Evidence map›Paper›PMID 38394258›Full record

ArticlePloS one2024

Multi-omics data integration for the identification of biomarkers for bull fertility.

Valentin Costes, Eli Sellem, Sylvain Marthey, Chris Hoze, Aurélie Bonnet, Laurent Schibler, Hélène Kiefer, Florence Jaffrezic

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
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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

8 authors.

Valentin CostesUniversité Paris-Saclay, UVSQ, INRAE, BREED, Jouy-en-Josas, France.ORCID 0000-0002-8959-1489
Eli SellemUniversité Paris-Saclay, UVSQ, INRAE, BREED, Jouy-en-Josas, France.
Sylvain MartheyUniversité Paris-Saclay, AgroParisTech, INRAE, GABI, Jouy-en-Josas, France.
Chris HozeR&D Department, ELIANCE, 149 rue de Bercy, Paris, France.ORCID 0000-0002-5900-5506
Aurélie BonnetUniversité Paris-Saclay, UVSQ, INRAE, BREED, Jouy-en-Josas, France.
Laurent SchiblerR&D Department, ELIANCE, 149 rue de Bercy, Paris, France.
Hélène KieferUniversité Paris-Saclay, UVSQ, INRAE, BREED, Jouy-en-Josas, France.
Florence JaffrezicUniversité Paris-Saclay, AgroParisTech, INRAE, GABI, Jouy-en-Josas, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bull fertility is an important economic trait, and the use of subfertile semen for artificial insemination decreases the global efficiency of the breeding sector. Although the analysis of semen functional parameters can help to identify infertile bulls, no tools are currently available to enable precise predictions and prevent the commercialization of subfertile semen. Because male fertility is a multifactorial phenotype that is dependent on genetic, epigenetic, physiological and environmental factors, we hypothesized that an integrative analysis might help to refine our knowledge and understanding of bull fertility. We combined -omics data (genotypes, sperm DNA methylation at CpGs and sperm small non-coding RNAs) and semen parameters measured on a large cohort of 98 Montbéliarde bulls with contrasting fertility levels. Multiple Factor Analysis was conducted to study the links between the datasets and fertility. Four methodologies were then considered to identify the features linked to bull fertility variation: Logistic Lasso, Random Forest, Gradient Boosting and Neural Networks. Finally, the features selected by these methods were annotated in terms of genes, to conduct functional enrichment analyses. The less relevant features in -omics data were filtered out, and MFA was run on the remaining 12,006 features, including the 11 semen parameters and a balanced proportion of each type of-omics data. The results showed that unlike the semen parameters studied the-omics datasets were related to fertility. Biomarkers related to bull fertility were selected using the four methodologies mentioned above. The most contributory CpGs, SNPs and miRNAs targeted genes were all found to be involved in development. Interestingly, fragments derived from ribosomal RNAs were overrepresented among the selected features, suggesting roles in male fertility. These markers could be used in the future to identify subfertile bulls in order to increase the global efficiency of the breeding sector.

Indexed as

InfertilitySemenAnimalsBiomarkersCattleFertilityHumansMaleMultiomicsSemen AnalysisSpermatozoaBiomarkers

Identifiers

PMID38394258
PMCPMC10890740

What Socratic 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 Socratic graph.