazil. cintiacoelhom@unb.br.

Funding

Research Support Foundation of the Federal District (FAP-DF) 00193-00000858/2021-51
6 · The paper itself

Abstract

Integrating foreign genes into loci, allowing their transcription without affecting endogenous gene expression, is the desirable strategy in genomic engineering. However, these loci, known as genomic safe harbors (GSHs), have been mainly identified by empirical methods. Furthermore, the most prominent available GSHs are localized within regions of high gene density, raising concerns about unstable expression. As synthetic biology is moving towards investigating polygenic modules rather than single genes, there is an increasing demand for tools to identify GSHs systematically. To expand the GSH repertoire, we present SHIP, an algorithm designed to detect potential GSHs in eukaryotes. Using the chassis organism Saccharomyces cerevisiae, five GSHs were experimentally curated based on data from DNA sequencing, stability, flow cytometry, qPCR, electron microscopy, RT-qPCR, and RNA-Seq assays. Our study places SHIP as a valuable tool for providing a list of promising candidates to assist in the experimental assessment of GSHs in eukaryotic organisms with available annotated genomes.

Indexed as

Genome, FungalGenomicsSaccharomyces cerevisiaeAlgorithmsMolecular Sequence Annotation

Identifiers

PMID40021804
PMCPMC11871141

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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.