Evidence map›Paper›PMID 40828283›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Identification of Sex-Specific and Sex-Biased Transcripts for Genetic Sexing.

Serena Aceto, Stefano Perrini, Marianna Varone, Francesca Lucibelli, Gennaro Volpe, Paola Di Lillo, Angela Carfora, Sarah Maria Mazzucchiello, Giuseppe Saccone, Marco Salvemini

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Serena AcetoDepartment of Biology, University of Naples Federico II, Naples, Italy.
Stefano PerriniDepartment of Biology, University of Naples Federico II, Naples, Italy.
Marianna VaroneDepartment of Biology, University of Naples Federico II, Naples, Italy.
Francesca LucibelliDepartment of Biology, University of Naples Federico II, Naples, Italy.
Gennaro VolpeDepartment of Biology, University of Naples Federico II, Naples, Italy.
Paola Di LilloDepartment of Biology, University of Naples Federico II, Naples, Italy.
Angela CarforaDepartment of Biology, University of Naples Federico II, Naples, Italy.
Sarah Maria MazzucchielloDepartment of Biology, University of Naples Federico II, Naples, Italy.
Giuseppe SacconeDepartment of Biology, University of Naples Federico II, Naples, Italy.
Marco SalveminiDepartment of Biology, University of Naples Federico II, Naples, Italy. marco.salvemini@unina.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sex-specific transcripts are RNA molecules expressed predominantly or exclusively in one sex, providing insights into molecular and physiological differences between males and females. This knowledge underpins the development of precise and efficient genetic sexing methods applicable in various contexts. In agriculture and livestock management, early sex determination could enhance resource management and productivity. In ecology and conservation, genetic sexing informs population monitoring and species management. In applied entomology, it could improve biological control strategies, such as the sterile insect technique. Here, we describe a bioinformatic framework to identify sex-specific transcripts using RNA-seq sequencing data in eukaryotic species with or without a sequenced reference genome.

Indexed as

Computational BiologySex Determination AnalysisTranscriptomeAnimalsFemaleMaleBioinformaticsBiological controlGenetic sexingNext-generation sequencingSex-specific transcriptsTranscriptomics

Identifiers

PMID40828283

What OpenQuestion holds

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Registered trials

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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.