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Novel classifier orthologs of bovine and human oocytes matured in different melatonin environments.

Theriogenology
January 1, 1970
Thanida Sananmuang et al. (4 authors)
Journal ArticleMeta-AnalysisHuman StudyAnimal StudyMolecular Study
Study Details

Study Goal

The researchers aimed to identify classifier orthologs that could universally categorize oocytes matured in environments with varying melatonin levels across mammalian species.

Results Summary

The study identified 15 verified orthologs differentially expressed between low and high melatonin environments, which accurately classified oocytes based on melatonin levels using SVM (misclassification rates < 0.18, AUC > 0.9). These orthologs may help assess melatonin sufficiency in oocytes and guide supplementation decisions.

Population

In vitro matured bovine oocytes and in vivo matured human oocytes (from young and old patients).

Effective Dosage

10^-9 M melatonin for bovine oocytes (human dosage not specified).

Duration

Not specified.

Interactions

None mentioned.

Extracted Claims (3)
InterventionDirectionEndpointPopulationDosageImpactClaim #
melatonin
neutral
developmental competence
in vivo and in vitro matured oocytes
-
influences
#1
melatonin
neutral
oocyte-specific gene expression patterns
mammalian species
-
modulates
#2
melatonin supplementation
neutral
melatonin sufficiency in target oocytes
-
-
could be implied
#3
Abstract

It has been demonstrated that melatonin influences the developmental competence of both in vivo and in vitro matured oocytes. It modulates oocyte-specific gene expression patterns among mammalian species. Due to differences among study systems, the identification of the classifier orthologs-the homologous genes related among mammals that could universally categorize oocytes matured in environments with varied melatonin levels is still limitedly studied. To gain insight into such orthologs, cross-species transcription profiling meta-analysis of in vitro matured bovine oocytes and in vivo matured human oocytes in low and high melatonin environments was demonstrated in the current study. RNA-Seq data of bovine and human oocytes were retrieved from the Sequence Read Archive database and pre-processed. The used datasets of bovine oocytes obtained from culturing in the absence of melatonin and human oocytes from old patients were regarded as oocytes in the low melatonin environment (Low). Datasets from bovine oocytes cultured in 10-9 M melatonin and human oocytes from young patients were considered as oocytes in the high melatonin environment (High). Candidate orthologs differentially expressed between Low and High melatonin environments were selected by a linear model, and were further verified by Zero-inflated regression analysis. Support Vector Machine (SVM) was applied to determine the potentials of the verified orthologs as classifiers of melatonin environments. According to the acquired results, linear model analysis identified 284 candidate orthologs differentially expressed between Low and High melatonin environments. Among them, only 15 candidate orthologs were verified by Zero-inflated regression analysis (FDR ≤ 0.05). Utilization of the verified orthologs as classifiers in SVM resulted in the precise classification of oocyte learning datasets according to their melatonin environments (Misclassification rates < 0.18, area under curves > 0.9). In conclusion, the cross-species RNA-Seq meta-analysis to identify novel classifier orthologs of matured oocytes under different melatonin environments was successfully demonstrated in this study-delivering candidate orthologs for future studies at biological levels. Such verified orthologs might provide valuable evidence about melatonin sufficiency in target oocytes-by which, the decision on melatonin supplementation could be implied.

Medical Subject Headings (MeSH)
AnimalsCattleGene ExpressionHumansMelatoninOocytes
Study Links
Quality Scores
SafetyNot Assessed
Efficacy75/10
Quality85/10
Citation Metrics
Total Citations4
Citations/Year0.8
Relative Citation Ratio0.35
NIH Percentile18.8%
Research Impact Scores
APT Score0.25
Weight Score0.80
Normalized Score0.67
Related Supplements
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